Monthly Archives: February 2017

Episode #40: “Listener Q&A”

Episode #40: “Listener Q&A”

 

Guest: Episode #40 has no guest, but is co-hosted by Meb’s co-worker, Jeff Remsburg.

Date Recorded: 2/14/16     |     Run-Time: 51:29


Summary:  We’ve had some great guests recently, and have many more coming up, so we decided to slip in a quick Q&A episode. No significant, recent travel for Meb, so we dive into questions quickly. A few you’ll hear tackled are:

  • Some folks talk about how the inflation numbers are manipulated by the government, and how the calculations have changed. Is there any merit to this?
  • What is your opinion on market neutral strategies? If you had to build a market neutral ETF, what strategy would you use?
  • Your buddy, Josh Brown, indicates that a significant portion of valuations, specifically CAPE, are the confidence in the stability of the stock market, which will justify high valuations here in the U.S. This makes intuitive sense, but I’d like your thoughts.
  • Have you given any thought to the application of a trend following approach over a lifetime? Specially, use buy-and-hold when younger, but move to trend as one approaches retirement?
  • Based on your whitepapers, you’ve indicated that trend following is not designed to increase returns, but rather, to limit/protect your portfolio from drawdowns. If this is the case, how does an increase in the allocation toward trend in your Trinity portfolios correlate to a more aggressive portfolio? It seems if “more trend” is supposed to reduce drawdowns, it should be found in Trinity 1 instead of Trinity 6.
  • Have you done any research on earnings growth rates compared with CAPE to get a more accurate indicator of expected returns? For example, while the CAPE for many countries in Europe is low, their growth rates are also considerably lower than the U.S., which could justify the lower CAPE as compared with the U.S. Your thoughts?
  • Does your “down 5 years in a row” rule apply to uranium, or is it too small?

As usual, there’s plenty more, including a listener wondering why Meb didn’t challenge Rob Arnott on a discussion topic during Rob’s episode, why Meb is in a cranky mood (involves auditing), and a request for more gifts of tequila from listeners. All this and more in Episode 40.


Episode Sponsor: The Idea Farm and Global Financial Data


Comments or suggestions? Email us Feedback@TheMebFaberShow.com

Transcript of Episode 40:

Welcome Message: Welcome to the “Meb Faber Show” where the focus is on helping you grow and preserve your wealth. Join us as we discuss the craft of investing and uncover new and profitable ideas all to help you grow wealthier and wiser. Better investing starts here.

Disclaimer: Meb Faber is the co-founder and chief investment officer at Cambria Investment Management. Due to industry regulations, he will not discuss and of Cambria’s funds on this podcast. All opinions expressed by podcast participants are solely their own opinions and do not reflect the opinion of Cambria Investment Management or its affiliates. For more information, visit cambriainvestment.com.

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Meb: Happy Valentine’s Day, podcast listeners, we got Jeff Remsburg in the studio for a co-host. Jeff, welcome.

Jeff: What’s happening?

Meb: Jeff that’s a new version.

Jeff: Jeff.

Meb: I’m in somewhat of a foul mood, you seem to be in a pretty good mood. A reader sent in a bottle of tequila… Reader. I keep saying “reader”. Because I’ve been blogging for 10 years, I keep saying “reader”. A listener sent us a bottle of good tequila, so Jeff’s happy, he loves tequila. So you podcast listeners, keep sending Jeff booze, he’ll keep this podcast rolling.

Jeff: The rule is we have to drink it in the office, though, so.

Meb: Okay, well the…what was it? Was it Anejo, [SP] Blanco?

Jeff: I think it was Anejo, I believe, wasn’t Blanco.

Meb: You know what the third one is?

[Crosstalk]

Meb: Respesado.

Jeff: Reposado.

Meb: Reposado. It’s a desperado is what it is. I’m in a foul mood because we’ve been through a lotta audits recently and I’m now doing GIPS auditing and it’s just sort of mindless, terrible, miserable. But podcast has taken us away from that, we’ve had some good ones lately, Ed Thorp and John Bollinger’s I thought went great. Really interesting guys, old school market historians. You can listen to those and probably find 10 new things each time you listen to ’em. So we thought we’d break it up, do a Q&A episode. You guys remember to keep sending us questions, we’ve been having a lotta great ones, so we’ll read them on air live. And Jeff, looks like you got a whole stack, so why don’t we jump right in?

Jeff: Yeah, we got some great ones, so we’ll just dive in, see how far we can get.

Meb: And it’s feedback@themebfabershow.com.

Jeff: All right, number one, one that I thought was pretty insightful here. Based on your white papers, blog, and podcasts you’ve indicated that trend following is not designed to increase returns but rather to limit and protect your portfolio from massive drawdowns at buy and hold experiences. If this is the case, how does an increase in allocation toward trend following and the six Trinity Portfolios correlate to more aggressive return seeking portfolio? It would seem that if trend following is designed to reduce drawdowns rather than increase returns, an increase in trend following allocation would be present in Trinity 1 versus Trinity 6. Love your input.

Meb: Well, you know, same trend following alone is…we often say it’s like saying “dog”, where, you know, a Dachshund looks different than a Rottweiler and so there’s a lot of different flavors of trend following. At its core, if you just overlay a moving average on something, historically speaking, on one asset class, yes, that likely what it’s gonna do is reduce risk and volatility. It may increase returns, it may hurt returns, but in general it improves your Sharpe ratio, decreases volatility in drawdown. So it’s risk reduction. But there’s lots of ways you can do trend following as a way [inaudible 00:04:12] shops do it, a more concentrated approach where say for example you’re using a dual momentum approach, what a lotta people talk about now, where you sort on momentum and concentrate in what’s going up the most and then overlay the trend following, and that is actually much more of an out performance style strategy historically.

So there’s a lotta different ways you could do it. The base case when I say it’s not return enhancing, I mean, at its core, overlaying a moving average on say one asset class is not return enhancing. So, if you put together a portfolio, and we did this on our white paper Trinity Portfolio near the appendix, and if you read the first version, you probably wanna update and read the second version, the 2.0, because it, I think, left out some of these charts and tables that we put in there after a lotta people had requested them, is that if you have a spectrum of portfolios and on the left side it’s the most in buy and hold and on the right side it’s the most in trend following, you know…and another way to think about it that we do in practice is on the left side is the most in bonds and the right is the least in bonds and the most in trend following, same sorta thing. Philosophically speaking, yes, in general, trend following has had a lower drawdown than buy and hold. However, bonds have also historically had a lower drawdown than equities. And so there’s sorta two main levers and when you combine them, I think you still end up on the correct spectrum. It’s how much do you have in low vol fixed-income or bonds and how much do you have in traditional buy and hold assets versus trend following assets. And so as you move to the right on that spectrum, you start to look a lot different. You know, it’s not necessarily that it’s gonna be more risky, though it is more volatile, the spectrum goes from low volatility to high volatility as measured by standard deviation, the drawdown…

Jeff: But if you’re using trend following to try to reduce some of that to get you out of markets that are rapidly changing directions assuming you’re not being whipsawed around, wouldn’t you sort of step out of the way some of that volatility?

Meb: Theoretically yes, but you gotta remember that’s coming at the expense of bonds. So bonds are lower vol than the asset class exposure that the trend following funds are targeting. So, you know, 5 year T-bills, low…you know, 10 year even bonds probably lower vol than the trend following portfolio in general. It just depends. Now the problem with this is that people are gonna look at the next month, three years, five years, and it’s gonna completely color their experience. And so whether or not the aggressive portfolios have lower or higher draw…and same thing if you just did a traditional equities and bonds split. I mean, you could have a scenario where the 100% equities or 80% equities, 20% bonds has a lower drawdown than 80% bonds and 20% equities. I mean, look at last year probably, I don’t know that, I’m just speaking off the top of my head, bonds got whacked over a certain period when they bottomed…interest rates bottomed I think maybe in the summer and started running up and then equities did just fine. So if you had a portfolio that was heavy on bonds which you expected to be lower vol or drawdown, that’s not what happened. Over the long-term, it’ll be interesting to see. But it’s a good question. I don’t like to say that by the way, I don’t like to say, “That’s a good question.”

Jeff: Well done, listener.

Meb: I was told by our PR people in the early days, they said when someone asks you a question, don’t immediately say that’s a good question, because you’re buying time. And then it also implies that all the other questions are terrible, but now I’ve gotten in the mindset to never say “good question”. So good question.

Jeff: Well on a side note, you mentioned applying the strategy to basically equities and the fact that bonds are…they would dampen the portfolio a bit or dampen the volatility. Have you ever thought about using trend following on bonds?

Meb: There’s a couple things in there. One is… So not to get too complicated, because on these podcasts it’s a little hard to talk about without numbers. You wanna go step farther and talk about those…the spectrum of returns for portfolios, with equities, and bonds, it gets even more complicated when you start talking about real returns. Because bonds, you know, for example, 10 year U.S. bonds you say on a nominal basis maybe only have a 20% drawdown and stocks is 80 plus. On a real basis, bonds have declined 50% because of inflation. They look much more risky when you think in terms of real, and then once you think in portfolio terms of real, it evens it out even more. So it’s an even more complicated question that I think that the reader even intended.

Trend following on bonds, look, everyone does it, fixed income, different markets, all the trend following funds do it. It’s historically if you’re just trend following in an account, not using futures, not using leverage on, like, 10 year bonds and less, I don’t think matters at all. I think it’s probably a waste of time. It may matter in the short-term, you may miss a rise in rate environment, but they’re just not volatile enough. Now if you’re leveraging them, if you’re doing them as part of the leverage portfolio, that’s different, but say junk bonds, emerging market debt, corporate bonds, it works great, trend following has. But those are also more and more volatile.

Jeff: Be curious to see in, you know, a decade or two if we look back at now as an inflection point where if you were using it, you would get outta the way of a significant rise in rate environment for a while.

Meb: Well, that’s what everyone’s been expecting for about 10 years, but you also gotta think about the flipside. What if interest rates continue declining? What if we see…

Jeff: Japan.

Meb: What if we see negative rates in the U.S.? You know, I mean that’s what no one really expects, but I don’t see why that’s not at least a possibility.

Jeff: Well speaking of inflation, that segues into another question which is good. You hear some folks, for instance, Shadowstats or Zero Hedge talk about how the inflation numbers are manipulated and how the calculations have changed. Is there any merit to this?

Meb: All of our conspiracy theory listeners’ ears just perked up. Look, have the calculations changed over time, the same as GDP, the same as valuation metrics, almost anything? Yes. And I think at some point you have to take a honest assessment, has it done enough to make a difference? And one of my favorite examples of this was a project, I think it was MIT, where it was called Price Stats maybe or the Price Discovery Project or something. I’m murdering this, I apologize, we’ll put it in the show notes. Where it was a group that was started to measure inflation just by comparing… Oh, The Billion Price Project I think it’s what it called. And they would just look at prices on the Internet for various goods and then compute CPI basket. And lo and behold, guess what? PEG [SP] CPI, almost exactly in the U.S. And so a lot of the people that, you know, are freaking out about the government and all the manipulation is trying to do for whatever reason, you know, turned out that it’s actually a pretty fairly accurate measure. And someone bought them, and I think it’s Sachsen [SP] or Credit Suisse, one of the banks now has it. But…because I think it’s called Price Stats, and it’s a pretty cool indicator and it’s also likely a leading indicator because I think it’s comes out more than CPI, and you can see in real time when it’s moving up or moving down. But we’ll added it to the show notes, I can’t remember the exact name of it. So I don’t sweat it, but, you know, I also don’t spend a ton of time…it’s not something I would spend a ton of time with.

Jeff: I remember years ago in my past life, we were writing an article on this and there’s a “Forbes” article back in I think 2014 maybe, said that the government has changed how they calculate inflation more than 20 times in the past 30 years. That’s not to say it’s been consequential ever single time, could be just tweaks, but they’re definitely manipulating it.

Meb: Well, they kicked out horseback riding as a means of transportation and everything else. I mean, of course it’s gonna change, I just…I don’t know that it’s like some conspiracy theory that it’s under reported by 5% a year.

Jeff: What’s interesting, other people’s takes on it, I think one of your past guests, Porter, I might butcher this, but I think he has his own somewhat proprietary or sort of rule of thumb heuristic. He just looks at like the Ford F-150, the cost of it, and uses that sort of as a proxy for various inflation measures.

Meb: Yeah. I mean, either way it feels…you know, and it’s also…it’s highly dependent on what your lifestyle is and what you’re spending on, you know, whether it’s healthcare, education. If you’re buying a computer and TV, it’s been…tech has a massive deflationary impact in general. And, you know, there’s other areas, college education, etc., that’s had high inflation. So there is no one just inflation basket so a wealthy person has a totally different inflation rate then someone who makes 20 grand a year. So you can look at the broad based economic inflation, but it’s also very hugely individual exposed depending on what you spend money on.

Jeff: Yeah, there’s a heavy skew with that technology. There’s some story anecdote about somebody complaining about the fact that inflation wasn’t capturing the rise in cost of living. And some expert had said, “Well, you know, look at your new iPad. You have twice the computing power that you did, you know, 10 years ago or 2 years ago even.” And the guy said, “Well I can’t eat my iPad.” All right, next question. What is your opinion on market neutral strategies? If you had to build a market neutral ETF, what strategy would you use?

Meb: Ed Thorp essentially in the last episode, if you haven’t listened to it, it’s great, you know, built his entire career around market neutral strategies.

Jeff: Back up just for anybody who’s not really fully aware. Just give a quick definition.

Meb: No, I’m not… Oh, I thought that you said give a overview of that, I said too bad, you’re gonna have to go listen to the podcast. I mean, market neutral is essentially…the goal is to have no overall exposure beta to the market. So if you’re a hedge fund that had a 100% long book and 100% short book, the goal being way back all the way to Alfred Winslow Jones in the 30s whenever he did his first hedge fund…is it Alfred Winslow Jones? Man, I’m mispronouncing words right and left today. You know, he started the world’s truly first hedged fund because the goal was to have a long position and a short position, they cancel out the overall effects in the market, and if you’re a good stock picker, you should make money no matter which way the market goes. Theoretically it’s great idea, right? The challenge of course is that it’s not that easy and it’s gotten harder over the years to be able to pick both longs and shorts, but it doesn’t mean that there’s not ways it couldn’t be done. I mean, we’ve written posts on this in the past. We wrote one…gosh, called something along the lines of, you know, “A Market Neutral System and How to Fix It” or something. And the problem with most market neutral systems is that they have no market beta exposure and the market goes up 5%, 10% a year, right? So there’s a natural headwind.

So you want in general, I think, a intelligent exposure to that tailwind. And so here’s an example. So I think the test we ran was a very common factor, something like buying high momentum stocks and short and low momentum stocks, very common, well known factor. You can get data on this back to the ’20s, same thing with value on the [inaudible 00:15:36] database, it’s free. You can download the monthly returns, and I think I did something like this, I said, “All right, if the market’s at an all-time high, you’re totally market neutral.” And for every 10% the market goes down, you reduce to short book. So the theory being is that when the market’s down 50%, you don’t wanna still be 100% short, you wanna be reducing your short. And the market’s down 80%, you really, really don’t wanna have huge short exposure because usually at market bottoms, the shorts, the really junky stuff, the stuff that’s down to a dollar, you know, is gonna rip, and it’s gonna double, and triple and that you have a lotta pain on the short side.

So we ran that test and it worked out great. So, I mean, that’s an example of a dynamic sorta market neutral. The problem you run into then of course, is you lose a little bit of the comfort of it being market neutral. So, you know, let’s say you start reducing all your shorts when you’re down 40%, 50% and all of a sudden the market goes down 50% again, like in Greece, or Russia, or Brazil, or something. So, you know, I don’t think there’s any magical solution, there’s a lotta different flavors to it. I don’t have any problem with it. I don’t think I will allocate to any market neutral systems, but I would [inaudible 00:16:50], I would totally be happy to.

Jeff: Well how would you balance a market neutral strategy in a broader portfolio where you might wanna also have specific factor-based strategies? I mean, is it just up to the engineer to say, “Well all right, let’s say 20% it’s gonna be market neutral, 80% when you go to XYZ,”?

Meb: Well the market neutral could be factor-based, so you could do a market neutral fund that buys value stocks and shorts expensive ones. That’s a factor-based market neutral. You can also buy a portfolio that’s just long value stocks and that’s 100% exposed long. So you could design it in any way you want, and there’s…you know, a lotta family offices prefer long/short equity and market neutral because it’s a little lower volatility. You know, the challenge, like anything, is finding ones that outperform, is can you find a long/short equity manager strategy or market neutral that can outperform, otherwise why not just buy bonds and be done with it?

Jeff: Well just sorta pushing for a new super conservative investors out there, you know, retail investors, what’s sort of a good conservative market neutral approach they could apply to, you know, try not to suffer any significant drawdowns and still stay somewhat long?

Meb: Buy some CDs. I’m serious, I don’t think most people should be going and buying expensive…and most would be expensive. Look, I’m sure there’s a lot of alt funds out there, and I spend almost zero time researching them, so it’s not like I can say, “Hey, you need to buy this fund from research affiliates, or AQR, LSV, or, like, one of these shops.” You know, I just…I don’t…I’m not that familiar. I’m sure there’s some good ones out there. And then…but market neutral can also mean something, you know, much more nefarious. It could be something like long-term capital that leverages up 50 or 100 to 1 and theoretically is market neutral, but because of the leverage, all of the sudden becomes a very aggressive fund. So it’s not…just saying market neutral doesn’t mean aggressive or conservative, it just means people are trying to line up positions on each side, and the best way…so, like, talking about Thorp’s, that’s the dream market neutral portfolio, that it goes on for 20 years, it has 3 down months out of whatever it was, 230, and those down months were all less than 1%. Like, that’s the market neutral portfolio you what.

The problem is because of Ed Thorp and everyone like him, there’s 10,000 quants with PhDs from MIT that all wanna make hundreds of millions as well. So they all now have the same database, and we talked about this a little bit on, I think the podcast, when he said you type in a traditional multi-factor stock that’s attractive from a multi-factor model that’s cheap, and high quality, and good momentum, and it’s got all the good factors, and every single quant shop owns it. So the edge there is gone and it’s harder, and so you need to start thinking about either more esoteric asset classes and factors or to try to be…we have a friend that says the alpha in this world of hyperactive trading and all the edges having been worn away by these, you know, PhDs and quant shops, is to actually get more dumb. Meaning, move out to a time frame that you can still take advantage of the large behavioral biases of large bear markets and people acting foolishly in crowds at extremes. Problem is that just plays out on a much longer time horizon. So if you can find a good RRB, mail us in, we’ll add it to the podcast.

Jeff: You mentioned research affiliates and your response there, so I’m just honing in on keywords, that leads us to another question. A listener is listening to our past podcasts, and the one with the Rob Arnott from Research Affiliates, Rob had said something which the listener found interesting which you Meb didn’t challenge. The listener wants your thoughts on it. Rob’s quote was, “Managed futures are not an investment in any asset class. People think of it as a commodities investment, it’s not, it’s zero. It’s long some commodities, short other commodities. For most managed future strategies, what it really is is a momentum strategy that chases what’s newly beloved and has performed well on a bet on manager skill. And if you got a great managed futures manager, it’s gonna be marvelous. If you’ve got an average managed futures manager, it’s gonna go nowhere for you. It’s not an asset class, it’s a bet on whether the manager or the algorithm has merit.”

Meb: I’m gonna channel Charlie Munger who I’m going to see tomorrow, at the meeting he’s the chairman at the newspaper he owns, I forget what it’s called. Anyway, I’m gonna channel him and just say I actually agree with him.

Jeff: Done and done?

Meb: No, well, yeah, I can, I always wanna add more. I mean, look, I agree it’s not an asset class. It’s…there’s really only four asset classes: stocks, bonds, commodities, and currencies, and almost everything else is an amalgamation of those or an active strategy using those four. So you could argue that real estate is an asset class, but really it’s a mix of equity and debt, same thing with corporate bonds. Managed futures is simply trading positions long and short on, you know, that many try to do 50 to 100 global asset classes, and industries, and sectors, you know, does that approach which..and again, managed futures means many things, but 80% of managed futures is probably trend following. So does trend following have an inherent return structure? And I think it does, but yes, it will be dependent on the system and algorithm or manager you pick and how much you pay for it.

Now, my belief is that most of them do the same thing. You know, could you pick one that does terrible and one that does amazing. And if you look at the dispersion in 2016 for example, managed futures didn’t have a very good year. I think the average return was probably somewhere around zero, if not negative. But there was funds that put up plus 10%, 20%, minus 10%, 20% on each side. So very clearly their trading different markets have different algorithms. But in general if you pull up charts of the mutual funds or hedge funds that do it, they have on average, a fairly similar equity curve over time, particularly if you compare it to a traditional asset class like stocks or bonds.

Jeff: Wait, was that dispersion based upon…you’re saying different asset classes or was that purely based upon different manager skill level? Because it’s a little frightening to think that you could have a range of…

Meb: Your manager skill for most these guys is an algorithm. It’s not, you know, Paul Tudor Jones showing up tomorrow and saying, “You know what? We need to short gold.” In his case it might be, but for the managed future shops, it’s traditionally not, it’s an algorithm. So for Harding, and Winton, and, you know, Dunn and these guys, they have systems and so it’s one of them may target 20 markets with 50% in interest rates and fixed income, another may target 100 market…global markets with only 10% to fixed income. So it’s the same as if you said, “Hey, look, there’s 100 equity managers that are very concentrated and active, and one was up 20 last year and one was down 20.” You could come up with a quant system that would be in either of those scenarios, but the vast majority of them tend to move together.

Jeff: Buyer beware.

Meb: Well it’s same with anything. I mean, you buy a quant stock fund. So it’s…let’s say you have a quant stock fund that picks 10 stocks out of the S&P 500. One is dogs of the Dow, buys the 10 highest dividend stocks. Another is what we called cash cows of the Dow, shareholder yield, right? Another one is does that stock begin with the letter A?

Jeff: To what extent are the managed futures algorithms as transparent as buying dogs of the Dow? I mean, can you get 100% awareness of what they’re doing strategy-wise…

Meb: Some of them.

Jeff: …or are you kind of guessing?

Meb: I mean some of them. Like some of the funds are index-based and pretty darn transparent about it. So like ETFs, you can look up their holdings every day. Mutual funds, you can look them up, you know, once a quarter. And so they’re…like, if you go into AQRs or any of these sites that have managed future fact sheets, they’ll say, “Look, here’s our asset allocation, we’re gonna target 25% risk in each of these four buckets. Here’s the contracts we’re gonna trade and here’s what we’re gonna do.” You know, and will they say, “Look, here’s our exact system,”? Probably not. But most of them, you know, are fairly transparent about their process. Now some aren’t, and then the ones that…there’s also plenty of managed futures [inaudible 00:25:36] shops that also have a subjective element. So they’re not all pure algorithmic either.

Jeff: Well that’s what sorta freaks me out just a little bit, is, I mean, at Thorp you asked him a question, how do you know when your factor has lost efficacy and it’s time to bail versus when will reversion to the mean kick in? And if you’re dealing with a managed future strategy that’s largely black box in nature and you can’t really tell the definition of what they’re doing, then how do you know whether down times are reflective of what’s within the normal rate of possibility for a loss versus when is something materially changed?

Meb: Well you looked at history and you can come up with simulations, but, I mean, again, equity’s lost over 80%. So, you know, the U.S. stocks in 1930s, would you then claim that equities are a broken asset class that you should never allocate to?

Jeff: Yeah, I’d be out since the ’30s.

Meb: Yeah, you definitely would. You would’ve been knocked out in ’29 by selling options and on…

Jeff: Then long calls.

Meb: Who knows what.

Jeff: All right, next question is a bit long so I’m gonna condense it a little bit. It has to do with your stocking investment from this past Christmas. You know what it is?

Meb: My stocking?

Jeff: Mm-hmm.

Meb: Yeah.

Jeff: Uranium. Quick takeaway from the listener question is that he’s unclear whether or not the rules of an asset class being down for several years in a row, and then the ensuing potential for a reversion to the mean to have it be a ripper, [SP] whether that applies to uranium. Because it’s very small as a sector. So Meb, do the same rules apply here when you’re dealing with something that’s a sector as small as uranium?

Meb: Well first of all, uranium’s not a sector, uranium is an industry. So the way that most shops do the classification is that there’s about 10 sectors, you know, it’s healthcare, tech, utilities, stuff like that, they just added real estate as a sector. But there’s about 10 of those and those are much more broad and have a lot more depth. And then industries are much more concentrated, so maybe something like biotech stocks, or medical device equipment makers, or uranium stocks. And so there’s depending on the classification scheme, I don’t know, 50 of those? And so it’s the same thing as if you said with almost any market there’s increasing levels of granularity, and so this piece that the listener’s referring to which is about asset classes, and we’ve done a lot of posts here on both asset classes, industries, countries, sectors, what happens when they go down a lot, so 60% to 90%, and also what happens when they go down many years in a row, so when they go down 1, 2, 3, 4, 5, 6 years in a row. And the… I mean, this…we published this in our first book back in ’06, ’07, whenever it came out, ’07, ’08, IV [SP] portfolio. And there’s a chart in there and it talks about…it says, look, at the asset class level when things go down a few years in a row, it’s usually a good time to buy, and at a sector or an industry level because they’re smaller, more concentrated and thus more volatile, you need to stretch that out a bit. And so instead of it maybe going down two or three years in a row, you want it to go down three, four, or five years in a row.

It’s the same thing of comparing maybe a U.S. government bond to equities. And we talked about, like, really bad months. So the…and I’m gonna murder the statistics, but let’s say it was like the worst 1% of bad months in stocks was like a 10% down month, and so usually when you bought after a 10% down month and held it for 3 months you get a good little bit of outperformance, and then…but the bond trigger was 5%. So you had to adjust. You know, so you can’t consider cash or bond-like instruments the same as you would stock. So same thing with being sectors and industries, and the whole uranium and coal stuff is meant to be a fun kind of diversion, I’m not going and loading 100% of my portfolio in uranium stocks at Christmas. Now, that we…however, now that we’ve seen us write this post two years in a row, I guarantee you it’s gonna happen. We’re gonna get all these crazy Shadowstat hedge fund…or Zero Hedge followers, they’re gonna wait till December and find out what our next pick is for the coal in the stockings and then go big, and then, you know, be down 80%.

Jeff: Any idea off the top of your head?

Meb: Because there’s nothing…I mean, look, in my mind there is nothing preventing something down six years in a row to go down seven, or eight, or nine, you know? I get that, it’s just in general, it’s like a rubber band when things go down that much and it’s universally hated, and it’s disgusting, and no one wants it, you really only need some something to go right or almost to go less wrong. And in this case, I don’t know, it was a handful of things, but, you know, it usually I think pays to at least start sniffing around things when they’re down 80% and down 6 years in a row.

Jeff: It’s, you know, it’s like your buddy Steve Sjuggerud talking about how he loves investments that are hated and in a slight uptrend. Speaking of these types of investments, you did coal a couple years ago. Any idea…

Meb: By the way, someone…and I actually didn’t notice this, someone had sent me a chart and said, “By the way, Meb, emerging market local debt on a five year basis is still, I think, has negative returns even though it ripped last year.” I have to look into it. Anyway, keep going.

Jeff: Any idea where coal is we…after…

Meb: I don’t. We’d have to…we…you know what we need? We need a assistant, and during the podcast live shows, to be putting…

Jeff: Show stats?

Meb: Huh?

Jeff: Just looking up stats for us.

Meb: No, to be putting up charts, you know, like on on TV where, like…we need this to turn into a little more than two guys in a broom closet with tequila. I think we need a we need a TV and an assistant that put up charts and be able to…let’s start recording this on video.

Jeff: You heard it here, send in resumes.

Meb: So I don’t know what coal’s doing, I have no idea.

Jeff: All right, let’s see here. What about…

Meb: You know why I don’t have any idea is because Bloomberg did a redesign of their iPhone app and it is atrocious. Did you ever use it?

Jeff: [inaudible 00:32:02]…

Meb: The old one was great. Did you download the new one? It’s unusable. So I don’t even actually have a good quotes app. So listeners, if you know a really good quotes app, email us. I need something to use.

Jeff: Another trend following question here. Have you given any thought to the application of trend following across time, for example, a lifetime to capture the higher gains of buy and hold when you’re young, provided you’ve got the fortitude for drawdowns, and the moving to trend following when older to avoid the drawdowns and volatility?

Meb: So there’s a lot in that question, some of which I don’t know that I agree with, but some of which if I did distill his question, it meant, “Meb, do you think that it makes to make sense to use trend following more when you’re older, because I think that it has more of a chance to protect you when you’re older and avoid drawdowns.” Does that make more sense?

Jeff: It sounds right, yeah.

Meb: You know, I mean, look, I don’t know that…I mean, I don’t know that young people who are learning to invest are gonna be, like, anymore rational or the lessons they learn. And when you say, do buy and hold as a young person and lose a ton of money, I mean, look at Japan where they went through this 20 year bear market. There’s probably an entire generation of young people like, “I’m never gonna…buy and holds, it’s moronic, why would I ever do that,” you know? And so I…and on the flipside, you know, one of the false insecurities that an older investor may have is they may think that trend following is guaranteed to protect them and it’s not. You know, trend following in general helps protect against long bear markets but there’s no guarantee. And you could have a market that were in right now where almost everything is going up and bomb goes off, whatever, who knows, and the markets all go down 40% tomorrow. That’s…trend following is not gonna protect you. You know, most of it’s…it doesn’t have time to react. So, you know, for most people when you’re talking about this kinda…if you want security, if you want to not worry, sell down to your sleeping point and just hold more in cash and short-term investments.

Jeff: Fair enough.

Meb: Take…if you wanna avoid the risk, then don’t take in it in the first place.

Jeff: That kinda reminds me of I think something you’d said or in one of the podcasts where the portfolio that you need to grow wealthy is not the same portfolio you need to maintain your wealth. So I guess it’s up to the investor over time to figure out where he sits on that spectrum and make the necessary tweaks.

Meb: I was just reading a great story about…see if I can find it on Twitter, where we talk…have talked a number of times on the podcast about Batista, the Brazilian guy who was once the top five wealthiest men in the world, and then due to concentration and all of the things that got him to be in the…he was over 30 billion, to be that rich he continued to do the same things and then eventually lost it all. And there’s a “Bloomberg” article about Eike Batista, and I’m just gonna read it real quick. The quote said, “According to allegations in the proceedings is that Batista acting on the advice from a spiritual advisor,” named something I can’t pronounce, “tossed about $130,000 worth of gold coins into the Atlantic last year from the deck of a yacht festooned with flowers and perfumes for the occasion.” Quote, “All those riches that everyone talked about his guru said in a phone interview from Rio, I don’t think that brought him good fluids. So the guru explained, ‘He advised Batista to make amends with the sea goddess Emenaha [SP] by giving gold back to nature after his years of mineral extraction.'”

Jeff: How much are you gonna throw away this year in the ocean?

Meb: I’ll think about it. I’m more interested in throwing away money into my 1960s Land Cruiser. That seems to be a perfectly useful bottomless pit.

Jeff: I drove past your place the other day and saw the “For Sale” sign sitting out there.

Meb: Yeah, I need buyers. By the way, podcast listeners, you want a 1967 Land Cruiser that runs on occasion, let me know.

Jeff: All right, next question here. After reading an article this week from your buddy Josh Brown, he indicates that a significant portion of valuations, specifically Cape [SP], are the confidence and stability of the stock market which will justify relative high valuations, for instance here in the U.S., Japan, and Switzerland while discounting the emerging markets. This does make intuitive sense, but I wanted to see your thoughts on it.

Meb: I disagree consistently with my friends there on this topic. And by the way, Josh, and Barry, and Crew [SP] are hosting their evidence-based investing conference West at some point this summer, I think down at Newport, I’ll be down at it. So if you wanna come hang out and drink beers in Newport this summer or spring, you have to look it up, I don’t know when it is, but we’ll be there. I can consistently disagree with them on Cape in general, looking at foreign markets because my comment there is that you get so caught up in the short-term and, look, the U.S. is in a big, fat, awesome bull market right now, and the Dow, it’s arguably the second longest ever, S&P, it’s one of the longest ever. I mean, we’re approaching, you know, 8 years bull market and there’s only been a handful that of hit, I think, 10 years and pretty nice returns. And so it’s easy to take a step back and say, “Man, times are good,” and just throw valuation out the window because it can go on for a long time. There’s nothing that says the market couldn’t get more expensive for five more years, and just put all the bears out of business and the market just keeps chugging along. That is fully within the realm of possibility. And it’s done that before, I mean, the ’90s it got to a valuation, a CAPE ratio 45. It’s only, like, 27 now.

Jeff: This reminds me of…

Meb: There’s a long way to go.

Jeff: Reminds me of the article we wrote comparing it to 21, where you can keep hitting on a 19, potentially you’re, you know, 18, 17, get you 21, but statistically…

Meb: So people…

Jeff: …you’re most likely to win.

Meb: People draw so much…so many conclusions from a short amount of time frame and data in the way they feel now, you know, and then when times are bad, do that exact same thing with the opposite conclusion. And so when you look at a lot of these countries which by the way have been ripping for the last year, and they have low CAPE ratios in the year prior to that, and the world looked like it was gonna end, and Brazil is gonna fall into the ocean, and everything else would go through the Great Depression, you know, that’s the way that it always feels and looks, and you feel like things are never gonna get better. And lo and behold these markets go up 50%, 100%, 200%, triple, quadruple, whatever it may be.

Jeff: It’s recency bias.

Meb: Yeah it’s a recency bias. And so, I mean, look, you know, we…there’s a post we did I think four years ago that just said keeping it simple, and we have a fund that does this, and we said, “Look, let’s have your long [inaudible 00:39:18] stock exposure.” You want the tailwind of stock, so we’ll have that stock exposure with the factored tilt. And then were gonna put the market in four different boxes. It’s based on valuation and trends, so is the market in an uptrend or downtrend? Is the market cheap or expensive? Couldn’t be more simple, right? And historically, that has worked out great and it’s the exact way you think it would, where if you’re in an uptrend which happened, uptrend in the market is cheap, that happens a third of the time, and that’s the best performing quadrant. Historically that’s done 14% per year. But the next best quadrant is an uptrend in an expensive market which is where we are now, that happens 30% of the time.

So right there an uptrend, which we know in most markets around the world, occurs around two thirds, 70% of time, most time markets spend going up. So about half the time it’s cheap and half the time it’s expensive. Well that makes sense obviously because that’s the definition of it. But the second best place to be in isn’t [SP] uptrend expensive, the problem comes…is when that uptrend becomes a downtrend, so that uptrend expensive is still 12% a year. Uptrend, when it flips to downtrend and expensive, it’s minus 6% a year. So it’s a terrible time to be investing. And so, you know, you need to be a little more careful. So in cheap and in a downtrend is still positive, it’s over 6% a year. You know, you can be a little more cavalier when markets are cheap because it doesn’t matter as much uptrend or downtrend, but when markets are expensive and rollover, that’s when you really want to start to batten down the hatches. But it doesn’t have to be 2017, could be 2019.

Jeff: Have there ever been any studies about sort of the velocity of the drawdown based upon this, you know, “expensive market” versus a cheap market? You know, is it a much faster, more violent drawdown at the very top or is there any sort of rhyme or reason?

Meb: Yeah, we wrote one, we wrote two, but one was called “Where the Black Swans Hide”, and it looked at returns in a bunch of different markets when in an uptrend and in a downtrend. And in a downtrend, the volatility’s much higher and returns are much lower. And there’s a lotta behavioral reasons we think that works, but in general you wanna avoid those periods if you can, thus that’s why trend following works, is you avoid the higher volatility. So you move to a low vol instrument like cash or bonds and you end up avoiding that. And so along the same line of thinking is that if you look at valuation, you know, a lotta people have done this, Montier has done some charts, so has Star Capital, we’ve done some, and you look at valuation and then future drawdowns, we just posted a chart from Hussman on this a couple weeks ago where the more you pay initially for valuation, the higher your future chances of a big, fat drawdown. And it makes sense, the less you pay, the lower it is.

Jeff: But yeah, no, I got that, I was just curious about, say for instance from a CAPE range, [inaudible 00:42:27] call it 30 down to 20 if the velocity of drawdowns during that time somehow could be measured as more violent or [inaudible 00:42:36] are falling farther quicker rather than say a CAPE then from 18 down to 10 you might have the same size of the drawdown, but it would take two or three times as long.

Meb: Yeah. Well as far as time, you know, we looked at magnitude of bubbles in, I think, our “Global Value” book and kinda demonstrated that the size of the valuation over valuation bubble correlated nicely to how long it took to wear off. So Japan, biggest bubble we’ve ever seen took 20 years to wear off. The U.S., for the 2000 bubble only took eight. You know, it got really cheap in March of ’09 a lotta people don’t remember that or don’t wanna admit that because no one was buying, but on a CAPE basis, it was signaling very cheap, I think it was low teens. You know, where we are now again, it’s not terrific, but it’s not good.

Jeff: Well, speaking of CAPE, another question here. I was wondering if you guys have done research on earnings growth rates compared with CAPE to get a more accurate indicator of expected [SP] returns. For example, while CAPE for many countries in Europe is low, their growth rates are also considerably lower than the U.S. which could justify the lower CAPE as compared with the U.S. Any thoughts?

Meb: Yeah, so earnings growth is certainly a component of total returns, we’ve written some articles on what we call the Bogle formula which is distilling future stock returns into the various components of dividends, and earning, or… and by the way, AQR, we just sent this to The Idea Farm, AQR has a good paper on capital market assumptions that looks at this. But just doing it down in the dividends, earning growth, and of course valuation change, the problem is that listener that emailed that in, is backward looking. So earnings growth, yes, it’s obvious that it was lower looking back, but do you expect that to continue going forward? You’re making a very active bet. And historically and ironically, if you look at a lot of these factors that work for broad stock markets, you wanna invest where the numbers are worse. So you wanna invest in the place with the worst trailing five year GDP. You wanna be investing where the worst currency returns were the last five years. You wanna be investing where… So all these things you would think would help. So yeah, if you could just magically forecast that somewhere’s gonna grow earnings 10% a year for the next 10 years let me know. Wonderful, awesome, we’ll plug it into the equation, you’re gonna have great returns.
But the problem is I think the ability to forecast earnings growth is a pretty tall order.

Jeff: Well that means you’re always battling the question of, is this time different, the behavioral bias, you know, everybody wonders about, and we talk about sort of investing in certain countries, no one wants to go where…no one wants to go to Greece, no one wants to go to Brazil.

Meb: I wanna go to Greece. I really wanna go to Greece, sounds amazing. I’ve never been to Brazil. And the only place I’ve been in Greece doesn’t count because it was with my brother when I was in high school and it was one of those islands on, like, the west coast. It was, like, Corfu or something. So…I mean, it’s like a spring break destination.

Jeff: All right, let’s…think were sitting around 45 minutes. Let’s do one more and wrap it up so we don’t go too long today. I am…

Meb: We can do an hour, Jeff. Why you always wanna cut it short?

Jeff: Doing it for you, you’re running outta steam, you’re losing your edge here. I’m 22 with a moderate to high risk tolerance and I’m looking to increase the risk return profile of a global asset allocation portfolio. I realize this will likely reduce Sharpe ratio, but do you know if adding global equities at the expense of global bonds would completely destroy the risk return profile of a globally diversified portfolio?

Meb: It’s sort of interesting that he says, I wanna increase the risk-adjusted returns and I know this is gonna reduce them, so should I do this? He’s like [inaudible 00:46:40], I wonder if he, like, already knows the answer to the question. I mean, there’s a couple schools of thought here. One is that if you truly have a really long-term time horizon and you don’t care about drawdowns, you know, the volatility numbers, etc., compress over a longer time horizon. So if you look at equities in the best and worst case scenario and the volatility on rolling 20 year periods, totally different than 1 year periods. And you start to see the ability for equities to become more bond-like the longer your time horizon is. The problem is the order of events. And so most young people or people in general, don’t think in terms of 20 years. I mean, how many people do you know put their money in a bank account, close their eyes and say, “You know what? Let me see what this is worth in 20 years,” right? It goes down 30%, they say, “Oh my God, I gotta sell this because I gotta buy a car next year,” or “I just had three kid…my third kid, and how in the world I have half the money I used to have in my bank account, but oh, we got a 20 year time horizon.”

You know, most people…it’s a great theoretical exercise, and so maybe this is a business idea. Maybe we come up with a investment company that locks away your money and says, “You know what? Tough. You can’t access this for 10 years. Not only can you not access it, we’re not gonna tell you what the balance is. Only in extreme circumstances, or maybe we’re not gonna charge you a management fee until you withdraw. And if you withdraw…” And sorta it’s…you know, we…

Jeff: Interesting. I mean…

Meb: There’s gotta be some behavioral nudges that would work there to where it would help people. It’s almost like a lock box scenario. It says, “Really? You think you really have a 20 year time horizon? Fine, give us your money and we’ll lock it up for 20 years and you can have it in 20 years.”

Jeff: That would fund your Greece trip.

Meb: No, but it’s I think the way…you’d have to be a little more creative about management fees too, because you’d say…you’re, like, penalizing bad behavior. So many of these brokerages and money management shops, you know, they tout doing the right thing, but all of the incentives are built in the wrong way. You know, the ability to see your account value every day, the ability to trade lightning fast, the ability to use margin, all these crazy things. I wonder if you couldn’t come up with a better model for investor success than what’s currently out there. Anyway, think of some ideas, readers, email me. Listeners. God, I can’t stop.

Jeff: See, that’s why we’re stopping right now at 45 minutes.

Meb: No more, is that it?

Jeff: Yeah, let’s call it a day. Why don’t you take us out?

Meb: Okay. And by the way, I didn’t even answer the question at all. The question was, as far as the global portfolio, one is you’re making an active bet against bonds by the way, and if you look at the global portfolio, it’s roughly 55, 45 stocks bonds, but a good chunk of that, and I think it’s a third of the world market portfolio is corporate bonds. And so corporate bonds are about half stocks and bonds. So, you know, putting more in equities, I’m totally cool with, and I think a great way to do it would be a global value approach, you know, using CAPE ratio or any valuation approach that’ll get you away from putting half in the world’s largest market cap. But anyway, long-term time horizon, yeah, go buy some of our global value fund and then put it away for 20 years, I think it’s great idea.

All right, we got some great guests coming up, you guys, keep sending the questions in. We may start doing these more often or maybe on Mondays. We’ll see what feels right for the Q&A episodes. But thanks taking the time to listen. For the mail bags, send all the questions and tequila to jeff@feedbackatthemebfavoriteshow.com. As a reminder, you can always find the show notes and other episodes at mebfaber.com/podcast. Subscribe to the show on iTunes, and if you’re enjoying the podcast, leave us a review. Thanks for listening, friends, and good investing.

Sponsor: Today’s podcast is sponsored by Global Financial Data. We’ve been using data series from GFD for almost 10 years, ever since I wrote my first white paper. The data’s been vital in our research in areas such as CAPE ratio calculations and historical simulations. For almost 20 years now, Global Financial Data has been aggregating and transcribing data from original sources with many sources no other data provider has published before. Please have a look at their website at globalfinancialdata.com for more info and to set up a trial account. If you mention that I sent you, they’re offering a 20% discount on all new business subscriptions. Again, that’s globalfinancialdata.com.

The State of the RoboSphere

I update this chart on occasion mainly out of curiosity.  If you have any more recent figures fire ’em over and I’ll correct…

Click to enlarge

 

roboz

Episode #39: Ed Thorp, Hedge Fund Manager, Author, & Professor, “If You Bet Too Much, You’ll Almost Certainly Be Ruined”

Episode #39: Ed Thorp, Hedge Fund Manager, Author, & Professor, “If You Bet Too Much, You’ll Almost Certainly Be Ruined”

ed

 

Guest: Ed Thorp is an American mathematics professor, hedge fund manager, and blackjack player. To beat roulette, he and the father of information theory, Claude Shannon, invented the first wearable computer. Along with innovative applications of probability theory, Thorp is also the New York Times bestselling author of Beat the Dealer, the first book to mathematically prove that the house advantage in blackjack could be overcome by card-counting. He also pioneered the use of quantitative investment techniques in the financial markets.

Date Recorded: 2/8/16     |     Run-Time: 58:56


Summary: Ed is a self-made man after having been a child of The Depression. He’s a professor, a renowned mathematician, a fund manager who’s posted one of the lengthiest and best investment track records in all of finance, a best-selling author (his most recent book is A Man for All Markets), the creator of the first wearable computer, and finally, the individual responsible for “counting cards.”

Meb begins the episode in the same place as does Ed in his new book, the Depression. Meb asks how that experience shaped Ed’s world view. Ed tells us about being very poor, and how it forced him to think for himself, as well as teach himself. In fact, Ed even taught himself how to make his own gunpowder and nitroglycerine.

This dovetails into the various pranks that Ed played as a mischievous youth. Ed tells us the story of dying a public pool blood-red, resulting in a general panic.

It’s not long before we talk about Ed’s first Las Vegas gambling experience. He had heard of a blackjack system developed by some quants, that was supposed to give the player a slight mathematical advantage. So Ed hit the tables with a strategy-card based on that system. At first, his decisions caused other players at the table to ridicule him. But when Ed’s strategy ended up causing him to hit “21” after drawing 7 cards, the players’ opinions instantly changed from ridicule to respect.

This was the basis from which Ed would create his own counting cards system. Meb asks for a summary of how it works. Ed gives us the highlights, which involve a number count that helps a player identify when to bet big or small.

Meb then asks why Ed decided to publish his system in academic journals instead of keeping it hush-hush and making himself a fortune. Ed tells us that he was academically-oriented, and the spirit of science is to share.

The conversation turns toward the behavioral side of gambling (and investing). Once we move from theory to practice, the impact of emotions plays a huge role. There’s a psychic burden on morale when you’re losing. Meb asks how Ed handled this.

Ed tells us that his early days spent gambling in the casinos were a great training ground for later, when he would be “gambling” with tens of millions of dollars in the stock market. He said his strategy was to start small, so he could handle the emotions of losing. As he became more comfortable with his level of risk, he would scale his bets to the next level, grow comfortable, then move up again from there. In essence, don’t bet too much too fast.

This dovetails into the topic of how to manage money using the Kelly Criterion, which is a system for deciding the amount to bet in a favorable situation. Ed explains that if you bet too small, won’t make much money, even if you win. However, “if you bet too much, you’ll almost certainly be ruined.” The Kelly Criterion helps you determine the appropriate middle ground for position sizing using probabilities.

It turns out that Ed was so successful with his methods, that Vegas changed the rules and eventually banned Ed from their casinos. To continue playing, Ed turned to disguises, and tells a fun story about growing a beard and using contact lenses to avoid identification.

Meb tells us about one of his own card-counting experiences, which was foiled by his partner’s excessive Bloody Mary consumption.

Next, we move to Wall Street. Meb brings up Ed’s performance record, which boasts one of the highest risk-adjusted returns of all time – in 230 months of investing, Ed had just 3 down months, and all were 1% or less. Annualized, his performance was over 19%.

Ed achieved this remarkable record by hedging securities that were mispriced – using convertible bond and options from the same company. There was also some index arbitraging. Overall, Ed’s strategy was to hedge away as much risk as possible, then let a diversified portfolio of smaller bets play out.

Meb asks, when you have a system that has an edge, yet its returns begin to erode, how do you know when it’s time to give up the strategy, versus when to invest more (banking on mean reversion of the strategy). Ed tells us that he asks himself, “Did the system work in the past, is it working now, and do I believe it will it in the future?” Also “What is the mechanism that’s driving it?” You need to understand whether the less-than-desired current returns are outside the range of usual fluctuation. If you don’t know this, then you won’t know whether you’re experiencing bad luck (yet within statistical reason) or if something has truly changed and your “bad luck” is actually abnormal and concerning.

Next, Meb asks about Ed’s most memorable trade. You’ll want to hear this one for yourself, but it involves buying warrants for $0.27, and the stock price eventually rising to $180.

There’s plenty more in this fantastic episode, including why Ed told his wife that Warren Buffett would be the richest man in America one day (said back in 1968)… What piece of investing advice Ed would give to the average investor today… Ed’s interest in being cryogenically frozen… And finally, Ed’s thoughts on the source of real life-happiness, and how money fits in.

The show ends with Meb revealing that he has bought Ed and himself two lottery Powerball tickets, and provides Ed the numbers. Will Ed win this bet? The drawing is soon, so we’ll see.


Sponsors: Soothe and Lyft


Comments or suggestions? Email us Feedback@TheMebFaberShow.com

Links from the Episode:

A Man for All Markets

Beat the Dealer

Beat the Market

The Kelly Capital Growth Investment Criterion

 

Transcript of Episode 39:

Welcome Message: Welcome to The Meb Faber Show, where the focus is on helping you grow and preserve your wealth. Join us as we discuss the craft of investing, and uncover new and profitable ideas, all to help you grow wealthier and wiser. Better investing starts here.

Disclaimer: Meb Faber is the co-founder and chief investment officer at Cambria Investment Management. Due to industry regulations, he will not discuss any of Cambria’s funds on this podcast. All opinions expressed by podcast participants are solely their own opinions and do not reflect the opinion of Cambria investment management or its affiliates. For more information, visit cambriainvestments.com.

Sponsor: This podcast is sponsored by the Soothe app. We all know how stressful investing in volatile markets can be. That’s why I use Soothe. Soothe delivers five-star, certified massage therapist to your home, office, or hotel in as little as an hour. They bring everything you need for a relaxing spa experience without the hassle of traveling to a spa. Podcast listeners can enjoy $30 to their first Soothe Massage with the promo code “Meb”. Just download the Soothe app, and insert the code before booking. Happy relaxation.

Good morning ladies and gentlemen. We’re here in a rainy and foggy Los Angeles morning. Today we have an incredibly special guest, Professor Ed Thorp. Ed, welcome to the show.

Ed: Thank you very much.

Meb: So, we have a little bit of a younger audience, lot of younger quants. And so just a real super quick intro for those who aren’t familiar, I’m just gonna [inaudible 00:01:45] previous backgrounds, and then we’re gonna hop in because we have so much to cover today. So, Ed is a total self-made man. He’s been a professor, a renowned mathematician, a fund manager who’s supposed to be one of the best track records in all of finance, best-selling author, creator of the world’s first wearable computer, and finally, a successful gambler. Two words you normally don’t hear together. And if you had to pick investors for the Mount Rushmore of investing, Ed would be on there with the likes of Simons and Buffett. And oddly enough, you would probably be on the Mount Rushmore of gambling too, and certainly the only one on both.

So, Ed has just written a great new book, his memoir titled, “A Man for All Markets,” lots of fun stories, don’t want to spoil it. So, let’s jump right in. Ed, I thought we could start where you do in your book. So back in Chicago, and in SoCal in the 1930s, you were born a child of the Depression. You know, my father was actually born around the same time on a farm in Nebraska, no running water, outhouse, all that good stuff. And I saw it kind of color his entire life. The way he thought about things, the way he approached, not only his career but investing. So maybe it would be a good start to talk a little bit about how you thought that experience affected your personality and, in general, worldview growing up.

Ed: Well, I was born in the depths of the Depression, actually. Think the Dow touched its lowest point in July of 1932, and I was born in August of 1932. So, it was uphill all the way, but bumpy in the stock market. And people were very poor then, very much like you picture people in the streets of Moscow when I was there in 1972. Dower, drab clothing, everything was precious. Everything was saved and used, and there was 25% unemployment.

So, it was a grim time in the history of the country. We finally got bailed out, so to speak, with World War II. So, I experienced all that, and that gave me a perspective on later events that I think aren’t shared or appreciated as much by people who are much younger.

Meb: And so, you had to scrap a little bit. You had to take on a few jobs. I think you had the what, 2:00, 4:00 in the morning newspaper route as well, right?

Ed: Yeah, when my family moved to California in 1942, I was about, we’ll pretend that I got to work delivering newspapers at 2:00 a.m. or 3:00 a.m. in order to make a little extra money. And I was going to a high school which was academically, not particularly good. It was ranked 31 out of 32 in the L.A. City school system. So, nobody there went to college, but I was interested in science, math, literature, quite a few things. So, I ended up earning money to buy science equipment and also learned how to teach myself things. And that served me well in later life, the learning how to think for myself and to teach myself.

Meb: And in teaching or so I’m thinking, I remember the book even you referencing making your own gunpowder, nitroglycerin? Is that right?

Ed: Yes, but I learned something, theoretical in science. I also tried to put it to work. I made explosives, gunpowder, nitroglycerin, guncotton, and shot off rockets, that sort of thing.

Meb: And you know, it’s funny, I come from a family of engineers on both sides. And my mom tells a funny story about my uncles who had built pipe bombs, and then hid, set one off, and then buried one in the backyard in North Carolina. And then my grandfather, years later had unearthed it, and thought it was some big plot, and that someone was burying bombs in his backyard. And so, had called the police and I think it even escalated a few levels above that. And eventually, I think my uncles told him many, many decades later. But, you know, it’s interesting because there is oftentimes a link between bright kids and sort of getting into mischief. And you were a bit of a prankster too. I mean and there’s a whole handful of kind of humorous pranks you had kind of pulled when you were a younger guy. Is there any one, in particular, that sticks out? As particular, one of your favorites?

Ed: Well, one of them, it got a fair amount of press. There was a large indoor swimming pool in Long Beach called The Plunge, and it was part of an amusement park area down there. So, I used to go down sometimes, catch the bus when I was a teenager, and go own with myself, all by myself with a friend and look around, and argue with people at one of the outdoor places called the Spit ‘n’ Argue Club, where people would hold forth for 15 minutes in topic.

So, I learned how to reason against people who believed in Flat Earth Society, that sort of thing. Winding down, when I was learning chemistry, I came across a dye called analum red, and this dye could color 6 million times its own weight a deep blood-red. So, I put a little pinch in the goldfish pool in my backyard and it turned it a deep blood-red. And I went back to my little chem lab behind the garage that I had installed there. I heard a lot of screaming. My mother had come out and saw that the pool was blood-red, and she thought I was in there somewhere.

So, I calmed her down, and I thought about it a little more and said, “Well, this could lead to a really fun prank.” So, I went down with a confederate that I’d recruited to the Long Beach Plunge, and we put a little bag of analum red in the pool that was sealed with wax. And we had some strings tied to it so we could tear it apart. Then we walked to the sides of the pool, and a swimmer came by and stretched the strings, and unleashed the dye.

And we got out, dried off, ran upstairs to see what would happen. And there was a large red cloud that had formed. People began to scream. And they hero-dove in and stirred it all up too in an attempt to rescue who was bleeding to death in the middle of this red cloud. And then finally, they realized that, as the cloud dispersed, there was nobody there. But the pool turned kind of a Kool-Aid, a red Kool-Aid color, and everybody basically bailed out. You know, got their arm stamped and they left.

We came back in the afternoon. Not many people checked back. And then the next day, there was an article in the newspaper about pranksters dying the Long Beach club, Plunge, red. So, it was very entertaining to me.

Meb: That’s funny. My favorite go-to growing up was the old-school sink that had the little spray nozzle next to the to the main nozzle, and I used to put rubber bands around it so that anytime anybody would come into the kitchen would get it hosed down. The problem with that one is that it’s much easier to get caught because there’s only a few culprits, than the pool.

So, one quick question, and so we’d asked on Twitter. We said, “Hey, we’re having Ed on tomorrow. Anybody have any good questions?” We got all sorts of questions, but one that I thought was interesting, we may include a few as we go along and it says, “You know, a lot of people likely look up to you, quants, gamblers as, you know, kind of their Eider [SP] mentor. Was there anyone that, you know, as a child, and you know, in middle high school, growing up that you looked up to as sort of a role model, you know, in any field or in any sort of regard?

Ed: Well, my parents were busy working in defense industries during the war, and for some years afterwards. And so, one was working swing shift, the other was working graveyard. So, they were either working or sleeping. I saw very little of them. So, I kind of raised myself, but I had a wonderful English teacher at Narbonne High School in Lomita, who said he’d took me under his wing. He saw the results of my IQ tests and sort of honed in on me as somebody who had promise. In any case, he was almost like a second parent or a replacement for my parents. And so, I learned a lot from him, and it’s probably a lot to do with his nurturing that I focused as much as I did.

Meb: You know, it’s interesting that there’s so many commonalities. I remember my father, same sort of thing, was had no intentions of going to college. And if it wasn’t for one teacher that had kind of encouraged him along, it ended up similar to you. So, you had received a scholarship to Berkeley, eventually transferred to UCLA, we’ll mention it later, but ended up being a professor at MIT, and New Mexico State, UC Irvine, all these good things.

But I want to skip forward a little bit to age 26, you’re out of school, assuming grad school at this point, but let’s talk about your first Vegas experience. And this is with blackjack, and I think you had gone to Vegas and with what we would today call a basic strategy system, which is sort of the basics. You know, you can’t really beat the casino, but you’re probably not going to lose a whole lot. And apparently that first time, there was a fair amount of ridicule from other players in this experience. So, I was wondering if you could talk about that or why that was the case.

Ed: Sure. Everything you say is on the mark. What happened was I got a bachelor’s and a master’s in physics, and then while finishing my Ph.D. in physics, I was all done except for the last part of my thesis. I ran into a lot of math problems it was in quantum mechanics, so I started taking more math courses. And then I realized that UCLA was slow graduating people in physics, but math was a relatively quick. So, I changed to math to get my Ph.D. sooner. So, it happened quickly enough so that I wasn’t able to apply for a job immediately. So, I was kept on for another year as an instructor at UCLA while my thesis adviser helping get a good placement which turned out to be MIT.

During that year, I went over Christmas vacation to Las Vegas. It was Christmas 1958 because we didn’t have any money, and they had good accommodations at low prices, and also cheap food. And I happened to hear about a system in blackjack that had been generated by four Army mathematicians. That’s the way they passed their three years at Aberdeen Proving Ground. And they had worked out a way to play blackjack almost even. A casino would have about a six tenths of a percentage, they thought. Their work was approximate, so that wasn’t an exact number. It turned out to be that the casino and the player were just about dead even using the strategy they had generated, but no one knew that at the time.

So, I took their strategy along with me, sat down at a blackjack table, and decided I’d risk $10. The reason I was willing to do that was because I had figured out how to beat the let, and I knew that I’d be having to learn about how to play in casinos, and get some exposure to the environment in a casino. In any case, I played for about 20 minutes with a little strategy card and everybody thought it was ridiculous. And then the card caused me to destroy a good hand. I think it was an ace and a seven and keep drawing cards. And I finally got a terrible hand. I got 12, 13, 14, 16, I kept drawing.

But then I ended up with a 7 card 21, and they all thought this was wonderful. That this was an amazing strategy and when they thought it was a fool’s strategy before. So, I learned from this that the players, at least in that little group, didn’t understand the game. And the people in the casino didn’t understand because once I’d drawn 7 card 21, they all wanted to see what’s going on with the card. And they all changed from ridicule to respect.

I went back to UCLA and grabbed the article written by the so-called Four Horsemen, the mathematicians from Aberdeen Proving Ground, and began to read it. And I realized, almost immediately, that as cards were played, the composition of the deck changed, often quite radically. And so, the odds would change, often quite radically in favor of the casino or the player. So, that was my inspiration. And now the question was how to actually make this into a practical system. So, I thought about that and got to work on it.

Meb: And so, it’s interesting because you had said in the book, there’s a great quote, you said, “Had I been more knowledgeable about the history of gambling and the centuries of effort devoted to the mathematical analysis of games, I might not have tackled blackjack.” And it was only once you sat down with the players, once saw how rational they were, but then also went back, thought about it a little bit, and this is kind of a great comment on I think interdisciplinary work where a lot of the status quo, and a lot of what people think to be, you know, correct, it often takes someone from a somewhat skewed or totally different discipline to think about in a different way.

So, all right. So, you started thinking about moving card counting, which is what people describe it as today. Maybe just give us a super quick summary of how that works on the most basics so the listeners can understand how you then implemented it going forward.

Ed: Okay, what I found out when I first attacked the problem by hand but then by computer after I moved to MIT. They had a new IBM 704 computer that I could use along with 30 New England universities. So pretty crowded. What I found out was that if you took small cards out of the deck, that shifted the odds fairly strongly in favor of the player. If you took big cards out of the deck, aces and 10s, that shifted the odds very strongly in favor of the casino. If you reverse that, a deck rich in big cards is good for the player. A deck poor in big cards is bad for the player. Now they’re mirror images. A deck rich and small cards is bad for the player. A deck poor in small cards is good for the player.

So, the point count that came out of all this was you start with a count of zero, aces and 10s, when they fall, minus 1 each. So, you start counting down if you see aces and 10s going out. If small cards go out, those are two, three, four, five, and six, then you add one to your count for each small card that goes out. And sevens, eights, and nines are fairly neutral so you don’t bother count them. They’re just zeros. And so, the count goes up and down as you see cards during play. And when the count gets positive enough, then you bet a fair amount. And when it gets negative, you bet small just to keep your seat, or you get up and leave or change tables. So, that’s the root idea. And that worked very well initially, and still works now in those casinos that haven’t messed the rules up.

Meb: So, there’s a couple interesting points I want to talk about. And so, you eventually started implementing this. You had some interesting, to say the least, partners that funded you some money. And you started implementing it, won some money. And what probably every entrepreneur in the country would think is a somewhat crazy decision, then decided to publish the work. You know, and one of the most often asked questions on Twitter is said, “Why didn’t Ed just keep this to himself, the secret algorithm, and make a gazillion dollars and never tell the world?” What was your thinking there?

Ed: Well, I was academically oriented. The ideal life for me was to be a full professor at a good university and have all kinds of smart friends and work on interesting problems. So, to me, this was an interesting problem that I was curious about. And the spirit in science is to share what you find out. So, to share my ideas was almost automatic.

However, I ended up actually going to the casinos to play because when I announced the strategy that I’d developed, there was a lot of ridicule both from newspapers and from Las Vegas, and Reno especially. So, the state of Nevada said, this is ridiculous there’s no such thing as a winning system. By the way, mathematicians have thought that was no such thing either.

But when I explained how it worked at a meeting of the American Math Society, then they caught on and they understood what was going on and they realized that it was right. So anyhow, I ended up accepting a bankroll offer from two very wealthy citizens, and we went out to Lake Tahoe and Reno for a test of the system. That was in spring break at MIT, 1961. And we took along $10,000. They wanted to take a $100,000 along, but that was too much in my view because if something went wrong, something might go wrong with me. So anyhow, you might add a zero to these numbers approximately because of inflation. A dollar then is worth about $8, close to $10, now.

I played for about 40 hours, about 20 hours was warm up and getting used to everything, and about 20 hours was serious. About $50 to $500 betting. And I predicted that we double our bankroll, and we actually made $11,000 after it was all over, instead of the $10,000 I predicted. So, everything performed the way I said it was going to, we were never behind more than 1$,300. So, that was the beginning.

Meb: We’re going to skip over some…you have some awesome stories in the book including, one of my favorites which is how you communicated your earnings to your wife over the phone. But listeners, you gotta go read the book to get all these. But here’s a question I wanted to ask and so, you know, a lot of people once it goes from theory to real world implementation, there’s a very real influence which is the impact of emotions. And so, we now know through the work of [inaudible 00:20:38], all these other guys, that there can be a real psychological burden on one’s morale and with losing money and gains don’t have an equal and opposite boost. And so, given this and given the prospect for, you know, runs with cards on either side, how did you stick with the strategy after suffering bad losses? Did you ever let emotions lead you to act in an inconsistent way? And did you ever make any exceptions?

Ed: Well, those are really good questions so I’ll tackle them one at a time here. First, actually having played in a casino to address the questions you just raised was perfect training ground for much bigger scale betting on Wall Street. So, one of the things I learned that I basically taught myself in the casino on our first big gambling trip was start small. Just bet $1 to $10, and play until it doesn’t bother you anymore until you can emotionally handle it. That’s 8 hours of the 20 hours of warm-up.

And then after that, I moved up to $2 to $20. That took about an hour. Then I moved to $5 to $50. That took another hour. And $25 to $300, another couple hours. And then $50 to $500. So, I learned how to handle my emotions, how to be disciplined, how to stick to the system by starting small at a level where it didn’t bother me, and then gradually scaling up as I learned that it worked, then I got confidence, and so on.

And so, there was one thing I learned that was a valuable ever after when the scale became 10s of…even hundreds of millions of dollars on Wall Street. The other thing that was very valuable was how to manage money. And so, I came across something which later was impounded in series of papers I wrote called the Kelly Criterion for deciding how much to bet in favorable situations. And that now has caught on with a lot of people. There’s a big book that I co-edited with tons of math and papers that have been written over actually centuries that relate to this topic. It’s called the “Kelly Capital Growth Investment Criterion.” It’s put up by Will Scientific. It has three editors, Bill Ziemba, Leonard MacLean, and myself. And we wrote, several of the papers in there and a lot of the connective material. But it’s a math thing. You don’t have to do a lot of work for you to…

Meb: And Ziemba’s a great author, by the way, listeners. But so, let’s talk about that real quick. Because I think one of the biggest mistakes gamblers, but also investors make often in their bet sizing is they take way, way too much risk or exposure given, you know, the odds. You see people sit down at a blackjack table, and they have $100 bankroll, and they’re playing with $20 hands. And it doesn’t matter, you know, even if they were counting in that regard because you’re gonna go bankrupt because you have such a high bet size. And so, for so let’s expand real quick, think about risk and return in the Kelly criterion. And so, its main goals, it involves a way to determine the approximate wager or position size when you have a sort of known edge. And I wonder if you’ll explain just simply for a bit for our listeners, is there kind of shorthand version you could summarize that, you know, investors can put into context?

Ed: Sure. The basic idea is that if you bet small in good situations, you won’t make very much money. You should bet really big. There’s a chance you’ll take such a big hit when something bad happens that it’d be ruined. So, there’s an intermediate level that works better than either of the extremes. And the Kelly criterion shows you how to calculate that intermediate level if you know the probabilities. And if you can only estimate them, then you can be somewhat conservative and still get a pretty good result in the Kelly system even with a lack of important information.

Many people don’t understand on how to bet size, and Kelly criterion theory shows you, if you bet too much, you’ll almost certainly be ruined. And you might think that only applies to somebody sitting in a casino or somebody managing a little portfolio, but it actually applies to everybody in quite a dramatic way. Later in the book, I talked about various busts that we’ve had. There was the ’29 Crash. There was the S&L Scandal in ’80s. There was the market meltdown in 1987, there was long-term capital management 1998. And there was the Big Bust in 2008-2009. And one theme that runs through all these is excess leverage.

And one thing the Kelly system tells you is how much leverage to use. And the amount of leverage that should have been used in all these situations is way less than the amount that people actually use. And so, the Kelly system says when you use too much leverage, you’re going to blow up.

Meb: You’re trying to say the hundred to one of long terms is a little too much leverage?

Ed: Yeah.

Meb: Well, you know, I mean it’s been eight years going on now since we’ve had the bear market in the U.S. And it’s funny because, you know, we’ll talk about this in a second but you know, the biggest mistake we see, particularly younger investors make when investing, is they often having not experienced a loss or a devastating loss, in general, they take on way too much risk. And financial advisers we, you know, we think make that mistake. In general, for younger investors, they say put all your money into stocks. But the problem is you neglect the emotional part is can someone sit through a 30%, 50%, 90% loss? It’s tough.

So, all right. So, we got a little more on Vegas. I want to talk about, you know, one of the things that with any business or casinos is that once someone finds a way to take millions of dollars from you, as in the case with Wall Street as well, often the rules change. And so, Vegas started changing the rules. You started to get some chemicals in your coffee. There’s even a pretty scary story about, you know, you didn’t say it was guaranteed, but your car accelerator getting stuck. And then eventually, they just straight-up started banning you from the casino.

And so, you know, that the challenge is not necessarily just having a winning system. It’s the threat of danger that could, and even, you also mentioned the casino outright cheating. And then the rules changed, ability to kick you out. So, I’m curious. You started a couple times to change your appearance a little bit. Was there a crazy, did you have a craziest sort of costume at all? I think one time you said maybe you shaved your beard or added a beard. What was the…

Ed: Well, I didn’t go on many gambling trips because I’m not strongly money-oriented. I’m more life and people-oriented. And I’m interested in doing kind of things that I want to do, rather than just trying to accumulate stuff. I happen to be lucky and also accumulate stuff, but that’s just the way it worked out. In any case, I went on a few more gambling trips, and on one of them I was, a point I made was to always have somebody around you know, to help guarantee my safety. So, there was a couple I didn’t know who volunteered to come along on one of the trips. They were…we have mutual friends.

And so, I decided to experiment with a disguise since I was having trouble getting a decent game looking like myself. So, I grew a beard, and I got contact lenses, and when I walked up to the hotel room where the people who were with me were staying, we were staying in the same hotel. I walked down the hall, knocking on their door, we met, we talked, we went to dinner. And then I played in this outfit with a lion shirt and casual pants, so forth, at a casino nearby in Reno. And I played for several hours, and I kept winning and winning. And eventually, the people and management came by one at a time to ID me, get a good look, so that when they kicked me out, they would know not to let me back in again. And the dealer, who was a young lady who was very interested in me because she saw a lot of money, she wanted to get together at 2:00 a.m. when her shift was off. We didn’t do that.

Meb: My wife wanted me to ask you if you’d ever dressed up as a woman, but I am guessing the answer to that is no.

Ed: No. People have…

Meb: So…

Ed: So…sorry. So, the punchline in the story is that they kicked me out about 1:00 a.m., and she very disappointed. So then shaved off my beard, put on fairly dressy pants and dress jacket, so forth. Put on sunglasses instead of the contact lenses, and came to knock on their door. And when they opened the door they said, “Yes?” They didn’t recognize me. So, I said, “This is gonna be good.” So, I went back to the same table in the same seat the next night, and as it happened, a parade of management started coming by to eyeball me, I thought eyeball me again. But they weren’t looking at me, they were looking at the guy on my right. He was a player cheat who kept trying to either add chips to his pile when he had a good hand or add chips to his bet or drop chips off his bet when he had a bad hand.

So, they jawboned him and criticized him and everybody came by to see who he was. And they kicked him out after about an hour. I made sure that I only spoke in a whisper when they came by to offer me drinks. And I asked for milk, and I didn’t use my voice so that the dealer could hear it. It was the same dealer I had before. And she didn’t recognize me. So, I played on. I won all evening and left. So, the disguise worked very, very well in that instance. And I was, I will say I was greatly entertained by that.

Meb: It’s funny, you know, so I ended up moving to Tahoe out of college, you know, along with a few friends, of course. We’d taught ourselves to count. And had been mildly successful. I think we eventually figured our winnings were about minimum wage per hour. But the biggest challenge for me was that once we learned, you know, you didn’t become almost like a computer.

And once you know that the game can get beat and you get kicked out of about five casinos, like the allure and fun for me, at least, was a little bit gone. And that all of a sudden now you’re sitting at a blackjack table watching people just lose all of their money over and over berate you for the terrible hands you’re playing, smoking cigarettes, and it just wasn’t a whole lot of fun, you know, at that point. And one of the biggest challenges I, you know, added a buddy and we said, “Hey, let’s play as a team. We can spread our bets, breadth,” all that good stuff.

And one of my favorite stories from him and why, you know, I eventually quit doing that, is we came back after about an hour and I saw another of our buddies and I say, “Hey, how’s Chris doing?” And then he said, “Oh man, he’s down a couple thousand.” I said, “How is that even possible?” I don’t even, with the bet sizing we’re doing, I don’t even think that’s possible. He says, “I don’t know, but he’s having a good time. I think he’s had six Bloody Marys already.” I said, “Oh, okay, well that makes sense.”

We’re gonna skip over…so, you gotta go read the book if you want to hear about Ed’s fascinating contribution to roulette, building a wearable computer, he talks about even thinking about wheel of fortune and baccarat. The one question I wanted to have before we move on to the bigger casino is, you don’t ever mention either sports gambling or poker. Were those games, do you ever thought about or had an interest in or in that time not so much?

Ed: Let me share with poker. What I understood, well, I read through a book called, “The Mathematical Theory of Games and Economic Behavior” by John von Neumann and Oskar Morgenstern, the classic fundamental book on mathematical style game theory. And poker is one of the favorite examples in that book, simplified examples that are worked out that launched a lot of people trying to figure out how to mathematically solve poker. And one of the intriguing things about poker is that you can mathematically analyze bluffing.

So, you can get a formula which will tell you know, in a situation with what probability you should bluff, fold, call, or raise. So, people have worked on this pretty hard for a long time. They finally, just now have solved two-person Texas Hold ’em limit poker, and I think they have a very good artificial intelligence program for Texas Hold ’em no limit poker. It’s not perfect but apparently, beats human players. This has just happened.

So anyhow, my analysis of all this when I thought about it was, I could spend years studying poker and trying to get good at it, but then my life would be a poker analyst and a poker player. And that wasn’t the kind of life I had any particular interest in. So, I passed on poker because it was too much work for what I was going to get back out of it.

Meb: Yeah, poker for me, I love playing, having a few beers, playing with friends. But sitting in a casino, same thing. I did like these tournaments that go on for like 10 hours. It’s just that it’s almost like torture to me. It’s the most boring thing in the world. Anyway…

Ed: So, I asked myself the question, what kind of life you want to have, and it wasn’t the kind of life I wanted to have. But let me…you mentioned sports betting. In the ’90s, I happened to hire a Ph.D. candidate in computer science who had a sports betting program, and it looked quite good to me. And there were a few ways to maybe simplify it a little bit, and add just a little bit to it.

And so, we gave it a try in Las Vegas, and we had a lady there, betting for us, a very smart, capable person. And she spent about five months using the system. We had about a 6% edge, and we ran $50,000 up to $173,000. But I decided to kill the program because people who were carrying living betting tickets were being killed and robbed in Vegas. And I didn’t want to risk her person in an operation like this. I basically just shut it down. It wasn’t worth it.

Meb: There’s definitely some unsavory characters. Well, let’s move on to the even bigger casino, Wall Street and investing. And so eventually you redirected your focus to the financial markets. And in the book, you said, “Gambling is investing simplified.” And so maybe you talk a little bit what you mean by that.

Ed: Sure. In gambling, you put money down and there’s an uncertain outcome and you get a payoff. Same thing in Wall Street. Put money down, uncertain outcome, you get a payoff. There are differences in details. Gambling is a much faster series of bets typically than on Wall Street. Not anymore, of course, with high-frequency traders trading in milliseconds and microseconds. But in the old days, humans were not so rapid in the way they did things.

The difference between the casinos and Wall Street is more one of scale than anything else, and the fact that at least in some casino games, you can calculate odds very accurately, not all of them. In most Wall Street situations, you can only estimate. So, if were to ask you for instance, where will the S&P 500 be? Or where will the DOW be, let’s say, at the end of this year? So, I could ask you what you think the midpoint estimate is, probability half higher probability half lower. You’d come up with something fast, someone else will come up with a slightly different number and so forth.

But we don’t know it’s going to be spread around that. And events could cause the spread, the outcome to be very, very far away from our estimate or very, very close. Typically, the estimate is, you know, any given year up 10% over the course of the year because that’s what history has shown. But in many years, the move is far greater or far less. So, on Wall Street, you’re busy estimating things that you can’t know exactly, whereas, with blackjack, you can calculate the exact probability that the dealer, if he’s honest, will deal you a blackjack on the next hand.

Meb: And so, you interestingly enough, picked an area that relies a little bit less on safe forecasting and a little bit more on, certainty is the wrong word, but the opportunity in arbitrage. And so, you know, so Ed started a convertible hedge which eventually became Princeton Newport, and concocted one of the near highest, if not risk-adjusted returns over 20 years plus another 10 with Ridgeline. And Princeton Newport had something like no down years and three down months, I think, or three down…no, three down months, I think. So, you talk a little bit about that strategy that you implemented and as a gazillion readers always were interested if that’s something they could still replicate today?

Ed: Okay, a lot of questions there. Let me tackle one at time. First record Princeton Newport, we ran a [inaudible 00:39:13] as I recall, 230 months, and we had three down months. They were 1% or less. All the other months were winning, all the quarters were winning, all the years were winning. And we annualized before fees a little over 19%, and the Dow did about half that. So, lots of people have had records in profits that good, few, if any, have had such a low risk associated with that kind of a record.

And the way we got that low risk was that I specialized in hedging securities that were mispriced against each other. Not securities in the same company. So, I might, for instance, buy a convertible bond in the company and sell short options against that bond, if I thought the bond was underpriced. And then the underlying risk of the company price-changing would largely be hedged away. And so, then I built a portfolio of a very large number of these things, and as money became available or as our positions were cashed out, I put more of them on.

And then we developed and branched out into other profit areas like index arbitrage, and locking in profits in futures markets and so forth. But always things in which the risk was hedged away as much as I could. And when you had a portfolio in which each little part had most of its risk hedged away, what was left was a diversification among many low-risk things. And the total risk would kind of wash out by the law of large numbers. So, that’s why the returns were so stable over this time.

Meb: And so, here’s an interesting…there’s nothing that breeds competition more than success. And so, you had a really long successful track record. And you talk in the book about, you know, eventually having conversations and helping to start firms like Ken Griffin’s Citadel as one of the first LLP user. First LLP, and then D.E. Shaw, and a bunch of others. One of the questions I have so, you know, if you look up a lot of these multi-factor models today or even the gazillion hedge funds, you’ll often see, you know, you pull the stock and AQR owns it, D.E. Shaw owns it, yadda, yadda all the way down, LSV owns it.

Let’s say you have a system that has an edge, you know, how do you…and it starts to degrade or do poorly. And this, I actually struggle with this. And I don’t know that I have a great answer, is it how do, you know, when it’s time to put a system to pasture versus say when it’s in a drawdown that it’s actually time to invest more in the belief that it’s a mean reversion sort of opportunity. Is that something you could comment about?

Ed: Sure. That’s a hard question that many people [inaudible 00:42:04] over the years. And the way I’ve addressed it is, if I’m doing something that I think gives me an edge, I asked myself did it work in the past? Is it working now? Do I think it’s going to work in the future? And I want to know what the mechanism is that’s driving it.

For instance, somebody who is a commodity trend follower and doing pretty well right now, worked for him a couple years, and we worked on various systems for trading commodities. And they did. They had mixed results, but on the whole, somewhat good. But I said to myself, I’m afraid to invest in this thing in a big way because I will never know if, when I have significant drawdown whether it’s just bad luck, you know, random chance. I’ll come back and explain what I mean by that in a minute. Or whether something has changed and things don’t work anymore.

Let me go back to the random chance thing. If you have something that trends upward historically like, let’s say the S&P 500, and let’s say it goes up 10% a year. There are random fluctuations around that, and some of them are fairly large. If you have an idea of the level of the random fluctuations, then you can tell whether something is really extraordinary out of line or not.

The same in blackjack. I learned that early in the casinos. If I have a certain edge, I can tell by comparing my results with the amount I should have made on average whether what’s happening is extraordinarily bad, so bad that it suggests something else is going on like cheating, for instance. Or sometimes it’s extraordinarily good, maybe a dealer is throwing cards my way. I’ve never seen that happen but were it be extraordinarily good, I’d also question that. In any case, you need to understand what the underlying average result ought to be, and how much normal chance fluctuations up. Down is bad luck. Up is good luck. How much that can be, and then see whether what is happening is outside that range. And if it is, then you wanna know why. So anyhow, if you don’t have a reason for knowing why something works, if it goes bad, you don’t know whether it’s bad luck or whether something changed.

Meb: Yeah, and we often talk about in on the podcast about how important it is to at least understand history even if you’re a buy and hold investor, you know, and we talk often about as a equity investor, you need to be able to accept 50. Like you mentioned in the 30s, the stock market went down over 80%. And ask anyone in Russia, Brazil, Greece, etc., but a lot of people may acknowledge that fact, but then of course when it happens they don’t believe that it’s really happening and so are unprepared for it.

All right. So, I’m wanna hit a few more topics before…we only have you for so long today. So, over your career, you mentioned you did all sorts of trading, convertible, Warren R, risk, thrift conversion, futures R, stat R, multi-factor models, trend following, all this stuff, do you have a most memorable trade over, you know, the last 40-plus years?

Ed: Well, one of my favorites, there are quite a few I mention in the book, one of my favorites was some warrants I bought way back in the early ’70s. When I first learned about warrants when I was educating myself about the market, I got a little book which told about how once in awhile you’d buy warrants for pennies, and they’d be worth dollars. You’d make a hundred times your money. And I thought, I’ve done a lot of warrant trading, and I thought that would never happen to me. But we picked up some warrants for something like 27 cents a warrant by, I have the exact numbers in the book. Then I bought about10,800 of them. And as for…and the stock, underlying stock was, I think, $8.

So, being a hedger, I hedged even this tiny amount on which we’d spent just a few thousand dollars. And the stock went down to something like one and a half. So, I covered the stock which paid for the entire cost of position, left a small profit and a couple thousand dollars. And the warrants were so cheap, I said to my partner just, you know, “Put them in a box and leave them there. They don’t expire for another 10 years or so.” So, we did, and then time went by, a couple of years, and we started getting phone calls. They wanted to buy our warrants. Are you looking to sell? The stocks moved up. It’s like $10 or $15 now, they want to pay us maybe $3 or $4. And I said, “No, it’s not enough. The warrants are worth more than that.” And as the stock moved up, the warrants became more and more valuable theoretically. And the people who wanted to buy it kept raising their offer, but never enough. So, I said you know, just to sit on ’em.

Pretty soon the stock got to 40 which was the exercise price for the warrants. So now they’re moving into the money and then the stock kept moving up. The stock finally moved up to, I think 180 or so. And the warrants were carried along with it. And so, we sold these 10,000 warrants on the way up, mostly near the top of our profit at more than a million dollars.

And the company it was sort of interesting. It was something called Mary Carter Paint Company, and they had purchased a bunch of land down in the Bahamas. They decided to see if they could erect a casino down there. And they got early permission to do that and they changed the name to Resorts International. And that was the cause of all the action in the warrants and the great explosion [inaudible 00:47:50] company. So anyhow, that was fun to see that happen.

Meb: I love it. You should’ve completed the circle by then going down to the casino and taking them for millions of dollars and making the stock go down. You know, I thought for sure you might have said the trade where you bought part of an oil tanker with Bruce Kovner, the Empress Demurs. But readers or listeners are going to have to read the book to hear about that story. It’s pretty awesome.

All right. We’re gonna do a couple, super quick questions. We only have you for about 10 more minutes or so. The great story in the book is you talk about getting to meet Warren Buffett. It’s who everyone’s gonna be familiar with, and you said you later told your wife that you thought he’d be, one day, the richest man in America. What did you see in Buffet in that meeting or that time that kind of led you to that conclusion?

Ed: Well, I learned that he had started in the stock market when he was something like 11 years old. And he was devoted to it, and extremely knowledgeable, and he’d already made a lot of money at that point. He was worth about $25 million at the point I met him and that was back in 1968. Now, in 1982, it took $100 million to get on the Forbes’ 400 list. Twenty-five million in 1968 probably would have gotten him on if they’d had that list then. Forbes, of course, didn’t know about him. They didn’t discover him until 1965 when he was well up the list. Pardon me, 1985, when we was off the list. They’d been running for three years before they even knew he was around.

But he was smart and knowledgeable. He was good with numbers. He understood long-term compounding. And he was gonna spend his life doing it. And he was an encyclopedia of information. So, I thought he had everything it took, and he’d already gone very far when I met him. Although a few people, except his investors and immediate friends, knew how far he’d already come.

Meb: You know, it’s interesting we talk a lot about Buffett, and we have done a ton of modeling that just goes and tracks his holdings through public 13F filings, and show that you could easily beat the market by a mile just by following his holdings once a quarter when they come out publicly delayed. But at the same time, like anyone in like any strategy, he goes through these periods of under and outperformance.

And so, it’s something like his stock picks, his long stock picks, not Berkshire, has underperformed the market 8 of the last 10 years. But if you go back to 2000, he’s outperformed the market on those stock picks by something like 5% a year, which would have beaten 99% of all mutual funds. And it just goes to show a lot of people’s edge, and in his case, I think, for example, is that is his ability to stick to his system, you know, much like you talk about in blackjack where he says, “Look, this is what I do and realize there’s gonna be times of underperformance,” and not changing his whole approach when markets are down or he’s doing poorly.

Okay, a couple more really quick questions, and then we’ll let you go. One Twitter question that we got like in six different variants was, if you could give a piece of investing advice to say a child, grandchild, you know, maybe with a slant towards kind of what’s the best strategy for the average investor to grow wealthy, what would you say?

Ed: For the average investor? He shouldn’t spend his time and life trying to beat the stock market. He should just buy a no-load low-fee index fund, like, you know, Vanguard, S&P 500, or VTSAX.

Meb: Well, that’s easy. That’s great advice. We certainly sympathize with that. A couple other ones, not necessarily finance-related and we’ll let go. You talk a lot about…I mean, I’m sure you get asked a ton about gambling, investing, written multiple books now. So, you must enjoy the writing process. Could you talk a little bit about, you know, are you a regimented writer or what’s your sort of writing routine?

Ed: Well, what I do is I make an outline of what I’m going to write. And I think about the outline and decide if this is really what I want to write about and how I want to do it. And then I begin to flesh in the outline. Now, I finally get a piece, a draft piece. After that, I look at it and think about it for a while, and decide how to try to improve the writing and the quality of the writing. And as one friend said, “All writing is really rewriting.” And I find that with each pass, I can make the sentence structure better. I get a few more ideas. It becomes more conversational, and so forth.

Meb: I think that’s true, you know, in my experience, it has always been to have a total amount of writer’s block and panic, and then to go totally insane and then kind of write it all at the same time. But the first draft is, you know, so many people think that’s the most work, but it’s really the 200 rewrites after that. So, you’ve said, I’ve seen recently a note that you’re thinking about or maybe decided to be frozen once you pass on and, you know, 20, 30, 40 years from now once science has caught up. It seems like in, you know, many ways everything you do is about defying the odds and proving that the impossible is anything but. What sort of odds are you thinking here and in what year do you think that the science may catch up if you had to give us an estimate?

Ed: There’s no telling. I think the probabilities are perhaps as low as 2% in succeeding, but that could be much higher. It’s a subjective thing. There’s no way of estimating. It could be 50% or 60%. As far as how long it takes, it’s a matter of how science rolls forward at what pace, and that’s a very uncertain thing, difficult to forecast which areas of science will move faster and which not so fast. So, I think one could be in storage for anywhere from 50 to 200 years.

Meb: It seems like a call option, right? There’s not a whole lot of downside, really only upside. So even at a 50 to 1, it’s not too bad. My uncle who’s a pilot and an engineer always gives his kids a ton of anxiety by saying he’s written in his will that he wants to be stuffed and put into a knight coat of arms in the hallway and that they have do that in his house, and they spend most of the time at Christmas worrying if he’s actually really put that in the will. Well…

Ed: It’s something like what you mentioned. Something like, well, you mentioned a call option. There’s the Resorts International warrants that I bought a long time ago. I’d say it’s something like that purchase.

Meb: So, in your book…

Ed: [inaudible 00:54:39] the same way.

Meb: Right. In your book, you touched on kinda that there’s a consistent theme that, you know, I found so refreshing because you see so much on Wall Street. So many people so obsessed, you know, with just the dollar and with just money. And with all this behavioral research you spend so much time and people thinking about how to make money. And then there’s been a lot of good books like Happy Money, and some others that say that people are actually really fairly terrible at optimizing on how to spend it. So, they make all the money and they do all the wrong things. They buy a bunch of yachts, and things that may not necessarily, you know, kind of drive the happiness. And so, in the book you touched on an example of referencing J. Paul Getty and said, you know, super wealthy but the happiest he ever was when he was 16 surfing in Malibu.

And just one last question, I want to talk about, you know, maybe you can mention, because I think it’s great for a lot of the younger investors and quants, you know, as they think about their life. You know, how do the success of your funds really, you know, as the years went on, affect your perspectives on the source of real happiness?

Ed: Well, I’ve I thought that the important thing in life is how you spend our time, who you spend it with, and what you do. And money is something which can make that much more agreeable and pleasant and make you much happier, but I don’t think it’s an end in itself. You should do what you want to do and what you like to do, and I think good things will follow.

Meb: We put a great quote in my first book by the climber George Mallory, and then it’s just been on the blog ever since and it says, “Enjoy is after all the end of life. We do not eat to live and make money. We eat and make money to be able to live. That is what life means and what life is for.” One of my favorite quotes.

Ed, one more question for you and then we’re gonna let you go, I saw somewhere that you said, I know you’re a rational science-based guy, you’ve never bought a lottery ticket, is that still true?

Ed: I bought five lottery tickets once when the pool was so large, carried over that I had an edge.

Meb: Well, I wanted to thank you for coming on today, so we said we were going to alleviate the pain of you making a negative expectancy bet. So, I picked up two Powerball tickets on the way to work, do you want the first entry or the second? Because I’m gonna take the other one?

Ed: Okay, I’ll take the first one.

Meb: All right, first one, just so the listeners can hold us accountable, it’s tonight’s drawing. I think it’s 200 million. Your numbers are 25, 28, 37, 41, 62, and Powerball of 20. Ed, good luck on that, by the way. You’ve been a gentleman. I would love to keep you here for six more hours and ask a hundred more questions, but I know you have wonderful, better things to do. Thank you, so much for taking the time today.

Ed: My pleasure. Thank you Meb.

Meb: Listeners, thanks for listening. We always welcome feedback and questions to the mailbag at feedback at the mebfabershow.com. As a reminder, you can always find the show notes and other episodes at mebfaber.com/podcast. You can subscribe to the show on iTunes and if you’re enjoying the podcast, please leave a review. We’ll have a link to the book, “A Man for All Markets: From Las Vegas to Wall Street How I Beat the Dealer in the Market with Ed Thorp”. Thanks for listening friends, and good investing.

Sponsor: Today’s podcast is sponsored by the ride-sharing app Lyft. I only live about two miles from work. My favorite means of getting around traffic-clogged Los Angeles is to use the various ride-sharing apps, and Lyft is my favorite. Today, if you go to lyft.com/invite/meb, you get a free $50 credit to your first rides. Again, that’s lyft.com/invite/meb.

Episode #38: EVBettor, Dr. Bob Sports, “Special Super Bowl Show: It’s Higher-Stakes Poker is What You’re Playing”

Episode #38: EVBettor, Dr. Bob Sports, “Special Super Bowl Show: It’s Higher-Stakes Poker is What You’re Playing” 

 

Guest: Our guest today prefers to be anonymous, instead going by the alias, “E.V. Better.” E.V. works in predictive analytics at Dr. Bob Sports.

Date Recorded: 2/1/17     |     Run-Time: 1:12:33


Summary: In honor of this Sunday’s Super Bowl, Episode 38 is a special, bonus “gambling” podcast. We welcome mystery guest, E.V. Better, which is an alias for “Expected Value Better.”

Meb starts by asking E.V. how he got to this point in his career. E.V. had a traditional finance background, working at a long/short hedge fund for 5 years, but realized he could apply certain predictive analytics that work in the financial world to the sports betting world. He helped create a basketball model at Dr. Bob Sports and enjoyed it so much that he made the jump from traditional finance.

Next, Meb requests a quick primer for the non-gamblers out there; for instance, how the various types of bets works, the “lines,” the most popular bets, and so on. E.V. gives us the breakdown.

The conversation then drifts toward examples of “factors” when it comes to gambling (such as “value” or “momentum” is in the stock market). E.V. tells us there are really two schools of thought in traditional investing – fundamental and technical investing. When it comes to gambling, there are similarly two schools of thought; you have the strength of a team that’s measured by traditional stats (for example, net yards per pass) or technical factors (having been on the road for 14 days…having suffered 3 straight blow-out losses). When you combine these two factors, you better a better idea of which way to go with your wager.

These leads to two questions from Meb: One, how many inputs go into a multi-factor model? And, two, how do you replace older factors that don’t have as much influence or predictive power as they used to? E.V. gives us his thoughts.

Meb asks about “weird” or interesting factors that are effective. E.V. points toward “travel distance,” though the effect has diminished over time as travel has become easier. He also points toward “field type.” This leads into a discussion about betting against the consensus (contrarian investor, anyone?). And this leads into a common investing mistake – recency bias. For example, because the Broncos won the Super Bowl last year, people expected them to be great again this year…and they didn’t even make the playoffs (Meb is still bitter).

Meb steers the direction away from the NFL. Whether basketball, baseball, or whatever other sport, you’re simply trying to find an edge over the house. Meb brings up “variability” (the more games the better if you have a slight edge), and asks how this changes over different sports.

E.V. says duration of season is a huge factor. Also, the level of data available for analysis is key (for example, the amount of data in baseball is amazing). But overall, E.V. says the goal is reduce the variance to make thing as simple and predictive as possible to find your edge.

Meb asks about underrepresented sports (curling, or NASCAR) offering more, or better opportunities (think “small caps” versus the “Apples” of the investing world). E.V. says the issue is finding a counter-party. You might be a great curling modeler, but have fewer market participants from which to profit.

This leads into how to quantify an edge, and what a good edge value should be. E.V. says a 10%+ edge would be fantastic, but it’s important to be conservative in your estimate of just how big your edge is. After all, you won’t have a consistent edge every game. Meb makes an interesting correlation to investing you’ll want to hear.

Next, Meb asks about gambling as an asset class. Where would gambling fit into a portfolio and how would it work together? E.V. says sports is a unique alternative asset class that’s uncorrelated to other markets. This quality makes gambling an interesting addition to a portfolio.

Next, Meb moves to “quick hits” – shorter questions, many of which came from listeners via Twitter.

  • What’s the worst bad beat you’ve seen?
  • Have you looked at “intra-game” gambling, or do you only focus on full-game bets?
  • How does a sport with a small dispersion in scoring (like soccer) affect how you bet versus a high-scoring sport (like basketball)?
  • Have you thought about any lines that change over the course of a day based on the concept of betters losing in the morning and becoming increasingly aggressive in the afternoon (going on tilt, trying to win back money).
  • What do you think about “the hot hand”?

You’ll want to hear E.V.’s answers.

Finally, we get to the topic du jour – the Super Bowl. Meb asks E.V. directly, “Who do you like with New England at -3?” If you’re thinking about betting this Sunday, don’t miss it.

There’s far more in this bonus episode, including discussion of betting on the results of the Super Bowl’s coin toss… How long it will take for Luke Bryan to sing the National Anthem… How many times will “Gronkowski” will be said by the commentators during the Super Bowl broadcast… Want to put the odds in your favor? Then join us for Episode 38.


Sponsors: Soothe and TheIdeaFarm.com


Comments or suggestions? Email us Feedback@TheMebFaberShow.com

Transcript of Episode 38:

Welcome Message: Welcome to “The Meb Faber Show,” where the focus is on helping you grow and preserve your wealth. Join us as we discuss the craft of investing and uncover new and profitable ideas all to help you grow weather and wiser. Better investing starts here.

Disclaimer: Meb Faber is the Co-Founder and Chief Investment Officer at Cambria Investment Management. Due to industry regulations, he will not discuss any of Cambria’s funds on this podcast. All opinions expressed by podcast participants are solely their own opinions and do not reflect the opinion of Cambria Investment Management or its affiliates. For more information, visit cambriainvestments.com.

Sponsor: This podcast is sponsored by the Soothe App. We all know how stressful investing in volatile markets can be. That’s why I use Soothe. Soothe delivers five-star, certified-massage therapists to your home, office, or hotel in as little as an hour. They bring everything you need for a relaxing spa experience without the hassle of traveling to a spa. Podcast listeners can enjoy 30 bucks to their first Soothe massage with the promo code “MEB.” Just download the Soothe App and insert the code before booking. Happy relaxation.

Meb: Hello podcast listeners. After our two-week podcation, we’re back with a lot of fun podcasts lined up. We just had John Bollinger this week and we wanted to squeeze an extra one seeing as it’s Super Bowl week. So we got a unique podcast today. Our guest is anonymous and we’re gonna go by his Twitter handle E.V. Better. Welcome to the show.

E.V.: Hey man. Thanks for having me. I really appreciate it. I mean I particularly enjoy this podcast so it’s a real pleasure to be on.

Interviewer: Well good. We’re gonna have back-to-back gamblers. I’m not gonna give away who our next guest is after you but we’re gonna have back-to-back gambling episodes. So, E.V., I’m gonna call you that throughout the podcast, which for the finance types who understand, stands for expected value. But today’s podcast is all about sports betting, gambling, handicapping. So why don’t you introduce yourself? Tell us a little bit about how you got to your position today, which is working as a writer and a handicapper. What is your title? Is it handicapper of sports…? What’s the correct phrase?

E.V.: Predictive analytics, sports analytics at Dr. Bob Sports so, and I would say that would be my official title.

Meb: Sorry, go ahead. I was gonna say Dr. Bob is a site for those that aren’t aware. He’s been around for probably 20 years and it’s had a statistical quantitative bent towards sports analytics and betting. So, yeah, tell us a little bit about your background. How did you get hooked up with Dr. Bob?

E.V.: You know, I took a traditional finance background coming out of school. I went through an investment banking program. Went into private equity and I worked at a hedge fund, a long/short hedge fund for around five years. Throughout this time, I always thought I would be in finance for, you know, the rest of my career. You know, towards the tail end of my stint with the hedge fund, I decided… You know, I was being burnt out and decided that I wanted to take a vacation while I was young instead of while I was too old. So I took some time off, went traveling, did a lot of research on different things. And you know, all this time, I was continuing to invest in the sports…or in the stock market but also in the sports market. And a lot of new statistical techniques, predictive analytics techniques I used from the stock market, I could apply to the sports market.

And so, when I got back to San Francisco, Dr. Bob is also based out of San Francisco, I got connected with him. He was looking for someone to help with a…he called it “basketball model.” I, you know, worked on it with that for him for a short project. It had really promising, good results and through that, I ended up going full time with him. And we decided that, you know, I would do…help with baseball modeling and then take over for the football handicapping at the site. So me and him do football and we use, you know, completely quantitative model with no… You know, we build a model but we don’t have any sort of direction on who it’s gonna pick.

Meb: We’ve seen this kind of huge interest and genesis of popularity for sports analytics and betting. Certainly, Moneyball helped popularize it for the broad populous. But for those of the listeners that either aren’t into sports betting or are just traditional financial types, why don’t we do a quick primer for the nongamblers out there? And maybe give us an overview, just very briefly, on how sports betting works, some of the most popular bets and lines. We can talk about lines, money line, but just a real quick overview of how it works.

E.V.: Yes. So the sports betting market are run by sports books, traditional Vegas books who set lines. There are a couple of different lines you can bet on. The most popular ones would be an against-the-spread line which will happen in all sports. You know, for example, for the Super Bowl, the Patriots are favored to win by three points. So they’re essentially making it a 50/50 proposition that Patriots win by at least 3 points. If they win by less than three points, two or one, then the Falcons would win. So you’re either laying or taking points with a certain team. That’s probably the most popular bet and with the highest limits would be against-the-spread bet.

The second bet would be a moneyline bet which is the same thing as an against-the-spread bet. It’s just a win probability which is the spread, amount of points a team is given is based off of the win probability and it’s a simple function of if the team… You know, a team that’s given 3…or that needs to lay 3 points would be expected to win by approximately 60%. So you’d be laying 150 to win 100 or, you know, that equates to 60% win probability. So that’s the second most popular bet which is called the moneyline bet.

And then there’s a total bet, which is on the total number of points that are gonna be scored. So the total for the Super Bowl, for instance, is set at fifty-eight and a half. So if both teams combined scores go over fifty-eight and a half, then that is… You can either bet on the over or the under for that and that’s generally set as a 50/50 proposition with Vig or I guess the house cake set on both sides so.

Meb: And so Vig is, for the listeners who aren’t familiar with betting, you know, Vegas takes its cut which roughly equates to just like in a casino or in trading on Wall Street, it’s almost like bid-ask. You know you’re paying a little bit on the winning bet if you win and it equates to what? Roughly it’s 10% on one side but roughly 5% overall, is that correct?

E.V.: Yeah. About four and a half percent overall minus 110 odd. So you pay when you lose. So you risk… So generally, the standard bet would be 110 to 100. So you’re gonna pay that 10 cents extra on the dollar when you lose. Yeah, it roughly equates to four and a half percent expense ratio. So you need to be above fifty-two and a half percent handicapper to be profitable.

Meb: Which is almost like talking about Blackjack and a lot of people say, “Man, I only gotta get slightly above 50%, right. This seems like an easy game.” But in reality, much like the efficient markets of investing, it’s actually pretty hard. However, you know, there’s been a lot of academic research over the years. There’s been a lot of publishing. Although, there’s not nearly as much as you see in the financial markets for various reasons but there are some academics that talk about it. I know Justin Wolfers out of Stanford, there’s been a lot of books, some famous ones by Stanford Wong. MIT even has a Sports Analytics Conference now which I think is next month and has a lot of great speakers like Billy Beane of the Athletics as well as Nate Silver from FiveThirtyEight, etc., etc. So it’s become a lot more popular.

So I figured, you know, since most people are familiar with the NFL and that’s one of the most popular in Super Bowl time, we’ll kind of continue to use that as our example before going into some other ideas. You actually had a monster year this year. So we talk about that 52% just to break even. And if I read correctly on the Dr. Bob’s, I think you did something like 70% against-the-spread with your picks this year, which is a pretty massive outperformance.

So let’s start talking about the NFL. Why don’t you give us an example maybe of a factor? So in investing, we all know that, say, value is worked historically, Buffet style or momentum. What’s maybe a factor that either historically has worked or maybe doesn’t anymore or historically is something that you could talk about? That has given betters an edge over the years that you think would be a good, kind of, introductory example of something that may have or continue to work in the NFL betting world?

E.V.: Before I touch on that, I just wanna mention Dr. Bob was actually a presenter a few years ago at MIT Sloan’s Sports Conference.

Meb: Oh, cool.

E.V.: And so that sports conference doesn’t have a sports betting bent. You will see a lot of analytics come from the sports betting worlds go to that conference. Because figuring out player value and figuring out team value is essentially what sports betters are trying to do.

Meb: Maybe we could get a journalism pass and that would be great. Have ever been, E.V.?

E.V.: I’ve never been but, like I said, the guys I work with have been before, and have presented there, and been on panels. So I’ve heard mixed reviews about the quality, again like any conference, but it depends on who’s gonna be going and speaking so.

Meb: All right. Well sorry to distract you, back to the NFL.

E.V.: Sorry, yes. So the factors at work, so basically when you talk about value and momentum, there are really two schools of thought in traditional finance really. The way I think about it, there’s fundamental and technical investing. Where fundamental is you ‘re looking at… you’re figuring out the intrinsic value of a company through DCF, simplistic multiple EBITDA, PE, price to book, etc. And then there’s the technical aspect which you’re looking a momentum, [inaudible 00:11:18], and things that don’t relate to the intrinsic value of that company.

And in sports betting, it’s the same way. You have the sort of strength of a team that can be measured by its, you know, traditional metric that you see, net yards per pass, on the offense or the defensive side, play success rate. Things that can be measured on a team basis, which I’d call the fundamental factors of investing. And then there’s a second group that are less wildly used. It’s the technical factors which would be like a team coming off of a huge loss. Playing 3 road games in a row, having 14 days of rest versus 7. All these factors need to be… While they don’t pertain to the intrinsic value of that team, they’d be pertaining to a team’s motivation in how they set up to play that next game.

And so, when you can combine these two types of styles, you really get just like you would get in any quant investing strategy would look at a value and momentum, and combine those to get a better tilt. You can do the same thing in sports investing. And, you know, some fundamental factors, I’d look at that are interesting are something like turnover differentials. Where teams that generally have high turnover differentials tend to regress more…tend to be very successful teams because they’re getting a lot of interceptions, fumbles, etc. But a lot of these things have a lot of high variance components to them.

So you’re gonna see, over the long term, that a lot of these regress downwards. It’s hard to sustain elevated levels of turnover differential. So that you won, sort of simplistic one that you could look at as a factor that is gonna be factored in any model. And what that does is it makes a lot of fundamental factors look better like points scored, defense. Because teams are getting shorter fields and so when you can compensate for these, you get more accurate predictors of how the team will do going forward.

Meb: You know, it’s interesting, when you think about this multi-factor approach, which you’re talking about, and it’s so endlessly complex. So starting to think about a market like sports betting where a factor becomes known and the same thing happens in investing. We often talk about price to book, which is one of the most talked about and published factors in the literature, and then a lot of money went into it. It has worked much, much…had a much worse track record in the following decades than it did in the early ones. And I’m sure the same thing happens in sports betting.

And so, you compiled this multi-factor model and one question would be, how many inputs do you actually look at in, sort of, this multi-factor model? And then two, you know, how do you think about either introducing new factors or removing factors that maybe worked historically? That maybe the market has caught on to and then doesn’t really have as much, sort of, influence as they used to?

E.V.: Yeah, those are great questions. I think it’s the same way that you would test any predictive model. You know, there’s a lot of hyper parameters that go in with the model. You prune, you do a lot of testing, iterations in trying to improve these models. Figuring out which factors to leave in, which factors you may have to leave out, and eventually, you come up… You know, what you’re trying to eventually find is an edge that you have in this certain game based on a lot of these different factors.

You know, a big difference in sports betting versus the stock market is there’s no bull market in sports betting. You can’t ride a rising wave. So it’s pure… Your comparison to Blackjack was apt in that you’re literally just playing edges. And so trying to find out things that have been priced into the market and then trying to find things that aren’t necessarily priced in the market is the game you continually play with sports betting so.

Meb: It’s a pleasant distraction for me. There was a couple of years ago where I started to go down this dark, deep examination into sports betting. And then I kind of shook my head and said, “Hey, no, this isn’t my day job but it’s a lot of fun.” And then you read about some of these factors that are fascinating to me. And one that had caught my mind was something like circadian rhythms. Meaning a team on the east coast, and I may get this totally backwards, but that was flying to the west coast and playing a late game. You know, meaning that their body was normally like thinking they should be asleep. And there was actually a little bit of an edge that could be had there.

Are there any sort of weird factors that you can talk about? And you may say, “Look, these are proprietary, too bad.” Any sort of weird or interesting factors you could talk about that maybe people would be surprised about. Rather than say, “I think you’re favorite net yards per pass or whatever it was?” Any kind of kind weird ones that come to mind?

E.V.: Yeah. Well I would say what you just described there can be accounted for in a lot of ways. You’ll see it a lot more in amateur sports or, you know, college athletics versus professional. But travel distance, you know and that’s one of the factors that used to have a much bigger difference than it has today. Distance traveled for teams going, distance wise longitudinally, latitudinally does have a difference in how teams play. But that effect has been diminished over time and, you know, sort of the narrative behind that is that travel has gotten a lot easier for these teams, right?

So, you know, before a college team is taking a bus and couldn’t study. But now they have iPads to watch a film on a flight and it makes it a lot easier to prepare for the next opponent. Things like that are interesting and you will have to keep watch. I would say some interesting ones that maybe well-known would just be, you know, the field type. You know, as it relates to football, whether you’re playing on grass, AstroTurfs, open stadium, closed stadium I mean these have statistically-significant impacts on point totals and different styles of teams benefit from different styles of surfaces.

So you’re looking at really any type of factor that you can quantify, or measure, or turn into a factor. You know, we’ll try to test and see if it has an impact on to the predictive accuracy.

Meb: You know, there’s a lot of talk of and a lot of sites will publish the percentage of bets that are lining up on a certain side. Does that come into play at all this kind of anti-consensus or betting against the crowd?

E.V.: Yes. So, you know, it does and it has an effect in a way. So for NFL for instance, you know, the way that… When I talked about the fundamental and technical aspects of evaluating games, their early season versus mid-season is a different way that you evaluate. And you see a lot more better biases come into play early in the season. And the reason for that is because it’s impossible really to gauge a team’s strength off of preseason indicators or… Because you don’t really know how X player is going to factor in to their new team. You know, especially in a lead like the NFL where there’s a high amount of turnover. Early in the season, you are gonna have preseason grades on these teams but it’s hard to measure the actual team strength without seeing them play the game.

So what you’ll see early on in the season is what you just mentioned, better biases coming into play. Like you know, I know you’re a big Broncos fan. You know, early in the season because they worked in the Super Bowl last year, they had high expectations going into this season. You know, now this year, they didn’t make the playoffs. So next season, you’re gonna see the better bias be that they’re not as great of a team as you thought they were coming into this season.

And a lot of times, you’ll see over and under-reactions based on the way a team performed last year and based on how you know the public is gonna view them. And through that, that’s how the bookmakers then set the price. And that’s where you can try to take advantage of your edge. And that was sort of it, just basically…

And then also, you know, I guess, you’ll see better biases all throughout the season. But for me, it really takes place in the early season, and then it’s sort of pricing anomalies later in the season. But early in the season, a lot of what I’m looking at is better biases. And how to capture how the betting market is going to view certain teams when there’s no real, concrete evidence on whether a team is this much better than they should be or not.

Meb: That was interesting because the “fading consensus” was something I had written about a few times in the blog. We have an internal, company-wide network where you bet…get the games against the spread. And, you know, for me, I just always bet the anti-consensus and had won. I had a pretty good year this year. Historically I figured…I seem to remember it comes in around the extremes are 55% against the spread. So good and enough to maybe beat the Vig but not that crazy interesting.

And so, of course, being the over confident guy that I am, entered the Super Contest, which Hilton puts on…I believe it has been going on for over a decade where you have to pick five games against the spread each week. And so I did this in 2014 and the winner usually is in the 60% range, somewhere between 60% and 70%. So I figured, you know, if this has a 55% edge, I just need a little luck, maybe a little magic, and I can hop into the top decile from maybe just the top quartile. And sure enough, 2014 was the highest percent winning for the winner. It was like 72%, which of course said I’m never gonna play again. But I’ve continued to win the inter-office this year. Jeff’s looking at me because he came in dead last and that includes Jeff by the way. I missed an entire week, so anyway.

E.V.: I think what you’re touching on is a great point in that because, you know, it’s a common misconception that books set the lines to get even action on both sides. And, you know, there’s been research done. There’s a good paper out by Steven Levitt the author of “Freeconomics” basically that, you know, these sports books they shade their lines based on well-known, better biases. And these biases include you know, loving historically-good teams, having… And so they will shade these numbers to reflect this side. And so because they know, they want action on the other side to increase their possibility so, you know…

Meb: And that particularly happens in the Super Bowl, is that correct?

E.V.: Well, so the Super Bowl, yeah, has an interesting aspect because, yeah, there’s a huge bias. It’s one of those largest, if not the largest, publicly-bet sporting event of the year. And so you’re gonna get a lot of first time betters who don’t, you know, look at 100 games in the season. And so when they see a team, you know, they see a team like the Patriots and they see a team like the Falcons, a bias that a lot of people have is to root for the underdog. And to bet on that moneyline where you’re getting plus money. You know, you’re betting $100 to win more than $100. And so what sports books will generally do is they’ll shade their lines downwards on that money line. So you’re going and conversely do the inverse to the favorite. So you’ll get a cheaper price betting the moneyline on the favorite than you would in a typical game.

And so, you know, there are certain intricacies throughout the sports thing world like this where the book are not necessarily trying to take balanced action. A lot of times, what they’re trying to do, you know, is increase their profitability. That’s why a contrarian betting strategy like the one you… A simple one like that can be pretty successful.

Meb: And this is interesting. So to me, it’s interesting because the NFL would seem to be the equivalent of a very efficient market where there’s a lot of money chasing it, big bets. And so, you also weighed in some other sports, right? So I know you do major league baseball which from a gambler’s perspective to me…or college do you do…? And you do college sports, college football and basketball, is that right or no?

E.V.: College basketball… So I’ve done models…I’ve built predictive models for college basketball which I’m improving actually as we speak. And then I did a preliminary baseball math model over the summer working with Dr. Bob on these projects. And you know, these are, yes, just different betting markets where you’re trying to do the same thing, gain an advantage over the house.

Meb: And so the cool thing about that is that, you know, in the investment world, we’d call this breadth. So from a gambler’s perspective, if you have an edge, the more bets you take, the better it is because it spreads out the short term variability. So sports like major league baseball and basketball are great because they have a massive amount of games, massive amount of teams. NFL is only gonna be 16 weeks per year plus pre, post-season. So to the extent you can gain an edge in those…

So talk a little bit about the differences in some of the sport. So what are the main differences between handicapping and analytics on the NFL versus major league baseball versus say college basketball. What’s similar and what’s totally different?

E.V.: Yes, no. That’s a good question. There’s a lot of differences and, you know, one of the big ones you mentioned on was the duration of the season. You know, a big one that you see in college basketball and baseball that goes in conjunction with that is the level of data. You know, baseball is really the first sport to, sort of, who are at the forefront of this sabermetrics, predictive analytics in sports. It’s really there. There are data sets out there that we use that are pitch by pitch, where you can get literally the rotation count, the number of spin the baseball is pitching, spatial coordinates of the data. When a pitch leaves the pitcher’s hands to when it hit the catcher’s gloves. So there’s a lot of really granular data in the baseball field. There’s a lot of games played.

And so with that, you know, you have to come to the betting market with the knowledge that this is kind of there for everyone. So you have to know that, “Can I incorporate this?” Whenever you’re making a bet, you have to just ask yourself, “Do you actually have an edge in this market versus the sports book versus other market participants?” And so with a sport like baseball, you’re gonna have a lot more data, you’re gonna need to be a lot more precise. Factor in everything from umpires, to weather, to stadium size, to type of pitcher. So from that standpoint, these sports can be very different. You know, college basketball is also different than football. But where they all share similarities and where, you know, really all predictive analytics share similarities is that you’re just trying to reduce the variance within these systems to come with sort of the true odds of the game, no matter what it is.

So in basketball, high variance events could be how well a team shoots from the three-point line that day. You know, I talked about for football high variance events could be the turnovers or baseball, you know, the contact percentage… You know, the difference between a single and an out could be a few feet over a second basement gloves. So there’s a lot of, sort of, variance within these sports that you then have to try to… You try to figure out where these sort of leverage points are and then release them all to try to find an edge. So while they’re different sports, the concepts are pretty much the same in trying to gain an edge in these sports.

Meb: Oh, it seems to me like there’s a lot of sports out there and you’re kind of covering the major ones but they would seem to be under exploited. Meaning, you know, the NFL and Major League Baseball, in my mind, and I could be wrong, seem to be probably the most sophisticated with most people chasing it. But I don’t know. NASCAR or I don’t even know if there’s betting markets in curling, or cricket, or everything else around the world. Is there sort of a range where you would say, “Hey, here’s some markets that there’s probably a lot of opportunity that there’s not a lot of people weighting in?” Just the same way in the U.S. if you’re focusing on small microcap stocks where no analyst are covering it or you’re focusing on Malaysian, you know, companies. There’s probably a bit of an edge to have where there’s not as much competition versus the 10,000 person who’s following Apple. Are there some sports that you think that there’s a lot of opportunity and fruits still to be had or what’s your perspective there?

E.V.: Yeah. You know, you made a great analogy with small caps versus the Apples of the world and it’s the same thing. But a big difference in sports betting is the [inaudible 00:30:22] effect imposed to you finding a counter-party. So you could spend all the time you want and you could probably get to be the best predictive modeler in curling but, you know, how much money are you gonna make from that really? Because you know the limits on a curling event or some sort of esoteric sport is gonna be really low.

Where when you get to these major sports, you’re gonna see higher limits and also you’re gonna see more market participants in a sport like the NFL. The NFL is a unique sport. You know I would say more unique than baseball or even basketball in that the public likes to bet the NFL. The public doesn’t necessarily like to bet baseball or basketball where, you know, every person that you meet is gonna have an opinion on football. So you could say that that’s a disadvantage but you could also, you know like we talked about earlier with the biases, consider that an advantage in some respects. While, yeah, I agree that the lines are probably softer on more esoteric sports, there’s a lot less capital to be had just because of the way book set limits.

Meb: You can’t move around $10 million bet sizes betting cricket and curling is what you’re saying?

E.V.: You know, pretty much sure about it. But curling, yeah…

Meb: I was gonna say this is a great segue, you know, and this is kind of a first podcast. There’s so much to be talked about here, we may have to have you on regularly but.. So we’ve kind of talked about the overview, about NFL, and a few sports. So assuming that you have an edge and like let’s say your NFL system, let’s say you’re confident that you have an edge. Now that doesn’t mean you’re gonna win every year, it doesn’t mean you’re gonna print 70% a year but let’s say you have an expected value where… And what’s a good estimate? Is there something you target? Is it 60%? Is there a certain sort of number that you’re looking at on a per-year basis by the way?

E.V.: You’re talking about returns or…

Meb: No, no, no.

E.V.: …you’re talking about…?

[crosstalk]

Meb: Percent wins. Okay. So we’re gonna go into the returns and money matters here in a second. But is there kind of like against-the-spread percentage of games that you target or is that totally not something you even really focus on?

E.V.: No. I mean absolutely that’s something we… We quantify how much of an edge we think we have but it’s, you know, been shown that it’s hard to actually… Most people are overconfident with their hedge so we generally try to either not talk about that or really be concerned about how much of an edge we think we have. So if say we think that this game is mispriced and instead of -3, the Patriot should be -6 favorites, you know? That will be a big discrepancy in terms of win percentage. I’d probably say you have a 10% plus edge, which would be a huge edge. And I would say that, you know, you really have to study your methods, your process and make sure that… And just generally be conservative on what type of edge you think you have. It’s gonna be different for every game. You’re not gonna have a consistent, you know, 3% edge every game. Some games, just like when you’re picking stocks, some stocks will show value based on the indicators and filters that you have. Some games will show up with a 5% edge, some will show up with a 2% edge. But, you know, generally just like with investing, you wanna err on the side of conservatives and how much of an edge you actually think you have.

Meb: And that’s a great example. I mean talking about Warren Buffet, I actually watched his documentary last night on HBO which, listeners, it’s great, by the way. But he talks about the Ted Williams “fat pitch,” right? So “waiting for that fat pitch.” And the funny thing about, you know, service like a yours but in investing as well as is it’s not that sexy to talk about, “Hey, man, we’re targeting 55% or 58% win rate,” despite the fact that that will make you a rich man one day. The same thing as investing. If you say, “You know, we’re expecting this globally diversified portfolio to do X.” You know the sexy stuff is the people saying, “Oh, we think you can do 20% a year” as unrealistic as that is. But people, and you mentioned, are looking for the lottery tickets on betting where they bet these huge underdogs at a moneyline of 500. The same way that an investor is looking for small caps or these lottery tickets, but on average they don’t work.

So let’s transition a little bit. I’ve seen a quote where you said, “Sports analytics is a misunderstood asset class,” and I want you to explain a little bit about that. So that if you did have an edge in say NFL, and Major League Baseball, and college basketball, you know, treating that as an asset class that’s something that you think you can have a positive expected value, how does that fit in? How do you incorporate that and how do you start to think about kind of money management and bet sizing the same way you would, one, as a standalone portfolio but also as a portion of someone who has a larger investment portfolio?

E.V.: Yeah. I think, you know, just like when I was working in finance. You know, you use proportional bet sizing to determine how much you’re going to put on each independent event. Because sports is a unique culture and an asset class in that it’s uncorrelated with the rest of the market. I think that’s one of its biggest advantages whether the stock market is going… You know, when the stock market goes up, the housing market…you know, there’s some correlation with that.

And like we saw on the financial crisis, when things go down, you know, [inaudible 00:36:32] goes to walk towards one. You know, but that’s gonna affect how the Golden State Warriors are gonna play. That’s not gonna affect how the Atlanta Falcons are gonna play. So you get these independent, uncorrelated asset classes where if you do truly have an expected edge, you can really calculate and maximize your returns. Using you know simple formulas like the Kelly Criterion in which you determine your edge and the odds that you’re giving to come up with a proportional bet size to your bank roll. And through that, you know, you can start to… You know, just like if you’re playing Blackjack or just like if you’re doing any sort of events which are market agnostic, you’re not trying to predict the outcome of these events. You’re trying to play these edges that you have in the market and try to maximize the return from these different edges so.

Meb: You know, one of the biggest mistakes we see people make not just in investing but also in sports betting and in the casino is over betting. So they’ll sit down at the Blackjack table and they’ll be betting 10% or 20% of their bank roll on any given bet. And like you mentioned, that’s probably a recipe for disaster just because of the short term variability. The old school flip a coin six times in a row, you know, there’s a chance you’re gonna get six heads and a lot of people just don’t think about that.

And so, I saw one quote you had somewhere where it said…talking about bet sizing and thinking about Kelly. It says, “Your bet sizing is kind of correlated… How much are you willing to lose?” And so for a lot of people, they say, “My god, that sounds boring.” But if you have say $100,000 bank roll, a lot of these bets being placed at 1%, 2%, 3% of total bank roll but scaling that up and down based on the edge you think you have or the particular opportunity, right?

So we have a lot more to talk about. By the way, so what do you think is capacity? So let’s say Bill Gross is listening to this podcast. He says, “Oh, man, I need to start a betting fund and I wanna target three different sports.” What’s capacity like? Is it 10 million bucks if you really wanted to have an army of disguised betters in Vegas like Billy Walters used to in the computer group? Or is it a million bucks, is it 100 million? Like what’s the capacity on a sports betting operation if someone was to go about it?

E.V.: Yes. As someone who looks to maximize earning potential from this endeavor, this is definitely something that I’ve looked into and it’s… You know, we think about it from a domestic perspective just, you know, like you point out a lot of times. People look at stocks from a domestic perspective. But when you look globally, if you look at countries like the U.K., Australia, there’s a lot more fee regulation around sports betting in these countries. And so, you’ll see a fund set up that will place millions of dollars on, you know, a lot of times a soccer match because those are the most heavily bet overseas. But you’ll see these… You know, depending on what sport you wanna bet, depending on what edge you wanna have, there a lot of markets especially overseas.

We think domestically about Vegas Casinos and that is a small fraction of the amount of volume that gets transacted globally. I think I’ve seen from the 8GA, you know, who was estimated $100 billion in transactions that went on last year in gambling and sports betting. And globally, that number is gonna be much bigger. Because, you know, obviously when you have entities able to bet into these markets, you’re going to get a lot bigger players. It’s just it’s higher stake poker is what you’re playing. So here, because of the regulation that surrounds it, they can get a little more murky on how much you can get down, and the limits, and things like that. It’s smaller domestically but internationally, if you’re willing to look there, you’re gonna find much bigger markets.

Meb: Well, there is some stat already that Macau’s revenue is something like four times Vegas already. Just something that’s just totally astonishing. And I see that one of the most gambling-centric cultures in the world is getting to ready to add casinos. Isn’t Japan coming online with casinos? I think I saw that the other day? Anyway, so it’s interesting. You know, I think a lot about it but let’s move on.

So we now, are gonna move on to a little bit of quick hits. So these are shorter questions. Feel free to answer as long as you want. But also there are some questions that were submitted from Twitter and if the responses are any indication, sports betting is a very large interest for a lot of people because we got a ton of questions. So feel free to take as long or as short as you want with these questions.

First one, what’s the worst bad beat you’ve seen either personally or just in sports betting over the last few years?

E.V.: Oh, man, I mean I could go into a lot of different stories on different bad beats. I mean I think any time you have, you know, the traditional, yeah, you bet the under on a football game and it’s garbage time for a team. I think last week’s Pittsburgh-New England game I think, you know, the game was well out of hand. I think the Patriots were up 21 plus points. And, you know, the game is really meaningless under three minutes to go for the Steelers but they’re still scoring points. And for the regular person, you’re not watching the game. But for someone who has a financial interest in the game, you’re at the edge of your seat and just thinking to yourself, “Why is this guy trying to sort of touchdown passes when the game is out of reach? Just give up.” And so, you know, that over will hit and it will just be one of the many bad beats. But you know, you take the good with the bad because a lot of times you’ll get it the other way. So I think just understanding the variance, the inherent disorder that is gonna be in football, you have to do this and look at games over a long season. You have to expect it and it’s gonna go both ways so college…

Meb: I remember before I became a quant way back when, one of the reasons I became a quant is because I took on way too much risk. I would take as much risk as you’d give me. And I remember I had something like a nine-game parlay which, listeners, if you don’t know, you have to like all nine games right which is the equivalent of buying Apple in 1980 and then forgetting about it for 20 years. There’s a very, very small chance.

So I was getting ready to win this massive game parlay. And then Deion Saunders who was playing for the 49ers returned some punt, or a kickoff, or a touchdown which made me lose the entire parlay. And I will never, never forget that.

All right, next quick hit, have you looked at any anomalies or thought about intragame? You know, I know there’s a lot of markets in betting to kind of do this future style where the betting can go on during the game, as well as quarters, and full game lines. Have you looked into that at all or do you focus purely on the full-game bets?

E.V.: Oh, absolutely. We’re really in an inflection point of how sports market places are evolving. You know, traditionally, the bets I talked about earlier on the show, you know, against the spread, totals, money line, those are all pregame bets that were set. Now, these books will set in-game line. You can literally bet in between drives. You know they’ll adjust their lines based on win probability. And what I’ve been doing this past season to some, you know, success was just getting out… I, you know, based off of some of my football models, did a half-time line. Where a half-time I had an automated program simulate how the game would play out. And if there was an edge based on the half-time line that most all sports books would put out. You know, I would Tweet that out and say, “Hey, you know, the book says that there’s 52% chance, my simulation has a 55% chance,” or whatever that maybe. So I think that in-game, there is a lot of opportunity too where a lot of people studied the full-game lines. But in-game probabilities, half-time, a lot of these things are newer and just with newer propositions. There is gonna be less data. There’s gonna be less people that are really good at that. So I think that, you know, these are gonna be things that are gonna continue to evolve and things that definitely we’re looking at exploring and exploiting so.

Meb: Well, I mean back in the day in a lot of the books, I mean you go back far enough, they used to do the full game, half game, quarter lines, or whatever, they would just divide it in half. And that’s obviously very sub-optimal but one of the reasons that the half-time line may have an edge is because the books have less time to come up with [inaudible 00:46:24] line and less time for the market to react. And so that’s a potential anomaly that maybe interesting as well.

Next question, Twitter, how does a sport with a small dispersion in scoring, like soccer, affect how you bet versus one with a higher level like basketball?

E.V.: Yes. So I mean that’s a great question that has a lot of levels to it. And I would say, you know, anytime you look at a different sport, you have to look at how much skill versus how much variance is within the sport.

So with the game like basketball, you’re gonna have, you know, around 100 [inaudible 00:47:05] of the game, in a professional game, around 65 in a collegiate game. And so, you know, more often than not, the true winner is gonna come out on top. It’s gonna be very rare that you see the Golden State Warriors lose to a team that they shouldn’t lose to.

Whereas, you know, in sports with fewer positions like hockey…you know, soccer is a little different, they have a bit more. But a game like football, right, I compare football to soccer, you know, I’d estimate the variance component to be around 25% to 35%. So because, you know, in football, you only have 22 drive the game, and soccer, I’m not sure of the correct…exact amount of possessions but it’s far fewer than what you’re gonna have in basketball.

So, you know, if you can capitalize on one of these opportunities, then you’re gonna have a much higher chance of winning. And it’s gonna be a lot harder even if you’re an underdog for the favor to come back. So I would say that’s one of the…whoever asked that question, that’s one of the key fundamentals and the first steps in breaking down any sport is determining that, sort of, skill-to-luck component that is involved in the game.

Meb: Michael Malbeson [SP] who, I think, is at Credit Suisse now has written a lot on this as well as Charlie Ellis, and well add some links to the show notes. But talking about games that are a little more dependent on luck versus games that are a little more dependent on skill really, really interesting stuff. We’ll include in the show notes.

Next quick question, have you thought about any lines in a sport that changed over the course of the day based on the concept of betters losing in the morning and becoming increasingly aggressive for long shots in the afternoon? And the common thoughts would be either horse racing or of course that the NCA tournament where later in the day, people that lost all their cash are getting increasingly aggressive in poker. In a lot of sports we call this “going on tilt,” to try to win back that money. Is that something you think books or you guys adjust for or ever thought about?

E.V.: I haven’t adjusted for that but I would say that, you know, there are obviously better biases that books take advantage of so…

Meb: Are you gonna tell us what they are?

E.V.: …you know, I wouldn’t be surprised if the books realizes that they had a huge winning day. And that people are trying to make money back and know which way the shade a line. And that would not surprise me. That’s not a factor that I’ve looked into. But, you know, just knowing that it’s not a true marker when there’s a buyer for every seller. It’s you versus the sports book. So knowing that you know, it’s not surprising that they try to take advantage of sports that are biases.

Meb: One more question, a quick hit and then we’re gonna move on to the Super Bowl. What do you think about the “hot hand?”

E.V.: You know, the “hot hand” is something that I’m not a believer in. You know, just because like I pointed out earlier, the goal in predicting these outcomes of these matches is reducing variance. And so, when you think about streaks, when you think about flipping… You know, flipping a coin 6 times heads in a row doesn’t make the next time any more or less likely that it’s gonna be heads. I believe that, you know, there’s a true value of what a shooter is shooting, when a passer, his completion rate will be and they’re gonna regress. How quickly or slowly that that happens, you know, is the tough part in determining. But eventually, you know, I think there’s a lot of variance within these games and we try to build marriage into the pond.

Meb: That’s great and that’s interesting. So you and I had actually talked about this before and there’s a good book by Aswath Damodaran that just came out. And on of the biggest challenges for a quant, like myself, or you who has this quant betting model, is putting a narrative around that system. So it’s pretty boring to go on CNBC and then be like, “Meb, why do you not like, you know, U.S. stocks or what is going on?” In particular, it’s really hard for me in the early days when we were just talking about trend following.

And so if you ever watched David Harding of Winton Capital go on, it’s the most mind-numbing thing for the interviewers. And I actually sympathize for a quant, it’s just like that’s what the model says, and that’s the answer to like 99%. So trying to weave in a story around why you like these various opportunities is tough but we’ve been getting a little bit better mainly because we hired Jeff but…

So for you, we’re gonna move on to Super Bowl. And now, I’m gonna start asking you some specific questions and if you say, “I’m sorry that’s paywall,” that’s fine. Who do you like? New England -3, who do you think is gonna win?

E.V.: Yeah. So you know, the games is really interesting from a perspective that New England has been something like 14 and 3 against the spread. I mean 14 and 3 against the spread this season, continually outperforming market expectations which, you know, is rare [inaudible 00:52:48]. But Atlanta has a historically good offense. And, you know, basically like you said, it’s boring to say but the models has a slight lean towards Atlanta. It’s not a play either way but it would be taking Atlanta +3. A lot of that has to do with their historically good offense and New England’s strength is [inaudible 00:53:12] adjusted defense is actually not that good. Taking the Falcon’s plus the points would be the lean.

The better play, I think, is on the under or that the model has is on the under. You know, Atlanta, just like New England, is an interesting team, outperforming market expectations against the spread. Atlanta is something like 14 and 2 on the over to the season. So the market has continuously undervalued their ability to score on any type of defense. Last week, they had a totals at 60 which was the highest ever seen in a playoff game, and one of the highest in something like 17 years. And it went over that totally.

You know, the market has continually just set expectations high and now, the total is at fifty-eight and a half where the average total for Falcons games during the season was 50. You’re seeing a pretty big market correction. You know, I think that there’s a lot of values, sort of, on that under so I think that’s the better play.

Meb: And so you mentioned Atlanta which I like to hear because as a Bronco’s fan, I kind of despise the Patriots. We got a lot of Pats fans in the office. But you also said in your article about the Super Bowl betting anomaly. Didn’t you say that…and maybe I read it wrong. Isn’t that sort of favoring the Pat’s moneyline or did I read that wrong?

E.V.: No. So what that’s saying is you’re gonna get… So I wrote an article about the anomaly that the books like to shade their moneylines just based on knowing that the receivable is gonna one of the most publicly-bet games. And knowing that instead of taking Falcon’s +3, what most people will do is take Falcon’s plus the moneyline. You know my research has shown that about 9% more people… So say that 50%…40% of people are gonna bet on the Falcons +3 points then that would mean about 50% of people are gonna bet on the Falcons plus the moneyline.

So you’re gonna see an overexposure to that moneyline that the books will generally try to compensate for by shading those moneylines lower for the Falcons. And getting less [inaudible 00:55:47] for the Flacons and getting a discount for the favor or for the Patriots. So it wasn’t an article saying that you should bet on the Patriots or you should bet on the Flacons. The play I was trying to convey was that if you want to bet on the Patriots, you should consider taking the moneyline because you’re gonna get a discounted moneyline price, if that makes sense.

Meb: Interesting. Okay. Well, a couple of other quick ones. Coin toss, you want heads or tails? As a quant I wanna say?

E.V.: You tell me.

Meb: I feel that there’s a lot of fun…

E.V.: You figured out… No.

Meb: Yeah, there’s a lot of fun with [inaudible 00:56:29].

E.V.: What’s that?

Meb: I’m gonna just read you a couple because there’s the classic, “How long is it gonna take to sing the national anthem?” And the average historically is around 2 minutes but the line I’ve seen online is over 2 minutes and 15 seconds. So maybe Luke Bryan is a long-winded singer, I don’t know. But there’s some of the real funny ones. And I can’t imagine any of these next three would be under. So like there’s one that says how many times will Gronk or Gronkowski be said on TV during the live broadcast? And the over under is only three. Doesn’t that seem like that would be a really low over under? I mean I feel like they pan to him almost every time the Pats have the ball. Do you think that that’s gonna go over or is that something that I’m just crazy about?

E.V.: It depends on where he’s placed in the stadium, right? I hadn’t looked into it but I think we saw a lot of him in the AFC Champions Game because he was in the press box with the owner Bob Kraft, and so they could pan to him a lot. But depending on where his placement is in the Super Bowl, you know, they may or may not pan to him too much and depending on how much you can view. So, you know, that would be what I’ll try to look for if I’ll try to evaluate that bet but.. You know, with this process…

Meb: We also have how many times will Gisele be shown on TV and the over under is only one and a half. I feel both of those are really undervalued. I think it’s gonna way over.

E.V.: See, the thing that I think you have to think about is there’s a lot of things that they’re gonna show during the Super Bowl, right? They’re gonna have to show Gisele once, they’re gonna have to show Gronk a couple of times. But there’s only so much time in the Super Bowl because then you have all these commercials you have to show. You have to show, obviously, the game itself. So, yeah, it’s interesting how they set these lines and, you know, if I had a data set, I would try to figure it out. But barring that, it’s just…

Meb: The Gronk days…

E.V.: …correlation.

Meb: …is a limited amount of games. Although you could probably go back to every game he’s been heard in and say how many times have they said the word “Gronk?” that seems like a good orb and it seems to me like it would over. They even have a line that you can bet that says, “Who will Donald Trump pick to win the game?” And he’s, obviously, friendly with Brady and so it’s actually Pats is 1 to 10 and Falcons is 11 to 2. But he’s so unpredictable. I feel like that’s almost a good bet just to take him randomly picking the Falcons. I don’t know.

You also had a good article going back to this kind of bet sizing, talking about the Super Bowl. So this ties in a little about just money management and investing. And, you know, this is on my mind because I watched the Buffet documentary. And we had actually written an article called something like “Buffet or Berkshire, which Would You Rather Invest in?” And so you have a very recent article that just came out called “Belichick or Buffet, Who Would You Rather Invest in?” Could you talk about that article a little bit?

E.V.: Yeah, it was just a fun concept. You know, when I was researching how well the Patriots had done since Belichick took over, I mean it’s astounding. He’s like 75% win percentage straight up. And when you think about the NFL and how much parity they try to induce with free agency, the short careers that these players have, the turnover on these rosters, you know, it’s really amazing that just… It’s really an amazing job he’s done in managing that team and keeping them afloat even when Tom Brady got hurt. I mean they went 11 and 5 when Matt Cassel was quarterback. So this guy has done it with a different cast of characters. And it’s hard to say that it’s anything but Belichick dominating not only NFL but also the betting market. He is 59% against the spread around in 17 seasons. So he’s…

Meb: Has that varied? Has that stayed pretty consistent or…? I guess you said they were like 14 and 2 this year?

E.V.: I mean it definitely varies from season to season. Like I said, this season, he’s been something like 14 and 3 against the spread which is incredible…incredibly profitable but he just bet on the Patriots every week. And so what I said was, “What if you just bet on the Patriots every week since 2000 when Belichick became head coach of the Patriots?” And I took that and I basically looked at that against Berkshire Hathaway A shares and said, “What would your return be based on betting on Belichick every week versus betting on…or versus being fully invested in Warren Buffet, with $100,000.” And basically, the conclusion was that, you know, Buffet I think would have turned your money $100,000 into something like $430,000 while Belichick would have turned it into something like $375,000. So not a difference but some caveats are that with Belichick, you know, the NFL season like you pointed out, it’s only 17 to 21 weeks a season. So two-thirds of the year you’re gonna have 100% dry powder.

Meb: Yeah. So I bet if you included the money sitting in T-bills, that actually would outperform by quite a bit.

E.V.: That’s right, exactly. You’re taking that dry powder and investing in, you know, safe houses like T-bills, or a managed feature against an account, or anything else, other strategy, you have that ability with this Belichick strategy so. I was just gonna say another interesting point is the max drawdown, obviously, all stocks were hit hard and the great recession. Berkshire was no different, you had to drawdown of around 50%. The max drawdown, you’re gonna see with proportion to Kelly sizing was around 27%.

In a run, that was [inaudible 01:02:35] actually the Patriots undefeated season where market expectations caught up to them after they won eight straight if you remember it, the Patriots were undefeated in 2007. After that, the market said, “We’re gonna start putting a really high spread on the Patriots every week.” And they subsequently under-performed for quite a while. But the max drawdown with this Belichick strategy was only 27% versus 50% by investing in Buffet. So it’s just a fun study. I don’t think many people have the financial discipline to leave $100,000 with Buffet for 17 years or bet on the Patriots every week. But it was just something that I wanted to look at.

Meb: All right. So we’re not gonna launch the Belichick ETF. We would have some sort of deflate ticker. What would DFL be…? I don’t know.

E.V.: Yeah.

Meb: Sorry for all my Pats fans. All right. So we gotta start winding this down. We’re running out of time. So for all of the aspiring, young quants, sports betters out there, talk to me a little bit about resources. So if someone is interested, obviously, what are some of the best, if you have, any favorite books, and then websites, and then lastly, like software or databases?

E.V.: Yeah. So for books, I would say just looking at for money management I think “Fortune’s Formula” which talks about, you know, Ed Thorp, Claude Shannon, how they derived sort of the Kelly Criterion, what came to be. Then for sort of domain-specific knowledge, I think that there are, you know, pretty easily accessible resources out there for different sports.

So for the NFL, I think that this book written in the late ’80s called “The Hidden Game Football,” has a lot of concepts that still aren’t implemented today in the NFL. Like when you should go for [inaudible 01:04:30] fourth down. The value of getting the ball on the 20-yard line versus the 25-yard line and quantifying that. That book really goes into detail on that.

For basketball, I think the Dean Oliver’s “Basketball on Paper,” has a lot of, sort of, quantitative metrics that are still used today in terms of the four factors. A lot of it has been advanced since then but I think those books are great starting points for anyone looking to get into it.

In terms of software, I think there’s a cool app out there called Onside Sports where it has different lines. You can put in bets as, you know, basically a dummy account and then you can see how much you had won or loss. And they’ll calculate that for you to see how well your picks would do. So I think that’s a good resource in terms of software that’s an app for your phone.

And then, you know, in terms of the process that I use myself, it’s no different than I used at my past financial job. We used databases. You know, we have a large backend in terms of debt pipelines that we pay for sports data, play-by-play data, pitch-by-pitch data, things of that nature. And then you know?

Meb: Is that something that’s publicly accessible or is it something that like, you know, people…or kind of like the Chris database? They’re gonna be putting…plopping down 10, 20 grand? Or is it all customized software and simulation for you guys, or is there a kind of the off-the-shelf stuff?

E.V.: So the predicting software is custom but the data itself, the feeds are, you know, they’re payday PIs. There’s a lot of different service providers for these different sports, for the different types of sports data you can get. And there’s different levels for different sports and so… It’s no different than if you were gonna get a Bloomberg feed. You know, they have financial data, we have sports data that we download and then use that to create our model.

Meb: Well, Bloomberg is not cheap either. I think we still pay like 25 grand. Somebody needs to disrupt that. Last question, any great sports betting podcast or Twitter handles we should be following?

E.V.: Yeah. I think you know, a sports betting podcast, it’s a fun one that I go on a few times. It’s called “Beating the Book with Gill Alexander.” He’s a guy that I used to work with and he’s done a great job of getting guys. He’s had you know Jeff Ma, the guy from MIT Blackjack Team on this show talking about sports gambling. You know, looking at ways to handicap the games. You know, I think that’s a great one to start off with. And then, obviously, there are sort of mainstream ones that you’re gonna see from like ESPN. They’re gonna have a lot of sports being podcast, obviously, that cater towards that specific demographic.

Meb: E.V., we always ask people if they have something beautiful, useful, or magical at the end of our podcast, you got anything for us?

E.V.: Yeah. One thing that I really find beautiful, useful, and magical is this extension on Chrome called Ebates. I’m not sure if you’re familiar with it. But essentially, the way it works is they are an affiliate marketer but they split the fee with you. So if you go and buy something on Amazon and they get a 3% fee then they will send you back something like one and a half percent. And the reason that this really works well with Chrome extension is because you’ll go to websites that you don’t even think have a rebate and you’ll see you’ll get 10% cash back. And then they just either write you a check or they’ll PayPal you the money. So for someone who does a lot of their shopping online like myself, it really comes in handy, more than you’d think so.

Meb: What ‘s the name of it again?

E.V.: It’s called Ebates like rebates without an R.

Meb: That’s one of these fascinatingly-obvious business plans and I’ve always thought and I never understood why this hasn’t taken hold. If so many of the social networks/websites… So like even Google, or Facebook, or you know, I mean YouTube does this a little bit for their creators. But the people who participate, the people that are involved that they don’t compensate them. So I’ve always wonder why, say like you couldn’t build a competitor to Google. And say, “You know what, we’re actually gonna give you quarter of your search revenue. So when you search for something, you click something, we’ll give you a quarter of it.” But the people that are involved and even more so for the content creators, the same thing for Facebook. Why would you not go to social networks says, “You know what, we’re gonna return a quarter, or a half, or whatever the revenue is to the people involved.”

We even wrote about this for content creators for one of our old Million-Dollar ideas in Fintech called “TheStreet.com 2.0.” for a lot of these websites that aggregate content. But a lot of the content creators, and writers, and bloggers don’t participate. So that’s a great idea. You just sparked a little bit of a weekend project presumably.

E.V.: Like you said, it can be applied to a lot of different industries. I think online shopping is a fairly obvious one that’s easy to implement. But even talking about trading or a lot of different things that have high frequency where someone is getting a commission and you could give some back some of that to customers. I think there’s a lot of potential there with that idea that you mentioned, yeah.

Meb: A very cool idea. Thanks so much for joining us today. It’s been a lot of fun. I imagine we’re gonna get a great response when we have to have you back on every once and a while. Where can people follow you if they want more information on your articles and writing?

E.V.: I think you mentioned my Twitter handle is @EVBetter. I’m posting all my writing at doctorbobsports.com. Just let me know if you guys want me to look at anything in particular and, you know, write about anything interesting. I’m always open to new ideas so.

Meb: Great. I have a lot. One of my buddies favorite, we’ll call him anonymously Chris, that’s actually his real name but he loves betting. I think he’s at Oakland Games when there’s a big storm coming in. Because I think it’s like under sea level or something and the field always gets swamped. So weather is his big favorite. We’ll talk about weather next time we have you on.

E.V. Better, thanks so much. Everyone, thanks for taking the time to listen today. We always welcome feedback and questions through the mailbag at feedback@themebfabershow.com. As a reminder, you can always find the show notes in other episodes at mebfaber.com/podcast. You can subscribe to the show on iTunes, my favorite app is Castro and if you’re enjoying the podcast, hey, leave us a review. We actually read all of them and thank you. Thanks for listening, friends, and good investing.

Sponsor: Today’s podcast is sponsored by The Idea Farm. Do you want the same investing edge as the pros? The Idea Farm gives small investors the same market research usually reserved for only the world’s largest institutions, funds, and money managers. These are reports from some of the most respected research shops in investing. Many of them cost thousands and are only available to institutions or investment professionals but now they’re yours with The Idea Farm subscription. Are you ready for an investing edge? Visit theideafarm.com to learn more.

Episode #37: John Bollinger, Bollinger Capital Management “People Have This Time-Frame Confusion That I Think Does A Huge Amount Of Damage”

Episode #37: John Bollinger, Bollinger Capital Management “People Have This Time-Frame Confusion That I Think Does A Huge Amount Of Damage” fd

 

Guest: John Bollinger is the president and founder of Bollinger Capital Management. An avid researcher, he has developed a number of widely used investment tools and analytical techniques. His Bollinger Bands® and related tools have been integrated into most of the analytical software and charting platforms currently in use.

Date Recorded: 1/26/16     |     Run-Time: 1:08:04


Summary: As John is also a market historian, Meb start by asking him about his historical influences – those individuals who helped shape John’s perspectives on the markets and trading. John gives us his thoughts, identifying who he believes is one of the most important figures in technical analysis. This leads to an often-forgotten takeaway – that many of the most effective market concepts have been around for a long time. Some very profitable strategies that still work today were being explored 100 years ago.

Meb redirects, asking John about his background. It turns out, John was in the film business as a cameraman. But by a few twists of fate, he ended up in front of the camera, providing technical commentary on markets for a fledgling financial broadcast network.

This leads into a discussion of John’s famous “Bollinger Bands.” He gives us an overview of the tool, and how he came to establish it. In essence, Bollinger Bands can help investors identify relative market bottoms and tops, helping find direction for profitable trades.

Meb then asks if John’s thinking on Bollinger Bands have changed since the early days. John tells us that the core concept stands the test of time, though he has added some extra indicators.

Next, Meb asks about combining two types of analysis – technical and fundamental – something John calls “rational analysis.” For many people, you fall into one camp or the other. But John was able to find overlap between them. He tells us how, and even ropes in two additional types of analysis to include – quantitative and behavioral. He thinks combing all four works better than using any single one. Meb asks how you actually use them all together, to which John gives us his thoughts.

Meb then asks which sector John is currently identifying as a good source of potential trading profits – but he immediately discounts the validity of his own question. You’ll want to hear why. This leads into a great takeaway – using the right charts for entry/exit in a trade. Specifically, a trader may use a short-term chart to initiate a position, but then not move to a medium-term chart to help him navigate how long to hold the position. Instead, he keeps looking at the short-term chart, which obviously will oscillate, and potentially scare the investor out of the trade. John says “People have this time frame confusion that I think does a huge amount of damage.”

Meb then asks about trade management. John says the most neglected issue is position sizing. People need to know how much capital to commit to their strategy, and there is a mathematical “optimal” answer. In essence, the problem is “betting too large.”

This leads John to reference the trading concept of “regret” – the percentage of time you’re in a drawdown. Turns out it’s about 80% or 90% of the time you’re invested. The only times you’re not in a drawdown are when you’re setting new highs, and that’s pretty rare. But most investors hate drawdowns and just don’t do well with this reality (part of the reason why investing is so hard for most of us).

There’s far more in the episode, including the most influential books John has read, Bitcoin, currencies, how to trade volatility, and John’s most memorable trades (good and bad). What were they? Find out in Episode 37.


Episode Sponsor: Global Financial Data


Comments or suggestions? Email us Feedback@TheMebFaberShow.com

Links from the Episode:

BollingerBands.com

Bollinger on Bollinger Bands

Wyckoff Books

aka Rollo Tape

Twitter BBands

Be a Good Loser

SystemView

Marty Zweig Books

The Rise and Fall of Silk Road

DIYAudio

 

Transcript of Episode 37:

Welcome Message: Welcome to the Meb Faber Show, where the focus is on helping you grow and preserve your wealth. Join us, as we discuss the craft of investing, and uncover new and profitable ideas, all to help you grow wealthier and wiser. Better investing starts here.

Disclaimers: Meb Faber is the co-founder and Chief Investment Officer at Cambria Investment Management. Due to industry regulations, he will not discuss any of Cambria’s funds on this podcast. All opinions expressed by podcast participants are solely their own opinions, and do not reflect the opinion of Cambria Investment Management or its affiliates. For more information, visit cambriainvestments.com.

Sponsor: Today’s podcast is sponsored by Global Financial Data. We’ve been using data series from GFT for almost 10 years, ever since I wrote my first white paper. The data has been vital on research scenarios such as CAPE ratio calculations and historical simulations. For almost 20 years now, Global Financial Data has been aggregating and transcribing data from original sources with mini sources no other data providers have published before. Please have a look at their website at globalfinancialdata.com, for more info and to set up a trial account. If you mention that I sent you, they’re offering a 20% discount on all new business subscriptions. Again, that’s globalfinancialdata.com.

Meb: Hey, everybody. We are coming back after a two-week podcast vacation. I’ve been doing a lot of traveling, but super excited today to be welcoming local friend and long-time market historian and trader, John Bollinger. Welcome to the show.

John: Thanks for having me, Meb.

Meb: Despite the fact that we both live in the same town in Manhattan Beach, you and I both fairly often are traveling. You do quite a bit of an international. Where have you been lately? You’ve been home for the holidays in New Year? You’ve been on the road?

John: I have been home for the holidays. Last year, I don’t know, China, Japan, Europe a couple of times. There’s a lot of interested in my work, so people are very anxious to meet me and, you know, get the word so to speak.

Meb: Historically, that’s been a lot in Asia too, right? I mean in Japan and in China, both?

John: Actually, yeah Asia, there’s tremendous interest not only in Bollinger Bands and the related tools such like that. But in technical analysis in general, Japan has a very long and deep history in technical analysis. And in China where, you know, things aren’t as clear as they might be because of government ownership of securities, and such like that. Government control of the markets, you often can’t see the traditional fundamental values at work. A technical analysis has assumed a sort of primacy amongst investors.

Meb: And I was gonna ask this later in the chat, but since it’s come up already, you know, I’ve known you for a long time, and one of the things that’s always impressed me is that you have a deep interest in, not just research history, but market history in writers. You look like you read a lot of these academic studies, and they’ll talk about, you know, momentum in reference of all the studies in the ’90s. But I’ve been talking to you for years and you all talk about, you know, looking back to one of the true sort of market historians. Who have been the biggest influences on how you think about markets, and looking back on kind of the ways that you’ve developed as both a researcher and money manager in general?

John: I think a guy who was at the peak of his career, a century ago, by the name of Richard D. Wyckoff. Probably the most important person, I think, in the history of technical analysis, not just in terms of his impact on me. He developed many of the concepts that we think about today in terms of implementing modern technical analysis, even in terms of quantitative analysis, this idea of trying to identify supply and demand, trying to identify what sort of actors they are in the markets and what their conflicting motives are.

You know, he was thinking about these things at the turn of last century, started chalking, you know, prices up on the board, as you might imagine. But really got into the analytics of it, and eventually founded a school called the Stock Market Institute, and edited a magazine for a long time, the Wall Street Analyst. But he was just such a deep thinker that the concepts that he put forward a century ago are still relevant today, and that’s often what you get from studying the history of technical analysis. He finds guys who just saw things so clearly, and so profoundly that even though the times have changed, and the markets have changed, dozens of other things have changed the basic concepts are still viable.

Meb: So, for someone who’s interested in Wyckoff’s work, do I remember…did he write some books or there are books about him that you would you recommend? What’s a good starting point there?

John: He wrote one book under a pseudonym. The pseudonym was Rollo Tape. Following the tape back in those days was a big thing, and he wrote three or four more books under his own name. But if you can get copies of his magazines, and they’re still around in libraries here and there, it’s not that hard to find. Many of them are microwaved, micro-filmed, I’m sorry.

Meb: Probably microwave as well.

John: Yeah. So, you know, that materials available. Those are fascinating. He wrote in-depth articles, you know, as he was developing his concepts again, you can see how he would work through ideas about how the markets work and such like that. And that’s exactly the same thing that we do today, obviously, we have different markets but the process, the analytical process was the same.

Meb: You know, it’s funny because we often talk about a similar thing on this podcast which is, you know, a lot of people talk about value. And we say, “Look that Ben Graham was talking about that 100 years ago as well,” and talking about trend with Charles Dow, and a lot of these guys that at least. We’re talking about this thing, it’s nothing particularly that, you know, a lot of these audience is younger, don’t’ actually know that a lot of the concepts have been around for a really long time, and we link it to the Wyckoff magazine and books in the show notes we published. Is there anyone else off top your head that has been a big influence, you know, over the years in your thinking?

John: Well, you just mentioned another one, Charles Dow. He was the grandfather of trend following. He developed the ideas about trend following 120 years ago or so. You know, he’s the editor of Barron’s, which was another paper that he owned at that time. Hamilton, William Peter Hamilton took those ideas and codified them, you know, in a long series of editorials that basically the foundations of trend following investing as it exists today.

Meb: You know, it is funny because we had taken a look back and said, Dow Theory, there’s a lot of ways to interpret it but at the simplest kind of is a market going up? And he was looking at the industrials and transports, I believe. We would say even something if you simply just laid overlay the moving average on each, and so when they’re on agreement, they actually had the best performance. You know, when it was mixed, not as good, and they were both in down trends it’s the worst. It’s held up so well out of sample over a hundred years later.

John: Exactly. In 1930 or so, Robert Rhea who was the person who kind of codified all of Dow’s and Hamilton’s work. He suggested using the simple 5% filter, just take, you know, the prior highs anytime you fall 5% from them, you mark that average as being in the down trend. You keep track of three or four or five averages and, you know, when they’re all in up trends the market is doing well. When they’re mixed the market is going sideways. When they’re all in down trends, well, you know, what’s happening then too.

Meb: Yeah, you know, it’s funny. Keep it simple. Before we start balancing around a little bit more, you know, looking back in history let’s take a look at Bollinger’s history. You know, you were originally born in Vermont, right?

John: I am.

Meb: And didn’t start out in LA as a trader in market historian, right? Do I remember correctly?

John: That’s, you remembered exactly correctly. I was in the film business as cameraman. I went to the school of Visual Arts in New York, and went to apprentice to a cinematographer which is something I would do again later in the markets. Apprentice to a very fine cinematographer guy by the name of David Coyt, some people will know that name, sort of a cinematographer, cinematographer. I’ve spent the first 10 years in my career in the film business which what moved me from New York to LA., the sorts of films and the sort of work that I wanted to do that was more of it here than there was in New York, so that moved me out here. But all along I’d had interest in markets and my mom was getting ready to retire, she ran a small advertising agency. And she asked me, she knew I was interested in stock market stuff like that, she asked me to look after investments. And I quickly learned how hard that was, and started focusing on ways that I might do that better, started learning about technical analysis and such, and gradually transition from film to the markets by the time I was about 30.

Meb: And, you know, if I remember correctly you started spending a little time on not working the camera but in front of the camera, the predecessor to CNBC. What was that called?

John: It was the Financial News Network. It’s actually a funny story. There was a guy on the radio here in LA. By the name of Ed Hart. And in five minutes in the morning he could tell you everything you needed to know for the day about the markets, what to look at, what stocks to follow, what areas were hot, what areas were not. He was just really incredible. The Financial News Network, it just started up. It was the first cable network that was ever devoted to the stock market.

And they asked him to come down and work with them. And they had asked me about six months prior and I was very happy doing what I was doing. I was trading options at the time. I turned them down. But when I heard Ed Hart had gone to work for them, I said, “Well, it’s good enough for Ed it’s good enough for me.” So, I went down and asked the guy if the job was still open and it still was, they were interested in somebody who could provide some technical content on-air. And they had actually some very sophisticated computer systems that they had built up to analyze the markets.

The chairman of the board, a guy by the name of Earl Brian had written a master’s thesis on technical analysis and implemented it on mainframe computers. So, there was a liking of technical analysis at the network that came from the top down. So, it was very easy for me to integrate in and I started behind the scenes providing material for other people. And then oddly enough one day they were short of a person and a guy came in and said, “You go out there.” At that time, I was terrible. I had terrible stage fright, stuttering.

Meb: Could you find some old tapes with this? Were they archived somewhere?

John: Oh, yeah, yeah. There’s ton even embarrassing material around. But, you know, they liked the content that I provided if they didn’t like my delivery, and they put up with me long enough for me to make the transition to be fairly smooth provider.

Meb: It takes practice and so, would this have been around the same time or would it preceded or been in parallel with, when you really started developing Bollinger Bands? Because I know it’s been about 30 years, right?

John: Actually, it’s coming up on 34.

Meb: Oh, man. But it was around the same time as it to you?

John: Actually, I had just developed Bollinger Bands when I went to the Financial News Network, and probably in the prior six to eight months. I went in ’84 and I did the final touches of Bollinger Bands as they are today, probably 1983. I started on them on 1982. You have to remember, this was in the era before there were PCs. So, we had little, we called them micro-computers but they’re just basically the predecessor of the PC. You had to piece them together with cards, you buy memory cards and stuff like that, put them together. But I put one of those together and I had an early spreadsheet program called Super Cal. I’m sure somebody in the audience will remember that. It was for the old CPM operating system.

I was trading options at that time, and in order to trade options the one thing you have to have is an estimate of volatility. So, one day I copied the formula for volatility down a column in the spreadsheet, and I saw that it was changing over the time. And, you know, that doesn’t sound very interesting now but in 1982 we believed volatility was a static quantity. It was like a property, like the walls as white as the cars blue. You know, IBM’s beta is 1.2 that sort of thing.

And just about then that Robert Engle was doing his work with GE. He eventually get the Nobel Prize for his work on the fact that volatility was volatile. So, it was in the air that sort of idea and I had a trading system that I was using that used fixed parameters. And you constantly having to readjust them, it was a nightmare. And every time you readjust them you’d led motions into the marketplace or you’re bullish you adjust them to look bullish. If you bearish, you adjust them so it looks bearish. I was looking for some way to automate that process and seeing volatility changes that maybe I can use volatility. That was the genesis of Bollinger Bands.

Meb: So, the quick definition of what they are for people if there’s someone who’s been in a closet that’s listening to this podcast. What’s the quick definition of Bollinger Bands and the quick overview kind of in your opinion from the creator, the best way to use them?

John: So, Bollinger Bands are just a type of trading bands. All trading bands are more or less the same in their concept. They provide a relative definition of what is high and low. If you’re near the upper band, prices are relatively high, if you’re near the lower band, prices are relatively low. Bollinger Bands are sort of trading that is driven by volatility that was my contribution to the process. So, they’re automated, you don’t have to adjust them, you don’t have to change them, you don’t have to maintain them as the market regime changes the Bollinger Bands change, they tighten, they expand. They’re driven by a middle band. There are three lines, upper, middle and lower. So, the middle band is moving average, so if stocks are trending up the bands are rising. If stocks are trending down the bands are falling.

They provide that key definition whether the prices are relatively high or relatively low, and you can use that to assemble all sorts of trading approaches. You use them in pattern recognition to try to rigorously define W-bottoms or M type tops. You can use them to, you know, identify oversold and overbought opportunities. You can use them in trend following methods. Or, you know, in congestion range markets you can use them as buy and sell levels to reverse to the other side of the range.

Meb: One of the beauties of publishing like you have for so long, you also have to be one of the longest continual newsletter writers, right? You’re a capital grower, rather. When did you start that? In the ’80s as well?

John: Actually, it started in ’87, not an auspicious year.

Meb: Well, it depends, you may have started November or earlier in the year, but so you’ve been writing for a long time and one of the beauties of writing and John also does a lot of speeches around the world and videos, many videos that are probably people have seen in DVDs, a bunch of websites, Bollinger Bands and a whole book on the topic “Bollinger on Bollinger Bands”. But one of the cool things about publishing is other people taking your work and kind of running with it. What have you seen as kind of innovative or interesting ways that people have kind of built upon and used in ways you might not even considered over the years? Have you incorporated any of those methods?

John: So, I was like one of the original open source guys. When I developed the bands, I immediately put them out in the public domain and allowed other people share the formulation with them, and allowed other people to use them to incorporate them into their software and into their platforms. And the benefit of that is astonishing because over the years people will come to you and they’ll say, “Look, I’ve taken your work and I’ve done these fantastic things with it.”

I remember the first time that it really occurred to me what a treasure trove this sort of additional information was in Hong Kong, many, many years ago. A Chinese guy who was running some active trading approaches inside a hedge fund was using Bollinger Bands on the equity curves of the different approaches to allocate funds between the approaches. If the equity curve was trending up towards the upper Bollinger Band he would take money away from it and put money into a system that was trending down toward the lower Bollinger Band. So, he used it to allocate funds within a fund. It was just amazing.

Meb: Which is funny because it’s the exact opposite what we’ve seen in the literature of what most individuals and institutions wanted to, which is put money into the funds that are doing well and take money out of the performance chase.

John: Well, you know, Humphrey Neill the founder of contrary in opinion said you should do the opposite. And I found out in my career more often than not that he was correct.

Meb: Have you been working with these for 30 years, any general ways that your thinking is changed on using them in general? Are there any major takeaways that you use now that you wouldn’t have maybe 30 years ago?

John: Well, the first thing is that the bands themselves haven’t changed. They withstood the test of time. The basic idea turned out to be a first principle sort of idea, a robust idea that’s as useable today as it was when I developed them. I’ve added some extra indicators over the years that are related to them but other than that they haven’t changed very much.

In terms of my approach to using them the very first system that I built to use the Band, or actually the system existed before the Bands, the very first system I modified to use the Bands I still use today. So, some things have stood the test of time. Some things haven’t stood the test of time because market dynamics have changed a lot. I think years ago, it was a much simpler proposition, especially when trading individual stocks to simply try to sell the upper Band and try to buy the lower Band. The sort of success rate of that was much higher years ago. I think you need to be more sophisticated, you have to bring a little bit more to the party these days. You have to add, you know, some supply and demand information or some market trend information or some group and sector information. You have to add a little a bit more if you want to be as…

Meb: That is a perfect lead in to kind of the next topic that I would like to talk about. And, you know, so many investors in our world are severely what I like to called siloed, you know, they say, “Look, I’m dividend guy” or “I’m a pure trend fall.” And, you know, that’s fine. I think there is many approaches in the markets that work and, you know, people find the one that they’re attracted to God bless them.

But one of the things you’re known for is investing concept that is probably considered to be accepted today, but may not have been necessarily at the time which is kind of combining this juncture overlapped between technical analysis, which is the study of price trends, supply and demand, but also fundamental analysis, which you called rational analysis, which makes so much sense. Maybe you could talk a little bit about that? How did you arrive at putting those? By the way, John has to be one of the first CFA CMTs, there can’t be too many all around, right?

John: No. There’s actually a lot of us now, but I am the first.

Meb: First ever?

John: The first ever by simple default. When they gave the first CMT exam that’s Chartered Market Technician I was the only CFA that took it.

Meb: That’s funny. That’s awesome. That’s really cool piece of trivia. I didn’t know that. So, there got to be more analogies because there are so many CFAs. But for a lot of people it’s kind of like holding two very different beliefs in their head, you know, and so the prospect of using fundamentals and technical, it’s a little more accepted now. But how do you come around to that way of thinking? And maybe we talk a little bit it about how you possibly used the two of those together in investing approaches?

John: Well. First it doesn’t have to lead to cognitive dissonance. These things can be complimentary they don’t have to fight with one another. You know, I started the way that most people do, taking brokerage research and trying to make money out of that, stock tips from, you know, brokerage houses stuff like that, obviously that doesn’t work. It didn’t work then it doesn’t work now, ta, ta, ta. And then I shifted to technical analysis. But I was always impressed by…back in the day stock quotes are very hard to come by. It was very expensive. If you wanted quotes in your home, you got this thing that was a size of a refrigerator, had to have plumbing, you know, to keep it cool, it was crazy.

So most people who are involved in the markets would go to brokerage firm and brokerage firms would give Active Trader’s Desks, just given to you. You know, and obviously you had to generate commissions too to get one. The idea was that the firm that gave me a desk was a firm that no longer exists called A.G. Becker, and they had really terrific research, I mean really terrific research, both fundamental research and technical research, which was very unusual for a firm in those days.

And I would look at it and I would just go, you know, all of this is pretty good, and if you put the pieces together it’s even better. They had a woman there by the name of Elaine Garzarelli, who did a great group and sector product. They had a guy by the name of Roy Bloomberg who did a great technical analysis in options product and had a number of great fundamental analysts. So, if you could put all those parts in pieces together you could actually gain an edge so that’s the juncture of that idea.

Today, you know, it’s not just technical analysis and fundamental analysis today we’ve got four parts to the puzzle, right? There’s quantitative analysis, behavioral finance, technical analysis and fundamental analysis. So, you’d steal from all those different disciplines take little pieces that work and combine them into an approach that works better than any single one of those approaches individually.

Meb: And so, how do you do your process? How do you decide from which tool you had to draw? How do you put it all together? Do you have a systematic way about it or what’s kind of the combination? How do you go about it?

John: So, the thing that we know that I like the most or the things that I like the most are group and sector analysis. I think this is very powerful concept. Most people regard that as some form of fundamental analysis. I don’t actually know how it should be labeled. But I combine that with technicals, with momentum and such. I’m very interested in growth. I think there are times when the market value’s growth very highly, there are times when the market discounts growth. So that rotation between styles, between growth and value, between large cap and small cap that’s a very big piece of my process. Today, that would be called quantitative analysis, back in the day it’s called technical analysis.

There’s an interesting idea there is that, you know, these pieces have been shuffled around over the years, different groups have claimed different pieces. Much of what we know is behavioral finance today came from Kahneman and Tversky from their pioneering work, but a lot of it came from the work of a guy by the name of Humphrey Neill, who is another Vermonter, right? They called him the Vermont Ruminator and he developed this whole idea of contrary opinion that the crowd could be wrong, that people would go to excess.

And, you know, there were times when you should be in tuned with the crowd and follow the trends and there were times when you absolutely should not, and you should go the other way. So, you know, the history of people making, you know, efforts in analysis in this market is lived with people combined these ideas. It’s nothing that I come up with it’s an idea, you know, that has tremendous steps in terms of history.

Meb: Yeah, I mean it’s a scenario we often talk about that my favorite type of investment is, if you distill it down to the two simplest would be something that’s cheap in entering an uptrend. If I had to pick one thing and it’s interesting because that’s not the way the world has looked on kind of a country or sector level for a while, but it seems to have been changing in the past few months for a lot of what you would assume would be cheaper sectors, industries, countries have really started having great performances over the past six months. But for the prior years, I mean the U.S. has been the number one stock performer since the bottom of the crisis, and the cheap stuff has just gotten cheaper but that’s what creates opportunity. Were you kind of seeing opportunity now and the groups and sectors, is it…?

John: Just to hook back into that for a second, there’s this guy by the name of Bukowski. You know, he devoted the best part of a book to exploring exactly those kinds of ideas. I think they’re really fantastic ideas.

Meb: What’s the book? Do you know?

John: What works on Wall Street.

Meb: We’ll get back to books in a little bit. I don’t know if you can share this or not but is there anywhere like in kind of your research you’re seeing opportunity now? Any groups, any sectors off top of your head?

John: Well, in the short to intermediate term…

Meb: By the way, sorry. That’s a terrible question to ask and one of the worst things about TV is, you know, there is no timeframe and you actually had a good quote not to interrupt you, in one of your pieces talking about timeframe confusion. Where people will look at a short-term chart but will be trading on a longer-term time rising or be trading on a longer time rising but only looking at short-term charts.

John: So that comes from a whole idea I did about task analysis, right? There are certain things that we need to attach our analytical task to the appropriate timeframes. Long-term is our background, it’s what’s happening in the world. You know, it’s money supply growing, you know, are we in a secular economic uptrend that sort of thing. You now, intermediate term is sort of stuff we’ve been talking about. Growth versus value. What groups and sectors are doing well? What groups and sectors are doing poorly? What countries are uptrending? What countries are down trending? All that.

And short-term is really only for execution. And the classic mistake that people make is they make a decision in the intermediate term. They say, “Well, I like France and inside France I like the technology stocks.” All the parts and pieces are fitting together. So, they go to the short-term to execute and get their positions and stuff like that, tick charts and all that stuff looking quotes. And they get their positions and they don’t revert back to the intermediate term to analyze them. They just watch it go, tick, tick, tick, tick, and of course, when something’s going tick, tick, tick, tick, it goes tick, tick, tick, tick against you and you’re flushed out and you walk away. But we had no reason to be flushed out because your reasons from the intermediate term was still valid, so you should hold on to that position. So, people have this timeframe confusion that I think does a huge amount of damage.

Meb: And we see that not just with trading but also investing where so many people will come to me or having conversations with, say they have a long-term investing horizon or plan. And then will often really operate on their emotions and psychology on the timeframe of weeks and months. And, you know, that like you mentioned becomes the biggest problem on, you know, getting caught in the emotions but really losing side of the long-term.

John: The 300-pound gorilla that’s sitting in the corner is wearing a sign says discipline.

Meb: That’s Geoff by the way. For the podcast listeners, Geoff’s in the corner. Just kidding. I wish Geoff was in here right now because he loves trading options, and he would love to hear some of this. Yeah, discipline is the hardest part so along with the trading, you know, I know you’ve talked a lot historically about position sizing. And what’s your opinion on say stop losses or how to exit trades? What’s your, in general, approach to, once you put on a trade? Is it a defined exit? What’s your opinion?

John: So many parts and pieces there. First of all, for the typical person who is an active investor and or trader there is no question in my mind that the greatest thing that is neglected is position sizing. Okay, you’ve gotten an idea how much do you put to work? And you need to have a way to quantify that. You can go to Ralph Vince’s work if you want or there any number of people who have written on the topic.

I don’t think it really matters that much, which of the approaches you use, as long as you use one, as long as you have a rational idea. Because the problem is, here’s how the problem typically works out. You have a very elegant approach to the markets. It generates, say 17% year on average with a relatively small deviation. So, you need to know how much of your capital to commit to that. The problem is, is that there is in fact a mathematically optimal amount, say 7% or 10, 15 or 20, whatever it is that you should commit to that approach.

The problem is that on the down side it doesn’t matter that much, you just earn a little bit less. So, if the optimal position size is 15% and you’re 13% or 12% or 11%, you’re just gonna earn a little bit less, you’re gonna give up a little bit of your edge. The problem is on the other side, at 16% you’re gonna earn a lot less. And at 17% you’re gonna earn even more less. And that curve goes down really steeply, right? So, the problem is betting too large not betting too small. Betting too small, you give up some of the edge that you’ve developed you’re not gonna make as much money as you should. But if you’re over the peak of that curve, if you’re betting too large for your win-loss ratio, for your system dynamics the risk of ruin rises abruptly and that’s something I don’t think that people realize.

Meb: Interesting about it too is that, that’s assuming you actually can quantify the worst case scenario and a lot of times the classic trading phrase is, “Your worst draw-down is always in your future.” So, you know, for a game like Black Jack, it’s probably easy to quantify the correct betting size but investment markets it’s a little harder.

John: That’s why I said that didn’t really matter what approach you use as long as you use some approach so have an idea of where that peak is, and you can, you know, assure that you’re on this side of the peak. The safe side of the peak not the danger side of the peak.

Meb: You know, it’s hard to kind of describe this and the younger investors listening to this that haven’t had that really painful trade. You know, I learned this lesson a couple of times in my early 20’s trading, blowing up an entire account, you know, with that same thing taking way too much risk on one investment. And you learned that lesson once, you know, you feel the very real visceral pain of losing money and it colors you for forever. But you see this take place in echoes where people who haven’t had, and probably worst thing that could ever happen to a young trader is a string of unsuccessful trades.

John: That’s correct that’s absolutely correct especially if they’re their first, second, third, fourth trades.

Meb: Yeah. And that’s why I became a quantant [SP] and said, “Oh my God, I clearly, you know, have no idea how to position size or how to place these bets. And so it’s something that, you know, drove me into quantitative analysis because of the too much risk. But we see it all the time, I mean I even had a young lady from Australia emailed me today and she says, “Hey man, you know, I’m investing that and the other, but I just really hate draw-downs.” And I said, “Well, look you should probably be happily sitting CDs and just move on.” You know, you should be in very short-term bonds and just be happy with it or, you know, maybe half in cash. But the worst case scenario for that type of person is taking on too much risk and for the younger generation who for right now, for the past eight years has never seen a bear mark in the U.S., you know, the expectations started to get out the line. So, we always tell people to try to air on the side of caution. Try to look for what would be optimal and then kind of back away a little bit.

John: So, I run a little open source project. It’s a Python, written in the Python programming language. And what it does is it takes your trading stats whether they can be long-term short-term, it doesn’t matter. And it visualizes them for you so you can see them probably has a dozen different graphing styles. And it really lets you see the dynamics of the decision that you’re making and what they look like. One of them that’s really interesting that people find totally counter-intuitive but once they’ve seen it they never forget it, this is called regret.

And this is simply the amount of time that you spent in draw-down, the percentage of the time you are in draw-down, right? And people if you intuitively ask them, “How of the time are you in regret?” They’ll say, “Maybe 10% or 15% of the time.” It’s like 80%, 90% of the time for most people. Because the number of days that you’re making new highs on your equity curve, those are the only days which you’re not in draw-down.

Meb: So, you know, we actually wrote a post on this not on trading but applied to the brought indices called something like, “To be a good investor you have to be a good loser.” It was looking, I think even at the S&P and it says there’s only two possible states, all time high or draw-down nothing in between. I may get this wrong, I’ll post it in the show notes but I think the S&P was like 60% or 70% of the time in a draw-down, right? Like you…

John: Or it’s got to be higher than that.

Meb: Yeah, all time high is a kind of rare event.

John: Because even if you make it all time high tomorrow you’re down a tick and that’s a draw-down day.

Meb: And that’s hard for people.

John: It’s very hard for people. That’s why we did System View, so that you can just take your trading stats and plug them in and it will graph them out, and you can see this stuff. You know, it’s so enlightening when first time people see it, they go, it’s like somebody turned lights on in the room.

Meb: Can this be accessed through the Bollinger Bands’ website?

John: No, it’s on GitHub.

Meb: GitHub, all right. Well, we’ll post a link if we can find it. By the way, there’s a massive amount of researches on Bollinger Bands’ website. I assume if you’re probably like me, just looking at the website I imagine the vast majority of the tools which you built on the website, which is a lot. I imagine a lot of those you built for yourself because there was nothing else out there.

John: Good. Actually we have several websites the big analytical one is the same title as my book “Bollinger on Bollinger Bands”. It’s got a short name bbands.com. But that was totally built to allow me to trade. Its sister side is a group in sector, analytical site, those two sites were 100% built to allow me to trade. And, you know, we were touching on this before when you asked me about my newsletter. I write my newsletter for myself. It’s a discipline. I don’t write it for other people. Every month I have to sit down and I have to do that, it takes me a week. And it’s when I do my deepest thinking, it’s when I do, you know, when I forced to put everything together and make it in black and white.

Meb: You’re not publishing in Wednesdays, I think, right?

John: Yeah.

Meb: Because originally it was like for a weekend delivery, do you even mail it anymore or is it just electronic?

John: No, just electronic. No more paper.

Meb: The world is changing. I mean so it is funny because the reason that I started writing on the blog years ago, similar to what you’re talking about was to try to find feedback on a couple of ideas. And very just rudimentary ideas that I couldn’t find, you know, kind of being, you know, sitting in the corner of a dark room, not having an interaction. The resources said, “Hey, look who else is thinking about this and publishing ended up?” The same sort of thing ended up having to build it on your own, but you got a lot of the feedback and that to me has been a much better resource. But the writing certainly I think is a wonderful process to try to really learn what you think.

John: You know that feedback process is so important. When I started it was very hard. No internet, obviously, or anything like that. So, it was very hard to find other people to talk to such like that especially being out here on the West Coast, away from the financial centers and such. Although, we had a vibrant financial center here in LA at that time. It’s still hard to find people and books. You know, there was a guy by the name of Nidam. He ran a company called Nidam Book Finders, and you’d call him up and you’ll say, “I want a copy of Robert Rhea’s the Dow Theory need to say fine, you know, I’ll give you a call in a couple weeks.” He call you back and he say, “Pick it up at this antique store.” You know, he don’t like sort of like buying drugs.
Meb: You know, he reminds me so I just forgot about this. Listeners are used to go over with Pastor John because there was he had archived, someone called hoarding maybe your wife would call hoarding, archived Benz Magazines for, I mean how long you have them, do you still have them?

John: No.

Meb: Why would you do with them?

John: I gave them to the MTA library.

Meb: I thought that you used it in his kindle.

John: No, no, no.

Meb: I had a number of models that I built off Nelson Freeburg’s work where data series that hit only to my knowledge only existed in Barron’s and John had many, many years, so I spent a handful of days in a storage room writing down all of the data from Johns Barrons.

John: I still keep a big database from Barron’s, each week I enter a whole bunch of numbers out of Barron’s, very useful.

Meb: And I remember Rolf Benz used to keep a good spreadsheet there. And there is a lot of ideas that I think are coming that econometric, rational analysis, time series that I think a really fascinating that there’s a handful of other people that do some similar work there too but there is an area I used so much time in “Fastback” was a great book back in the day Stock Market Logic.

John: “Fastback” was a terrific guy, I mean he was a really deep thinker and he did incredible work.

Meb: And so what would on top of writing in books and by the way you probably know this. But my first whitepaper was actually written to avoid taking the seam to level three. is the only reason I wrote it because they’re getting rid of the paper requirements that “Oh, my God I don’t want to take the test and so I actually have never written a paper before and wrote a paper and lot that’s actually gonna be 10 years anniversary I think this month. Anyway, let’s talk about books for a second because you’re a big market historian in kind of thinking, who are some other books that younger investors may not know about are books that you maybe of most gifted to people other than “Bollinger on Bollinger Bands” but some really good books that have been influential to you, any other ideas off top you end.

John: So there was a statistician at GE by the name Arthur A. Merrill and he retired at 65 as, you know, was the way in those days and he started the second careers of market technician. And he is grown so concisely and beautifully, it was astonishing so anything you can find by Arthur Merrill, you know, it’s sort of hard to find but it’s in the library since about any of his work is really terrific, just to see how his mind worked and how he thought about markets. Another, you know, sort of more contemporary guy is fund manager by the name of Martin Zweig, he had a couple of books “Winning on Wall Street” and “Winning with New IRAs. I think it was some…

Meb: Yeah, I was sitting on the shelf in my brother’s house, I remember that book.

John: Yeah, yeah. So those books are chock-full of interesting ideas.

Meb: Anything about some more we can talk about and let me know. Those are some great ones. I was gonna joking when we said, interesting thing about Los Angeles, I said, “We’re gonna…in the next couple months host to some sort of FinTech Happy Hour Meet up. So, we’ll let you know whenever that’s gonna be. And listeners if you find yourself in LA, we’ll post it publicly. So, along the books, you know, you had a lot of resources on the website. Any other outside tools, website, technical analysis, software things that you used that a thing are particularly useful or is it all just custom built coded up by JB.

John: I do some coding but really only when there’s no alternative. I like to code, you know, it’s a nice discipline, I think it’s actually good for you, makes you thinking in sort of interesting way. But I don’t think that it’s really essential anymore there such powerful tools available. If your client types like yourself are the statistical language are has built, a huge thriving community around R in Finance. And, you know, very helpful people.

Meb: People, is there like a central hub for that, is it a place you can go or is it…

John: There is a group in Chicago actually called R in Finance, they have website. That’s a great start place for that, a very friendly, very nice, very helpful…

Meb: Yeah I mean that’s a good news in those days. You can almost find any type, I mean always above my pay grade, I do, it’s little goading as possible. I think I tapped out on my coding, it was my freshman year in college. But there’s a lot of communities built around basically anything you know there’s some zero for hedge funds, value investing club for those guys, the Bogleheads, who tend to be pleasantly insane about, you know, the Vanguard Investing.

And then there’s a lot of quant finance, Quantopian is the newer one on kind of writing up the algorithm. So there is a lot that we can find out there. One of the my favorites things to do when I’m talking to people is all go grab their Twitter’s stream and you can sort them there’s a really terrible design website but it works. Only one that I know of called Fastroid and you can sword people’s tweets by the most popular. And so we to look Johns and, I mean I already would…it seems your top five all most popular tweets revolved around Bitcoin.

John: You know that’s just an accident, I’m very interested in Bitcoin, no question about that. But I happened early on when I first started on Twitter, one of the first tweets I ever saw was about Bitcoin. And there is a huge Bitcoin community on Twitter, I don’t know why? There’s another huge Bitcoin community on Reddit as well. But I just fell into them and, you know, they’re sort of kindred spirits. So, I random tweets about it.

Meb: So what this is, tell me. Is it one we ever owned or traded Bitcoin? Do you think it’s actually, you know, the same rules apply? Do you think the Bollinger Band has been worked on Bitcoin?

John: Bollinger Bands work fantastic on Bitcoin. And they work fantastic on all forex.

Meb: Yeah. As you did say, currency traders in general ones tend towards lean towards technical analysis in general but often you hear in the circles in the vernacular love using Bollinger Bands.

John: So, there is a reason for that, currency trading is pairs trading, you’re long one and short the other essentially. So, sometimes you’re, you know, you find a stock you like enough stock you hate, you pair them together and that’s a pair. Their portfolios are full of pairs trading. The ideas to earn a return at reduced volatility over time take out the market factor and just capture the sweetness of your ideas. So, forex is pairs trading and pairs have a statistical property, they’re stationary or they exhibit in the statistical parlance, stationarity. And it just turns out that Bollinger Bands in any approach like Bollinger Bands work just a little bit better with series that exhibit stationarity. So, there is sort of a built-in edge to using Bollinger Bands on anything that’s a pair.

Meb: That’s fascinating.

John: And you can create pairs, right? I mean you can, you know, you can be long IJR and short SPY, right? I mean you can create all sorts of pairs and then analyze those ratios using Bollinger Bands and you’ll find this tremendous value there.

Meb: I was listening to, have you remembered Gunlock and sometimes pairs make sense to me sometimes they don’t. I remember listening the Gunlock talk about a pair trade ones and what was it. It was like long Apple short Gold or something vice versa. And I was like, “What in the world those two things have to do with each other.” I have no idea but pairs trading is an interesting area. But Bitcoin is fascinating, I’ve been sharing, I think it’s a very interesting diversion, I never own one. I don’t trade it. But it’s very pleasant distraction.

John: So, we’re just coming up on a point where Bitcoin is really gonna get tradable, we’re gonna get the Bitcoin ETF pretty soon. And that will be, you know, that will be liquid and in and out, you know, for low commissions and low spreads and blah, blah, blah. And I’m really looking forward to that is all I can say. I think it would be great trading in long.

Meb: This is surrounded by so many interesting stories I mean the whole Silk Road story. Just hold on to it in the bio if you’ve never heard of Silk Road listeners, there is great wired story. I think it’s becoming a movie now, straight out of some, you know, a science fiction but so closes to me a marketplace we could buy and sell anything. But Bitcoin was kind of the perfect currency to do that. In the end, the founder eventually, you know, getting arrested because he was trying to put on hits on people while making tens of millions of dollars each month working from a cafe or like a library.

John: So that was the founder of Silk Road not the founder of Bitcoin.

Meb: Bitcoin have acknowledged founder now.

John: There is a founder, you know, nobody really knows who he is? But put it this way, he was a heck of a coder. I mean he supposedly a Japanese guy, I mean we’ll leave it at that.

Meb: As you said I wouldn’t be surprised, I would love to hear one day that turns out that was the CIA that developed Bitcoin as a way to trade, I mean as you said, you can’t track it but to be able to see what’s going on to show you money scenarios who knows I…

John: That makes sense to me.

Meb: Yeah. And, you know, I put it up as a subscription option on the idea form for a while and no one subscribed. Despite being, you know, in kind of a younger tech crowd in Los Angeles I’d only know many friends that use it but then I go to other countries. I mean I remember I was down in Mexico as chatting with a fellow who has a bunch of Bitcoin ATMs. You know, that was his business to put him Bitcoin ATMs.

John: Bitcoin is clearly more popular outside of the states, there’s inside the states. And you know it’s sort of understandable because if you’ve had currency problems in your life then the idea of an alternative currency gets much more appealing.

Meb: It is, you know, for someone who travels a lot until you see this, you know, we’ve seen a lot. In the U.S. most investors don’t traditionally think that much about currencies, you know, being the reserve currency but also the world’s biggest economy, most investors and individuals don’t know anything about occurrences hey it’s a great time to go skiing in Canada now, it’s a great time to go down to Mexico or vice versa when the U.S. dollars is doing poorly. But almost every conversation you have with an international investor is just littered with currency, you know, exposure or ideas and, you know, a lot of the house to do with many foreign emerging currencies, you know, can go through periods of huge volatility and draw-down’s and everything else involved.

John: Well, and, you know, we’ve had the advantage of being able to lend and borrow in our own currency because we have to reserve currency for so long, you know, most other people in the world have never experienced anything like that. So, we have a certain, you know, we perceived the dollar in a way which frankly most international investors simply cannot comprehend because they never had that. So, yeah, you’re right once you get outside of the states forex the exchange rate is a huge part of every decision.

Meb: You know, I assume you trade currency, I mean you trade pretty much everything, right, stocks, currency, is that accurate or not accurate?

John: Yeah, yeah. Pretty much. Actually, what I mostly trade is volatility.

Meb: Oh. I mean you’re getting late into the podcast for that but that is a wonderful rabbit hole to start to go down. I mean what’s your genius when you’re trading volatility expressed through options are you trading volatility funds or you, what you’re doing?

John: So, I’m really interested in all the VIX derivatives that we have now, I think they offer ,you know, really interesting opportunities. I think the thing about volatility is not so much how you trade or what you trade there is many different ways to go after that option is how I learned it but I don’t really do that anymore. The interesting thing about volatility for me is how misunderstood it is. The academic field…

Meb: Go on.

John: Well, the academic view of volatility just doesn’t, get the facts in the marketplace. And since most people are trying to trade it from the academic view that creates tremendous opportunities if you’re willing to sort of look outside the box and take an individual approach to it. So, I just think there’s tremendous opportunity in volatility today and I don’t think that’s gonna be odd way anymore. Because the academy is so attached to its view of volatility and they pounded into all the finance students, everybody comes out with those views and, you know, it’s almost sort of a universal truth and it just doesn’t fit the facts. I mean in nice theories in all that but they don’t pick the facts that we see in the marketplace.

Meb: Interesting. We have to feel like we’re gonna have you on back on like six months to really go down that rabbit hole otherwise we’ll be here three hours. Let’s start to wind down and do quick…a couple quick questions that we start to ask everyone. In these two, I didn’t ask on ahead a time so put them on the spot a little bit. Most memorable trade.

John: So, they tell a story in Chicago. There is God with a small G that runs the pits and it says he has three rules and he enforces those rules mercilessly. So, you’re allowed to buy the bottom tick once in your lifetime, you’re allowed to sell the tick once in your lifetime. Of course, you’re free to do the opposite as often as you would like. I once sold the very top tick, it was Stockholm Home Shopping Network and I shorted it at the all time high print.

Meb: So that’s good. You used to know that you’ve used up that bullet. You’ve shorting and you’re no longer…

John: So, I have one more opportunity, you know, at sometime in the next decade or so I have to find an opportunity to buy the bottom tick, I’ve never even gotten close to doing that. But it was happenstance it was not skill or anything like that, I just happened to be in the right place at the right time with the right idea and got.

Meb: Yeah. That’s funny. This is the way that it works. Do you have a memorable worst trade?

John: Yeah. I absolutely have a memorable worst trade. I was pretty active in the CMO markets, there to be collateralized mortgage obligations when that market blew up. So, that was a series of really, really awful trades. They all worked out in the end, this was before there was credit risk involved in these government securities, so it’s like absolutely there was no credit risk. So, in fact, they all worked out in the end and we were eventually made whole. But there was some really hard going for a while.

Meb: Yeah. For some reason, I don’t why this popped into my head, it reminds me of going back to your idea on losing was the concept of trading systems in designing and kind of what everyone and this has nothing to do with what you just said really. But it’s you could design a trading system that’s not particularly profitable but has a 90 some percent win rate which is to buy a security and exit on the first profitable trade. You know, and that has like a 90 if you want to great exit one to be certain but then have…

John: So your numbers all draw-down in one tiny little profit take.

Meb: The one that’s in a drawdawn it’s probably a great newsletter, you know, the usage for the little bit of sketchier ones. You could have like a 97% win rate by just never closing out the losing trade.

John: So, you know, there are people who actually do this. I mean it’s fantastic as it seems, I actually know somebody who does this.

Meb: Yeah. No, I mean look there is even many legitimate ways we’re talking about this with some friends about the, you know, even in investment side there is plenty of legitimate ways to build track records that, you know, are accurate but not necessarily ethical, right? And this goes on the newsletter or goes on everywhere but there’s, you know, as always buyer beware, again, going down a whole another rabbit hole. All right, last question we ask everyone, something beautiful, useful, somewhat magical maybe that people may or may not know about, you got something for us?

John: Well, about seven or eight years ago, I started to build a design and build tube amplifiers, it’s vacuum tube amplifiers as in the sort of stereo equipment that was popular in the 30s, 40s, 50s, and into the 60s when the transistor finally took over and solid state amps took over. So, I find these things to be absolutely magical. If you get a really well set up tube amp, vacuum tube amp, and a couple nice speakers, and a good recording, and you have yourself a time machine. You can get transported back to that moment in time, you can be there.

Meb: And so give me a little bit. So this is you listen to, this is just for listening the music.

John: Yes, just for listening the music.

Meb: What’s your go to style?

John: Oh, I listen…I’m an incredibly eclectic music listener. But I probably listen more jazz than anything else.

Meb: Yeah. I think I remember that about you. Who’s your favorite or best album, best artist? Do you have a go to?

John: I think, you know, I’m really love John Coltrane.

Meb: This is coming from someone who is, somewhat of a I just never gotten into, not gotten into never really spent the time to really explore. But I don’t know what a good starting point, I don’t know what the…

John: But I have world music too, I mean there was a new huge amount of world music. There’s a sort of music from the Rajasthan deserts in north of India, called Qawwali Music. It’s devotional music with, you know, six, seven, eight people sit down and, you know, have a couple drums and they have these beautiful little hand organs that they use. It’s just absolutely transcendent music.

Meb: Is this we come to your office where we find you blasting this in the background?

John: You won’t find it blasting in the background but you will find to play in the background.

Meb: That’s great. You know, I go through cycles on that. There’s times when I’ll be listening to music almost throughout the day, but I feel like it’s very cyclical for me. I didn’t go months without doing it. I need start plugging some in. Spotify has a pretty decent random called Discover Weekly that they look into the music and…

John: Yes or no about this.

Meb: It is pretty good, I mean I think I need to update some of my music because it gives me the same sort of stuff all the time. But I think that’s a pretty good resource.

John: I have a shorter musical cycle than you. I go in and out, you know, listening music on a much shorter term. Like I listen for a few hours and then I have to think in.

Meb: What’s go to resource if someone wanted to build their own, is it back tube amp? Is that you describe it?

John: Yeah. There is a very popular board, you know, on Internet, message board called DIY, do it yourself audio. And it’s a filled full of people.

Meb: So can you buy like, can you use the stuff you can buy from my Crutchfield, or there is a much more like a boutique’e [SP]

John: fifteen years ago you really couldn’t buy tube amps. They were very rare specialty items, but they’ve become really popular again. So, today in any decent hi-fi store will have a selection or tube amps …

Meb: Just not RadioShack anymore.

John: Not RadioShack anymore. The question is where do you get the tubes or that’s the question everybody asks. And tube manufacturers are starting up again. The key was is that Russia used tubes in their technology much, much later into the game even, you know, like the middle range MiG fighters had tubes in them. So, they kept two factories running far later in the history then, you know, the West. So, there have been some vacuum tube resources maintained. Now China is becoming a vacuum tube manufacturer, and there’s a new vacuum tube factory in Germany now.

Meb: Where are your travels taking your next, you hear for a little bit or you, you know, are you getting down the rain, going somewhere?

John: Next, I’m going to Japan. I’m gonna visit a couple of the Southern Islands, so I want to kind of get away from it for a little while.

Meb: There is one of the Southern Islands that I’ve seen photos of and it looks like a Caribbean Island, it’s unbelievably beautiful. I’ve spent a handful trips to Japan, but it’s been mostly in the north skiing on the mainland and then up in Hokkaido, but I’ve never gone south. And one of the southern islands looks absolutely gorgeous, I can’t remember the name off my head. So ill have to download later and see what you thought about it. Anywhere else, is that main for 2017?

John: No, no that’s my next trip. After that it will probably back to your land in the middle of the year.

Meb: Good. Go kick up the animal spirits. We are bullish on European equities so I’m particular in Eastern Europe.

John: But my big trip from last year was Tasmania, which I recommend highly to anybody, it’s fantastic.

Meb: Good one.

John: Good one, nice people, beautiful place. Clean…

Meb: I always popped over there, it was down in Melbourne and Torquay for an investment conference.

John: Just take the ferry.

Meb: I was either gonna take that road towards Adeline, I murdered the pronunciation or go to Tasmania. And I think we even have some fly fishing in Tasmania, I may get that wrong.

John: Oh, no they have a lot of fly fishing.

Meb: And so now I’m having a little bit of regret that I didn’t go. But I travelled fair amount that. I was finally, you know, I’m just gonna set up shop in a city for a few days relax. And so I just kind of hung out in Melbourne and pretended like I was a local, and just kind of went to the coffee shop went to join the local gym and worked. But the funny thing about a lot of Australia is very similar vibe to California. And Tasmania, I think is even more remote than most of the places.

John: So, Tasmania is actually pretty remote but the key is that it’s relatively unpopulated, the population density is very low. So, people aren’t frenetic, you know, they don’t have that big city vibe to them at all. They’re warm and welcoming and they live in a sort of, you know, or reasonable life pace and such like that. Food’s good, the scene was extraordinary and pristine.

Meb: …to do list. John thanks so much for coming by today. I don’t want to take up anymore time. Where can people go, they want to find more information?

John: Sort of go to site as bolingerbands.com has links to everything else that we have. If you’re interested in Bollinger band analytics, the go to site is bbands.com, B-B-A-N-D-S.com.

Meb: And of course on Twitter B bands talking about Bitcoin and [inaudible 01:06:49]. Thanks so much for coming out today. Podcast listeners we’ll post all the show notes with links to many of these esoteric books, vacuum tube vampires and everything else and mebfaber.com/podcast. You can always find the show notes and links there, as well as subscribe to the show and iTunes, Stitcher, Overcast, my favorite listening app called Castro. Thanks for listening friends and good investing.

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