Episode #82: Vineer Bhansali, PIMCO, “The Market Is Severely Underpricing The Probability Of A Sharp, Catastrophic Loss To The Downside”

Episode #82: Vineer Bhansali, PIMCO, “The Market Is Severely Underpricing The Probability Of A Sharp, Catastrophic Loss To The Downside”

 

 

Guest: Vineer Bhansali‘s 24-year investment career started at Citibank, where he founded and managed the Exotic and Hybrid Options Trading Desk. He later joined Salomon Brothers in its Fixed Income Arbitrage Group, followed by the CSFB Proprietary Trading Group. Dr. Bhansali was at PIMCO for 16 years, serving the last eight years as MD and Head of the Quantitative Portfolios Team, which he founded in 2008. Dr. Bhansali also managed all of PIMCO’s analytics from 2000 to 2010.

Date Recorded: 11/15/17     |     Run-Time: 1:08:30

Summary:  Per usual, we start with Vineer’s backstory. It involves his physicist-origins, an unexpected move to an assortment of trading desks, and a run-in with the great, Fischer Black.

Meb soon dives in, asking about main strategies Vineer uses with his group, Longtail Alpha. Meb reads a quote from LongTail’s website…

“LongTail Alpha’s sole focus is to find value in the tails of financial asset return distributions. Either in the left tail as a risk mitigation hedge on multi-asset portfolios, in the right tail to add convexity to an investor’s risk exposures, or in both the right and left tails to produce alpha from convexity and volatility opportunities in a hedge fund structure.”

Meb asks Vineer to use this as a jumping off point, explaining his framework, and how he thinks about tail strategies. Vineer tells us that, at LongTail, they believe the probability distribution of returns for asset classes and multi-asset portfolios is actually not bell-shaped. Rather, there are many imperfections and anomalies in the market. And the tails of the distribution are quite different than the central part. While the central part of the curve tends to have many, smaller moves, the tails tend to be dominated by infrequent, large events. With this in mind, the goal is to implement various options strategies to help you position yourself for these tail vents. Keep in mind, there are left tail and right tail events (and a hedged strategy in the middle). Vineer references them all.

Meb mentions how, right now, most investors are more concerned with the left tail events. So how should an investor think about implementing a tail strategy? And is it even necessary, given Vineer’s statement in a recent Forbes article:

“…people generally feel better when they believe that they have portfolios with built-in insurance, i.e. protection against losses, even though the expectation (or average return) of a portfolio with or without such insurance is the same.”

Vineer discusses the difference between “volatility” and “permanent loss of capital.” What you want from a left-tail paradigm is a methodology that keeps you in assets, serving your long-term benefit. Generally, you want to be invested in the stock market. Vineer tells us the name of the game is to be able to survive the relatively short-but-harsh pullbacks, and even accumulate more assets during those times. Given this, Vineer has a 4-lever framework he uses to help create a robust left-side portfolio. You won’t want to miss this part of the discussion.

As the conversation unfolds, you’ll hear the guys discuss how, even though there is some concern about a correction now, the markets are still severely undervaluing the price of a sharp downturn. And option premia are incredibly cheap by historical standards.

Meb then asks for more details about actually implementing a left tail strategy.

Vineer’s answer touches on understanding and identifying how much exposure one wants to equity risk and inflation risk. Then, there’s the need to understand one’s risk threshold tolerance – the “attachment point” at which you cry uncle, whether that’s being down 10%, 15%, 25% or more. Given this attachment point, an investor could then go to the options market and buy “insurance” at this level, for a duration of time suitable to the investor.

This leads Meb to wonder why people think of portfolio insurance differently than life, car, or home insurance. We all pay those insurance premiums without thinking much about it, but there’s so much resistance to paying for portfolio insurance.

Vineer actually wrote a paper on this challenge. He tells us part of the issue is an aggregation, disaggregation problem. The right thing to do would be to lump the cost of insurance into the portfolio and look at the overall portfolio returns. But people fixate on the “lost” cost of insurance when option premiums expire worthless.

Next up, the guys discuss the current volatility environment. Vineer address two questions from Meb: “why is volatility so low?” And “is there a sweet spot on the option scale (how far out of the money) for investors looking to purchase portfolio protection?”

There’s way more in this episode: option selling strategies (instead of buying insurance, you’re the one selling it in order to generate yield)… A great piece from Vineer about selling bonds as a way to hedge your portfolio… How the traditional inverse relationship between market direction and volatility might not be holding up as much (look at Japan recently – surging markets and volatility together)… Vineer’s thoughts on artificial intelligence and “how to beat the machines”… And of course, his most memorable trade.

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Links from the Episode:

 

 

Transcript of Episode 82:

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.

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Meb: Welcome, podcast listeners. We’re rolling into the holidays here. It’s almost Thanksgiving. We have a great show for you today. I’m really excited about our guest. He’s right down the road. He’s worked at all sorts of places, Citibank, Solomon Brothers, CSFB, PIMCO on various desks such as fixed income arbitrage, proprietary trading group, head of quant-portfolios. Most recently he started his own firm called LongTail Alpha. He’s also an author, written four books, some whitepapers, has a great blog. Welcome to show, Vineer Bhansali.

Vineer: Happy to be here.

Meb: So Vineer, let’s rewind back. You know, I think a lot…it’s pretty common today for PhDs in physics to head into the quant-finance world. But kinda when you started, that may not have been the most traditional career path. Give us a quick overview of how a physicist ended up on a lot of trading desks and eventually starting his own firm.

Vineer: Yeah. It’s a pretty interesting story. It’s actually quite an interesting accident. I’ve had a lot of, I guess, fortunate accidents. They don’t seem very fortunate when they’re happening, but they turn out to be very fortunate in the long run. So I’ve kinda learned how to kinda roll with it.

So this one goes back to 1991, 1992, when I was finishing my PhD, and I was at Harvard and I was doing my PhD in physics, and I had pretty much wanted to do nothing but be a physics professor. But I was in my third year finishing my PhD program and caught an interview out of Wall Street out of Goldman Sachs and I absolutely knew nothing about finance, and I actually wanted absolutely nothing to do with finance. And I went there because, you know, it was basically a free flight to go and get interviewed in New York.

So I went there and I met with a bunch of people in the various trading desks and various research people. And one of the most memorable ones was sitting across on the trade floor from an elderly gentleman who seemed like he also had a physics degree and he was interviewing me.

And I could kinda read upside down what he was writing. And, you know, he was basically writing was, “Doesn’t know any finance. Is very good at math. He knows a lot about differential equations”, and so on and so forth.

And it turned out later, I found out, it was Fisher Black. And I went back home to Boston and I told my roommate that I met this guy by the name of Fisher Black. Have you heard of him? And my roommate happened to be an economics PhD student. And he said, “I can’t believe it. You met Fisher Black.”

So anyway, for a little while there, I was a star. But anyways, the long story short, I got a couple of offers to go and work there. And obviously at that time, you know, I didn’t really know how to do it. The following year, when I was looking for a faculty position and post-doc positions, I got another offer. And this time it was from that same firm, and then also from Citibank, and went down again and they said, “You know what we would like you to do is to actually be on our trade floor.” And I said, “Wow. This is even worse than the last time.” You know, first, I don’t know anything about finance. And second, I know nothing about trading, you know.

So I kinda made kinda sure like, “Are you sure about this? You know, what am I signing up for? If I do this, does this mean that I’m gonna be a slave and I’m gonna have to work here for many, many years?” They said, “Nope. You know, you just come here and you work as long as you want and on top of this, we’re gonna give you X number of dollars”, which was some very large factor multiple of what I was gonna make as a post-doc.

“And at the end of the year, if you wanna leave, just leave.” I said, “That sounds like a pretty good deal. You know, I can’t believe these guys are so dumb because obviously, I’m leaving in one year, I’ll just take this money and…”

So I deferred my post-doc for a year, and I ended up at Citibank derivatives desk and started to, basically, day one, was told start trading fixed-income derivatives. And that’s basically it. I have intended to go back to physics, now, for the last, you know, close to 30 years. I feel like I’m on a long sabbatical from physics, just haven’t gone back. So that’s the short long, story of, you know, how I ended up in finance.

Meb: There’s hope for you yet. You know, as a former engineer, there’s a lot of similarities. I mean, I moved down to Los Angeles for a year, just to live at the beach and thought the same exact thing. I said, “I’m gonna hate Los Angeles and also give the chances of this company succeeding very low percentage, but I’d like to do it for a year. Check that beach box for a guy that’s a mountain guy, so you never know.

All right. So you’ve written on a lot of things that, you know, our listeners would be familiar with, managed trend-following funds as well as carry, sort of, ideas and value. But let’s talk a lot about some of the main strategies that are the core of what you guys do at LongTail.

And there’s a quote on your website that reads, “LongTail Alpha’s sole focus is to find value in the tails of financial asset returns distributions. Either in the left tail, as a risk mitigation hedge or multi-asset portfolios, or in the right tail, to add convexity to an investor’s risk exposures, or in both the right and left tails, produce alpha from convexity and volatility opportunities in a hedge fund structure.”

So why don’t you use this as a starting point for our listeners, explaining a little more about your framework and how you think about tail strategies and how they work.

Vineer: Yeah. So I’d love to. So basically, we believe that the probability distribution of returns for all asset classes and for multi-asset portfolios is really not bell-shaped or normally-distributed, which is… You know, the general assumption behind a lot of theoretical finance is that distributions are normal. And a lot of finance has been built on this edifice.

And we know, as participants in the markets, and especially as a physicist in this business, that the science of markets is very different. It’s not normally distributed. Things are serially correlated. There’s obviously long-term trends that, you know, maybe you and I both know about. And, you know, there’s also a lot of imperfections and anomalies and so on.

Now, what we have done is for the last 30, or maybe 27 years or so, I’ve been focused on this whole wide area of option trading.

And what I found, after having done this for, you know, almost three decades, is that people confuse the central part of the distribution, meaning the bell-shaped distribution and the two extremes, and they extrapolate. They think that…most people think, and that’s not true for everybody, obviously, that once you know what the volatility is, you know a lot about what happens for extreme scenarios, extreme situations.

Our approach is a little bit different. What we say is that the central part of the distribution is very different than the tails of the distribution. So this is, you know, somewhat akin to insurance, the difference between the insurance market and the reinsurance market.

So if you’re, for example, an auto insurer and you’re selling a lot of auto insurance policies, on average, you know the policy claims are very small and there’s a lot of people who are insured. And you can make a pretty good statistical estimate of what your payout rates are going to be.

And you can set your premiums to be, you know, just a little bit higher than payout rates and essentially collect that excess premium that you get from selling a lot of auto insurance because there’s an incredible amount of statistical data, and you know a lot about that central part of that distribution.

Now, you compare that to the tails of distribution, now that’s the domain of rare events. So now, the reinsurance analogy is a hurricane that happens once every hundred years, or maybe an earthquake, you know, that happens very, very infrequently, it’s very, very hard to predict in a very accurate mathematical way what the likelihood is.

And that creates an enormous amount of uncertainty from the point of view of somebody who is underwriting that risk. So somebody who is going to sell reinsurance on this catastrophic or very large deviation event will require a very substantial amount of multiple.

So if an event, let’s, you know, in the catastrophe area, an event that is likely to happen once every hundred years, most reinsurers would charge, you know, a multiple of, call it, 4 times that value or maybe, 10 times depending on, you know, how much demand and supply there is. But people talk in terms of multiples of the fair value of the loss.

So you have a very different market for the central part of the distribution and for the tail of the distribution. So you can imagine the tail of the distribution is dominated by very infrequent events, very large events, and price is really set based on demand and supply and almost like a behavioural need for either hedging, or for selling insurance.

On the other hand, the central part of distribution is, you know, based on a lot of data, very frequent, small events. And it’s not so much demand supply, but just a way for people to offset their normal risks. So you have very different dynamics that drive these.

Now what we have done, and this is kinda what I’ve been specialised on and written a couple of books on the topic, is how do markets work when you’re in the tails of the distribution? And what are relatively cheap or expensive securities, whether they’re options or strategies? You know, it could be trend following, it could be other strategies that help you position better for those extreme events.

And our approach, essentially, leads us to be somewhat of a contrarian when the tails are being under-priced. And in some markets where tails are overpriced, we take the other side and we will provide that reinsurance, as long as we can cover it, you know, using other methods.

So, just to kinda summarise, you know, our strategies, we got a heading strategy for people who are looking for catastrophic protection on the left side. We’ve got another strategy that protects people from melt-ups, for example, credit portfolios that might under-perform if the equity markets keep rallying and volatility keeps falling, you can, kind of, fortify the credit portfolio using [inaudible 00:11:33] upside.

And then a combination strategy that takes both the left and the right and combines it with this plus a few other levers to create the most cost-effective exposure to, you know, either one of the extremes.

Meb: And it’s interesting is that, you know, depending on the investor’s positioning, so a long-only stock investor, you know, is most concerned with the left tails, bad things happening. But, you know, I think so many investors also don’t really consider the right side, which is like you mentioned, the melt-up. There’s so many investors we talk to that have been scarred from the last two bear markets and they have this huge risk of, you know, markets melting up. It’s interesting.

So before we go any further, let’s kinda get in some specifics. So right now, most investors listening are probably most concerned with their left tail side, the big, bad events. So thinking of like the average investor who’s allocated, has a global portfolio, so whether it’s an endowment or somebody listening at home just for their retirement, how should someone be thinking about implementing it?

And you also had a great article in Forbes where you mentioned, “People generally feel better when they believe they have portfolios with built-in insurance, protection against losses, even though the expectation or average return on portfolio, with or without such insurance is the same.”

So the question is, you know, how do you think about implementing it? Do most people even need it? Why even bother?

Vineer: Right. So this is a very, very interesting question. And, you know, I’d love to answer it because I’ve spent a lot of time thinking about it and constantly, you know, update my own understanding and knowledge of it. But there’s various levers you can use for better, more robust portfolio construction.

So the first thing that you have to do is you have to understand as a, you know, long-term investor or, you know, a retail investor, you know, likely somebody who’s got, you know, real money on the line who’s not just doing it for speculative reasons, but really is investing, you know, for the intermediate to long-term, what they’re concerned about is not necessarily volatility.

So again, the academic literature and the risk management literature has over-emphasised volatility as a metric for measuring risk. If you believe what I said before, the difference in the distribution, in the central part and the tails, you’re led to thinking of risk in a slightly different way.

Risk for a longer term investor means the likelihood and the severity of a permanent loss of capital. So is there a situation that can happen where a very well-thought out plan of investing suddenly gets thrown out the window and you basically do something and panic. Either you sell your risk assets or you do something else.

So what you wanna try to do is any risk management or downside risk mitigation paradigm especially, even in the right-side one, but let’s focus on the left-side for a second. You wanna have a methodology that keeps you in assets that serve some long-term benefit, you know, for your welfare.

So ultimately, if you want to keep up your purchasing power and you want to grow with the economy, and as the GDP grows, people will get richer and the stock market will go up. So generally speaking, you want to be invested in the stock market. The pullbacks of the left-side events are usually harsh, but relatively short, anywhere from three months, you know, to a couple of years. And the name of the game is you want to be able to survive those pullbacks. And better still, you want to be able to accumulate more risky assets if the market sharply pulls back. So how do you do that? So that’s kinda the question.

Now there’s four levers that I think of that are important. The first one is you need to have an asset allocation framework that is well thought out. So how much are you gonna have in stocks? How much are you going to have in bonds and so on?

And there’s no hard and fast rule, but generally speaking, you know, anywhere between 30% and 70% equities is, you know, a fairly decent balance for most people. And we believe that most people should have, you know, an allocation. Anything less than 30 is probably too conservative. Anything more than 70 is too aggressive.

And you want to dynamically target that baseline allocation based on your own comfort level. So as markets move lower, equity markets move lower and the value of the equity markets falls, you need to have some amount of liquidity so you can buy, you know, more equities and so on.

So rebalancing is a great way to get started for moderate fluctuations, small fluctuations in the markets. So if markets move more, then you need other tools, you need some hard diversifiers that, in my way of thinking, I call them trending assets.

So you basically have two types of assets, or two types of asset classes. There’s asset classes, or strategies, that are [inaudible 00:16:21], think some value or, you know, value stocks and so on. And then there are asset classes, or strategies, that are trending.

So if markets start to break, you want these alternatives. You want things like trend following, you know, managed futures, etc., in your portfolio, some small amount so that you can capture the larger moves. So [inaudible 00:16:42] breaking down, and some of these strategies will help you mitigate the downside.

Beyond that, if markets jump, which neither the rebalancing will help you, or the diversifying strategies like, you know, trend following or [inaudible 00:16:58] will help you, is where you need explicit optionality.

So at today’s pricing level in the marketplace, the market is obviously, severely under-pricing the probability of a sharp, catastrophic loss on the downside. So yes, people are worried, but in terms of absolute volatility or absolute pricing of downside hedges, we call tail hedges, it’s actually at all-time lows.

Now in relative value space, you know, you can look at various structures and say, yeah, FTSE [SP] and S&P are very expensive because of, you know, what’s called the volatility skew, etc. But those are technicalities, largely because in terms of absolute level of implied volatilities, which is what sets the price of options, options on the left-side are extremely cheap.

And similarly for the melt-up on the upside, they’re enormously cheap because there’s been a lot of systematic selling of volatility, and we can get into that in a few minutes if you want. But there’s been a lot of selling of options in order to generate yield. So option premia across the board are incredibly inexpensive today by long-term history.

And then the fourth and final lever is that at all points in time, you want to have some amount of cash or cash-like securities. You know, they could be straight T-bills or they could be a savings account or maybe they could be, you know, very simple things like two-year notes and the treasury two-year notes that are yielding, you know, 1.6%, 1.7% today, that are the least default-likely securities out there.

So the way we think of managing portfolio risk for our clients and ourselves, for myself and for my own portfolio, is I think of all four of these levers active at all times and creating a mix of strategies that give you, in a sense, the best mix, or the most optimal exposure. Some of it is qualitative and some of it is quantitative. But generally speaking, you wanna have all four of these options or alternatives available to you to create a nice, robust, left-side portfolio.

Meb: Let’s say someone listening says, “Okay. I’ve got a pretty good global portfolio. I’ve got some of these diversifiers, but I don’t have any sort of tail risk ideas.” What is kind of the 30,000 foot perspective? You know, what would be some of the mechanics of someone that wanted to implement it? What are the tools? How do you think about the best way to think about the tail-risk sort of ideas?

Vineer: Yeah. So that’s again, a fantastic way to approach this problem. So you really need to have a framework. So the way I’ll describe our framework…again, this is not the only framework you can use, but it’s a systematic framework.

It’s a little bit like, you know, going to the doctor and, you know, saying, “Okay. I want a physical cheque-up and I wanna make sure that I live, you know, a long, healthy life. You know, what are the things I can do today that will ensure that, you know, I’ll have a healthy, you know, fun life and I get to do the things that I want to do?”

So that’s similar to do this. So here, like I said before, if you want gains in your portfolio, if you want capital appreciation, you need to be exposed to some sort of risky assets, whether they’re equities, or corporate bonds, or something like that, that grows with the underlying economy.

So the first thing that we do is we try to get an asset allocation. So if you’re an investor and you say, “You know, I wanna figure out what’s the best way to [inaudible 00:20:22]?” The first question I’ll ask you, okay, in the framework is, “What is your overall asset allocation?” And the only reason I ask that question is because what I want to figure out is what is your exposure to the two core factors that matter for long-term investing?

The first core factor is equity risk or equity beta. And the second core factor is inflation risk or what I call bond beta. So let’s say you have a very typical portfolio, which most people have. Let’s say you have 60% in equities and 40% in bond, the 60/40 portfolio. Your equity beta in this case might be 0.6 or 60. For every percent move in equities, your equity portfolio will move by 0.6. And then your bond beta will come from the 0.4.

But now, you have to be a little bit more careful because that bond portfolio, if it is sitting in high-yield bonds, also contributes significantly to your equity beta because higher yield bonds are issuances of companies so that they have equity beta or equity exposure as well.

So the first thing that we do is we kinda do a diagnostic. So this is like again taking the doctor’s analogy, you go to the hospital, you get an x-ray or an MRI, you say, “Okay. While you think you have, you know, XYZ condition, but here’s your real condition. Your real condition is that you got 0.8 equity beta or 0.9 equity beta.”

And you got some of these other assets. You know, maybe you got some, you know, real estate, vacation property that might get distressed in a deleveraging environment, etc. So the first thing that we’ll do is come up with a good estimate of the equity risk.

So let’s say in this example for your investor, you know, that turns out to be an equity beta of 0.6. The second step we’ll ask is, “Okay. What is…” And by the way, all of this, any investor can do for themselves. So I’ll come to the tool in just about 30 seconds here, on what you can do.

So the second question is, “Okay. What is your risk threshold or tolerance?” Not just volatility, but where would you cry uncle and say, “You know, I gotta get out. This is just too much risk, and I don’t want to lose any more money.” So that, I call the attachment point, or what is called in the reinsurance language, attachment point.

So how far away is your pain threshold? So some people say, “I don’t wanna lost more than 10%.” Some people say, “I don’t wanna lose more than 15.” Some people say, “No more than 25.” So for now, let’s go with an example of let’s say, 20%. Say the portfolio falls more than 20%, then after that, you’re completely protected.

And let’s say you want to protect this portfolio over the next one year, so your horizon is one year. Now, what you can do is, given these three core inputs, you can basically go to market, go look at, you know, an option. And assume here for simplicity that you’re underlying beta was through the S&P 500. You can go and price up an S&P 500 option, index option, with a strike that is 20% at the overall portfolio level, or adjusted for the 0.6 exposure, if your beta is only 0.6.

So you basically wanna [inaudible 00:23:26] that exposure on 0.6 of your portfolio. And you can go and find that option price from the market. And let’s say, you know, for argument’s sake, it turns out to be 1%. So if you now spend 1% of annual premium for a year, you can be guaranteed that the portfolio will not lose anymore than that attachment point, once you have bought that option.

So that insurance is widely available. And most investors are able, if they chose to, to go out and buy that insurance. And it’s very hard to do because insurance or purchasing protection against a portfolio is very hard to because it costs real money. But it’s doable.

Now, you can be more sophisticated. And a lot of the institutional clients that we have, they give us some degrees of freedom, we call them basis risks, that allow us to do much better than that 1% market premium. We can actually do the same thing for, you know, obviously, in a much cheaper way and for a better convexity or better profile.

But in a nutshell, with that approach and, you know, it’s very easy. That protection is available. And today, and just kinda concluding this particular thought, because option volatility is very low, it is very easy and very cheap to buy that protection, especially given the fact that the equity markets have had such an incredible run-up. You know, adjusted here, they’re up approximately 15%.

So to spend one or one and a half percent to protect a good chunk of that portfolio from a severe downdraft, doesn’t seem that expensive. But it is very hard to do. It’s very hard to do because investors typically do not like to part with premium, that’ll decay to zero. It’s a little bit like buying, you know, fire insurance on your house. You buy it, but you don’t complain if your house doesn’t burn down.

In the case of financial insurance, or financial reinsurance, when people buy insurance against their portfolio, they don’t like it when that premium goes to zero. But the end effect is the same. Having that hedging in place allows you to actually hold onto your portfolio for further gains on the upside.

Meb: I wonder why, mentally… and I kinda sympathise with this. I wonder why, mentally, people compartmentalise and bucket portfolios sort of insurance, in this sort of framework, different than they would life insurance, car insurance, house insurance because everyone owns those, right? Like it’s not even a question on all those, sort of, investments.

But with portfolios, I mean, almost no one does, as far as I know. Do you have any thoughts or insights on why, from a behavioural perspective, someone who has doing it, any thoughts on why that might be?

Vineer: Yeah. So I’ve written a paper on this, and this is called behavioural perspectives in tail risk hedging. And I’m actually presenting one of this in January at our local… At Chapman University. There’s a conference on this exact topic. And it’s fascinating. And, you know, it’s actually in the behaviour literature. It’s quite well understood, you know, why these, kind of, events happen.

So for example, you know, one example people use is, so if you are given a bunch of positives, a lot of gifts, you like to get a lot of small gifts. You don’t like to get one big package with all the gifts. You like to get them in little, small pieces.

But when people have losses, they like to aggregate all their losses together. And it’s an aggregation, disaggregation problem here. So when people look at insurance on their portfolio, the right thing to do would be to actually take the insurance and then combine it with, you know, how the rest of the portfolio has done and say, “Well, this whole package has done X.” But what becomes salient is the losses on the insurance. And that’s people fixate on. And it’s not in the common vernacular of financial, you know, I guess, asset allocation, today, to actually aggregate losses and gains, or rather, insurance and the underlying portfolio together. But it’s coming that way.

And I believe to me, it’s very similar to having, you know, stocks and bonds in your portfolio. Now, you can think, for example, when you have 60% in equities and, you know, let’s say 40% in bonds. Why do you have the 40% in bonds? You have 40% in bonds because even the bonds yield less than stocks, both in terms of dividend yield and in terms of ability to return over time.

The reason you buy bonds is because they give you protection from their diversification. So it took about, you know, 50 years or so in, you know, classic Markowitz diversification papers and so on, that it became natural for people to say, “Hey, look. Buy a bunch of diversified assets when the correlation is negative or zero.” It makes sense because it reduces overall risk and allows you now, to hold that portfolio for longer and garner the gains.

And, you know, that classic Markowitz mean variance portfolio theory is still in practise, and people still use bonds, even though bonds have a negative rate [SP] of return compared to equities. That same logic has not yet found its way into the common asset allocation vernacular. Because you could of buying protection using cheaper options, and I don’t say buy options at any price, buy when optionality is something you can buy cheap insurance on the downside, it’s not very different than allocating some of your money to fixed-income.

I think the major hurdle is that there’s a very finite bond decay element. When you pay premium for an option, at some finite point in time, that premium, even though it’s very small, it goes to zero. And people don’t like their assets to go to zero. But that’s the theory, that’s a behavioural bias. Fundamentally, you know, in terms of finance theory, there’s no way to really justify not buying insurance if it allows you to garner gains at the overall portfolio level, under this risk.

Meb: It sounds like it’s just a marketing problem. Any listeners, you got any good response, let us know. So Vineer, a couple of questions that spawned from your comments. One, I’d like you to comment on the current environment. So why is volatility so low? It’s hitting record lows, not just in equities, but in a lot of asset class, sort of, volatility measures.

And two is kinda, is there a sweet spot, kind of, on the option scale that you think for most investors is more beneficial? So is it kinda using at the money, 10%? 20%? Any sort of thoughts there?

So first is why does the environment look like it does? And then two, any particular, kinda takeaways on where practical implementation of this sort of strategy might be?

Vineer: Yeah. No, that’s great. The second one is an easier question to answer, so I’ll take that one first. And the first one is a little bit longer, and I have my opinion and my view on it, and I’ll try to justify it.

So where you should buy an option to strike or the attachment? It’s really a function of your own underlying risk reward trade-off utility function or pain threshold, so to speak. Now the at the money-implied volatility is very, very low.

So the VIX is obviously, you know, in many metrics… It just bounced a little bit in the last few days, but it’s, you know, 30 year lows. If you look at interest rate volatility, it’s also at, you know, 30 plus year lows and so on. So volatility across the board is very low.

So at the money volatility is low, but out of the money volatility, meaning deeply out of the money puts it at a much higher implied volatility. And that’s just a function of the fact that the people who are selling them, don’t want to sell those options, you know, at the same volatility as at the money because if the markets fall, usually, volatility rises.

So from a protection versus price point of view, it really is a function of, you know, where do you want your protection to be? If you’re closer to at the money, volatility is low, but the option costs more because more likelihood that it’s gonna end up in the money. If you’re further out of the money, there’s a lower likelihood, but at the same time, it’s gonna be more expensive in pure out volatility terms, but again, cheaper in terms of the total premium you spend.

So the trade-off that you make here, or what you want to make is, you know, how do you actually create a downside hedging portfolio such that you’re not paying an excessive amount of premium for buying out of the money options, but at the same time, getting the benefit of the cheaper volatility?

And, you know, one of the simplest structures you can do in the market today is what’s called a put spread. So you buy a put that’s closer to at the money, maybe 5% at, and set another put that maybe 10% or 15% out. So that put spread is buying a cheaper option in terms of volatility and selling a more expensive option, and giving you protection between that 5% strike and 15% strike, if you so choose.

So that’s, you know, just an example of what you can do, and you can move it around, you know, as the markets change. And the option markets, to be very sure, are very dynamic and volatility changes a lot. So you know if you’re gonna do this, you know, on a more dynamic basis, you have to be on top of it. But generally speaking, a simple structure like that, you know, would give people a lot of comfort and doesn’t pay an egregious amount of premium. So, you know, that’s one thing for people to look at.

Going to your first question, so why has the volatility, or the VIX or many other metrics like… You know, in fixed-income people look at the MOVE index and, you know, there is essentially every index. You know, gold has a volatility index, and then decay has one and oil has one. You know, essentially every index, and I look at about 30 or 35 of them, is trading at multi-decay lows. And certainly in many cases, below the 2007, 2008 crisis.

And it’s happened in my own career. I’ve been doing this, like I said, for about 30 years, and I try to take a very scientific approach to, you know, this stuff. To me, it all repeats every 10 years or so. And it is driven fundamentally by a need for yield. So the ultimate reason… And it’s kinda stunning and I’ve written on a few pieces, both on Forbes and our website, if anybody’s interested, but the ultimate reason is that there are still regions and countries of the world. Take for example, Germany, where yields at the two-year point and five-year point are negative, right? So you’re giving money to the government in order to get less money back.

Now, that makes a lot of sense when you’re afraid, for example, in the aftermath of 2008, or 2009, and you want your money back. So you’re willing to lend it to somebody who likely is going to give it back to you at, you know, maybe a lower interest rate, or maybe, you know, with some haircut.

But in today’s environment where equity markets are at all-time highs, etc., you know, there’s really no fundamental reason why a government should be confiscating your money. But that’s the state of affairs, and those rates are very, very low. And the corollary of very interest yields is that people have been forced out of the traditional markets where they get yield into other markets to get yield.

Now, it’s almost like a sequence of things that have happened. So you go from not being able to get enough yield in the bond markets to maybe not getting enough yield in various asset backs that have been high yield and so on.

And then the last rung of the ladder, and it usually repeats in each one of these cycles, you know, I’ve observed over the last, you know, 30 years or so, is that people start getting into synthetic ways of generating yield.

So in the 2006, 2007 event, you had a lot of structured products, a lot of synthetic CDOs and so on, where you packaged various underlying securities, you know, that were exposed to the housing market, for example, to get synthetic structures that would give you yield.

Now in today’s environment, that analogy, and this is in the paper that I, you know, recently published on what I call shadow insurance, or volatility selling, short volatility strategies. I call it shadow insurance because what people are doing…and with people, when I say people, I mean a very generic term for everywhere from large institutional investors, endowments, sovereign wealth funds, pensions, trend followers, risk parity managers, risk premium harvesters, and, you know, even many of the inverse volatility EDFs, everybody’s gotten into the business of selling options, of selling insurance.

Because when you sell an option, and the market does not move, you get to keep the premium. And that premium, if you add on to your already existing asset base, that looks like additional yield, and everybody’s looking for additional yield.

So the main reason, again, is very low yield in the marketplace coming from the [inaudible 00:36:06] banks, keeping a lot of liquidity, so there’s very few sources to get yield. And then the market taking a clue or a hint and saying, “Well, this is licensed to sell volatility”, and volatility selling really, is reason why implied volatility levels have gotten, you know, to very, very low levels that we’ve seen in the last year or so.

Meb: So there’s a lot in there. And then thinking about volatility, I mean, I remember back on the blog, pre-crisis, we were writing about a lot of volatility writing funds, and a lot of them exist in the CTA space.

A lot of famous names, and in looking back on that post, it’s funny because I don’t think any of them exist anymore because you plug along a lot of these firms that just kinda unconsciously sell vol, sell vol, sell vol, gives you a nice sharp ratio of two, you make a percent a month, or whatever it is, more if it’s levered, and then it eventually has down 30 month, etc.

One of the things I wanted to kinda talk about as we kinda shift around from buying vol to selling vol, and how do you think about… Price is, kind of, always the determiner. Like there’s a price at which it makes sense to buy a stock. There’s a price which it makes sense to not own the stock or to even short it for a company like Apple.

But also for options, you know, thinking about it right now, it seems like we probably both agree that volatility is pretty low, and many options, sort of, ideas are probably under-priced. But how do you think about the pricing of options, too? Is it, you know, a time when you think it’s totally reasonable to be selling options or implementing that sort of strategy? Like, how does that balance work in your head?

Vineer: Yeah. So I think of option selling a little bit like, I already used the term, shadow insurance or insurance selling. So when you’re a seller of insurance, you know, you are paying like an insurance company. How does an insurance company think? They say, “Okay. If I sell insurance in different asset classes”, and by the way, that’s what a lot of people are doing. “What is my aggregate maximum loss that I can suffer in a catastrophic event where everything gets correlated?”

So, you know, a new global financial crisis happens, everything gets unwound. How much can I lose, maximally, on all of those insurance policies? So the metric is a little bit different than a traditional portfolio metric. In a traditional portfolio, most investors look at, for example, sharp ratio, right? They’ll say, “Okay. My sharp ratio…” A sharp ratio is essentially the return that strategy delivers over the risk-free rate. It could be any risk-free rate you want. For example, you know, the T-bill rate divided by the volatility? So that’s the sharp ratio, return over risk ratio.

When you’re an option seller, your metric is slightly different, but similar. It’s basically, okay, what is my max income, or max yield gain per unit on the denominator or per unit of catastrophic downside risk? So if everything gets uncorrelated, or correlated, and everything moves up against me at the same time, what is my maximum loss?

And that’s the first stage of, kind of, that calculus is to say, “Okay. What I need to do is I need to diversify the insurance selling or the shadow insurance across many different lines of business.” And that’s essentially what people have done. Many large, deep-pocketed investors are selling interest-rate volatility. They’re selling equity volatility, [inaudible 00:39:25] volatility, and that’s why volatilities have dropped, or have gone down so much.

At this point in time, you have to now look at, “Okay. What can happen if we are running a very large short volatility portfolio if the market fluctuates?” The problem with volatility, very different to a traditional asset, is that the way you sell volatility is through an option and when you sell it…whether it’s explicitly or implicitly.

Now, when you sell an option, it has, by definition, by construction, a very non-linear response to underlying market moves. So using a sharp ratio type technique where the denominator is, you know, more well-behaved, the volatility is more well-behaved, it’s very dangerous because in this case the maximum loss is extremely non-linear and then technically, I’ll use one buzzword here, but in a option trader’s vernacular, it’s called the gamma, the negative gamma.

So if you think of now, the dynamic, and again, this is in the paper, when volatility is very high in the marketplace, the gamma turns out to be low, meaning for any small fluctuations, you don’t have the risk of a large change in the risk profile of your portfolio.

As volatility goes lower and lower, the gamma actually increases. And as volatility gets lower and lower, more and more people come into the volatility selling business because it’s attractive, first, and then secondly, you have to sell more in order to get the same deal because the price of options go down as volatility goes down.

So what this has is a very significant multiplicative effect on the amount of total risk or total negative gamma in the portfolio. And again in the paper, I show some calculations, but the bottom line is that the market gets very, very exposed to noise and small fluctuations.

And, you know, over the last four cycles that I’ve observed this, the story always starts the same way, that at some point, the posture of the market participants becomes so exposed through small fluctuations that any small fluctuation that is unexpected can create a very significant cascade.

And again, just to be very, very clear, sharp ratio is not a good metric for volatility-selling strategies, and, you know, just to echo what Meb, you said, a couple of minutes ago. Today, a great poster-child of this would be one of the inverse volatility ETFs like SVXY or XIV that trades in the market.

If you look at the sharp ratio, the cosmetic sharp ratio of one of these securities, it looks like a sharp ratio of four and a half. This is a volatility selling structure, right? So a four and a half sharp ratio is almost eight or nine times the sharp ratio of the stock market. The stock market sharp ratio over the long run is about 0.7 is 0.8.

So if you mechanically take the security, this ETF, at today’s pricing level, and put the sharp ratio in, let’s say, Markowitz optimiser or something like that, the optimiser is gonna say, “Well. Put an enormous amount of your allocation to this [inaudible 00:42:24] volatility EDF because it’s got such an incredible sharp ratio.”

But it’s very misleading because the rate of return to risk metric is not the sharp ratio, but it is how much return are you getting or a catastrophic potential loss on the downside? So again, to conclude, you know, this particular topic, I believe that maybe, the short volatility type of strategy has a little bit more to the run, but you are either in or very close to a very significant danger zone already.

Meb: Interesting. You know, Vineer, we don’t have a market environment where there’s ever gonna be volatility again. We’re getting ready to print, although it’s pretty close after today, I think November would be the 13th up month in a row in the stock market, which has only happened once before, ever, in the 1950s, and it never a calendar year. So I’m actually cheering that we do the full calendar year, 12 months up in a row, just to confound everyone that a year ago it was, like, you know, running for the hills.

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Meb: All right. Let’s switch gears a little bit because this podcast could go on for three hours because I have so many more question, but we may have to get you back on. But by the way, is that speech open doors in January, or is that a private event?

Vineer: I think it should be open doors at, I think, it’s at Chapman University. I think the organisers would be very happy to have participants show up to that. Contact them and see. Yeah.

Meb: We’ll post links to, not only all the papers and books and websites, but also to that speech if we can get a link afterwards. So I wanted to talk a little bit about a piece you wrote involving bonds. And the punch-line of the post, and here’s the quote. It says, “Investing is always a matter of price. At today’s prices, bonds are neither insurance, nor an investment. At best, they are hedges, but not by owning them, by selling them.”

So with that takeaway in mind, walk us through the thought process you had in writing this.

Vineer: So this is somewhat controversial. And I knew it was gonna get some people quite engaged, which it did. The idea here is that trying to…maybe it’s, you know, a little bit, you know, more aggressive at the top than it truly is, but I just wanted people to think about these very strong assumptions. In everybody’s portfolio diversification strategy, there’s an assumption that you buy stocks, you buy bonds, and bonds become diversifiers against stocks, like we said before.

Now, what has happened over the last, almost decade is that people have gotten an enormous freebie. So what has happened is yields have fallen. As the central banks have come in and pushed liquidity into the marketplace, that has collapsed interest rates globally. We just talked about negative interest rates.

And, you know, for anybody who knows how discounting works in fixed-income or, you know, basically any asset class… So discounting is an exponential function of interest rates. So as interest rates fall by a little amount, the discount factor rises. And what that does is it actually raises the present value, the NPV of future assets.

And yes, truly for fixed-income as yields fall, that, you know, obviously goes very high. And when yields go negative, bonds create above par value, which is another way of saying, you know, you’re paying more money than you’re gonna get in the future.

So as discount factors fall aggressively, bond prices clearly go up. And then as discount factors fall, asset prices, across the board, also go up because the discount factor is fundamental to all assets. So whether it’s equities, equities are discounted by the future dividend, expected dividends, the discount factor and so on and so forth.

So what you’re seeing with this miraculous, but wonderful freebie, where stocks and bonds are supposed to be diversifying in terms of, you know, day to day return volatility. And truly they are, and they have been in the short run. But all asset prices on an accumulative basis have gone up. So the accumulative correlation between stocks and bonds and, you know, a lot of other assets, is very, very positive because all assets have gotten bid up.

Now, that brings us to, you know, this one-page blog that I wrote a few days ago that you just mentioned. So there’s two ways of thinking about using bonds in an equity or diversifying portfolio. The first one is, okay. You say, “Look. I’ve got equities. Let’s buy some bonds.”

And that’s diversified based on this long-term historical correlation that people have believed. But the correlation between stocks and bonds as we know, you know, has been somewhat negative since 1987. But prior to that, due to high inflation, that correlation was actually fairly positive meaning stocks and bonds rose and fell together.

So if you believe that bonds have a finite lower level of yield, so yes, negative yields we thought would never happen, but they happen in Europe. So now, you’re at a point where you’re trading at, you know, extremely low yields across the board, across the globe. You know, if you look at, for many European countries, they’re trading lower than, you know, U.S. treasuries and so on and so forth.

The amount of diversification benefit that the bond market could provide you against stocks goes down because you’re close to that zero bound in yields. There’s really not much appreciation you can get once you’re at zero or, you know, somewhat below zero. So that’s the second part of it. They are not a diversifying or good insurance outlet.

Now, you also say, well, talk about the first one. What about as an investment? So investment in absolute terms is something that gives you more return on your money if held over time and really, you know, more real return on your money.

So if you believe that, and we got the inflation numbers out today, right around two percent or so inflation, you know, how can one look at a treasury bond or a five-year trend, you know, or even a shorter dated instrument that’s giving you, you know, between one and half and two percent yield, and say that you’re getting any investment return on your money. Are you really getting very real investment return on your money? Your purchasing power is not keeping up with the rate of inflation.

So the first idea is that buying bonds doesn’t supply you with much diversification because there’s truly not much price appreciation you’re gonna get. Secondly, when inflation is running at higher than 2%, and the central banks are really trying very hard to raise inflation. Then it’s very hard to justify having bonds as an investment in your portfolio because they don’t give you real return.

And that brings us to the conclusion, so why are they hedged? How can they be used as a hedge? Well, they can be used as a hedge, somewhat by actually betting that as inflation rises, and as interest rates rise, the bond market falls. And if the bond market falls and drags down in a reversal of what we’ve seen in the last 10 years, all the other asset classes, you get to protect your overall portfolio value. And by doing so, you’re not selling a lot of your equities that might’ve have embedded capital gains on it.

So that’s, kind of, the theme of the idea. And again, you know, as I mentioned, you know, this got some people thinking. And obviously, there’s, you know, many schools of thought. And in the short run, bonds will reflexively act like, you know, they reflect the quality instruments. But over the long run, if you hold bonds long enough, you’re neither getting return, and I don’t believe you’re getting much in terms of insurance benefit either.

Meb: Did you get some good, angry heckler email responses to that?

Vineer: No. Nobody was very angry. I think all the responses were quite intelligent, and one of the exceptions to my statement, which is very valid, is that once you look at liabilities, and most retail investors only have assets that they look at. But many of the larger institutional investors also have liabilities, and they are clearly, you know, bonds have a different role. They are there to match their liabilities. And so there is some role for bonds as, you know, long-term liability hedges.

So, yeah. So, you know, my paper, I got a lot of very intelligent comments on it. And, you know, really the point was to kinda open up people’s minds to the fact that if correlation signs were to switch, and inflation were to come back and stocks and bonds start to move back in together, you know, bonds would be better as short hedges, not as long hedges or instruments.

Meb: And I think that puts it in the same category, though, is tail risk is where if you were to actually short bonds, you know, you exist in that negative carry whirl, which is, you know, so many people hate on so many levels. Not to mention, I mean, thinking about Japan. I mean, how many macro managers have we seen in the last 20 years? That’s the famous Widow Maker trade, right, trying to short Japanese bonds and they just don’t seem to go anywhere.

Vineer: Yeah. And I see that, you know. That’s a very, very good point, Meb, because I say that in my paper, Japanification, right? So if there is a very small but finite probability and this is completely rational, right? The reason why people buy bonds at low yield and even negative yield is because there is a finite probability.

And this is a classic hallmark of rational bubbles is there has to be a finite probability of a very rare event, which is, you know, in this case, something like a Japan outcome that will induce some people to buy even at low yields. So that’s absolutely a possibility, and that can absolutely happen. And if that happens, you know, my piece will still be absolutely wrong. But I believe the likelihood of that happening is, you know, much lower than the market is pricing today.

Meb: We probably gotta ask a few more questions, start winding it down. As a former/current physicist who, probably, you know…having worked on a lot of the top desks on Wall Street, what are your thoughts these days about, you know, quantitative investing and the impact of say, big data and artificial intelligence?

Is that something you would spend any time thinking about or researching or have any impact on what you’re doing?

Vineer: Yeah. It does quite a bit. I mean, so to me it’s technology. You know, we’ve generated by many anecdotal writings…you know, in the last two or three years, the world has generated, you know, more data than it has generated over the last few hundred years. And the rate of data gathering is just going to, obviously increase.

And I wrote a paper on this topic on…you know, and the paper is called, you know, and it was given at the Journal of Investment Management Conference, “How to Beat The Machines Before They Beat You.” And, you know, one of the concluding thoughts was, that yes, there are certain things we can do. For example, not engage in the things that machines, or artificial intelligence, or big data-based systems are inherently better at, which is short-term tactical trading and market making and so on. But there are certain things that we can do as humans who can think outside the box, who are not required to think just in terms of raw data and data processing. And just in terms of very rapid, you know, linear regressions or whatever that, you know, underlying model might be.

And again, machine learning and artificial intelligence is kinda like, you know, the most talked about thing in the marketplace today. But there are certain things where there is not enough data, where humans are still extremely good at not only making hypotheses, but also predicting and then executing. So what I call places where machines don’t yet go because they don’t have enough data.

So we spend a lot of time thinking about that intersection because I do believe in my domain, the tails, almost by natural selection… I’ve selected an area where any marginal increase of quantitative or data-processing analysis can have a very significant impact. But even if it doesn’t, there’s still a way for priority thinking or, you know, for systematic human thinking to make a contribution, because there’s not enough data for a statistical system to actually, you know, make very good probabilistic judgments.

So we spend a lot of time thinking about it, and we believe that, you know, machine learning and AI and that data science is here to stay. You know, it’s just a natural evolution of technology. You know, it’s not unlike automobiles, you know, at the turn of the last century. Horses were the things that people used. And people said, “Look. Who’s gonna go and get this noisy, smoke-spouting object called an automobile, you know, when horses are so much easier to use?” And so on and so forth. And obviously, eventually technology, you know, improves exponentially and then automotives became not only cheaper but faster and cleaner and all that. And now you got, you know, the electric cars. So the horses have been relegated to, you know, the wilderness and to hobbyists.

So I do think over the next 50 to 100 years, you know, traditional macro investing, like traditional investing paradigms, are probably gonna go the way of the horse. Very specific domains where people would use them. Most of the day to day market making and trading will be machine-driven. But there are pockets where I think machines still have, or AI still has, a long way to go because there’s just not enough data.

Meb: Yeah. You know, I love thinking about these things. I was actually tweeting this morning over coffee. I said, “I wonder what everyone, if you had to go back 20 years, would think would be the most surprising market development over the last 20 years.”

It was pretty funny to see the responses because I said mine was negative sovereign yields. I said, “If you were tell people that you would have negative government bond yields, people would say you’re crazy.”And of course, like half of my responses were people talking about some sort of central banks and going crazy about that. And there was some very emotional cryptocurrency investors that were upset that I didn’t say Bitcoin. But, you know, I spent a lot of time thinking about that. You know, in the next 10, 20 years, what are gonna be the big surprises? I don’t have any good answers, but I think it’ll be fun to watch, certainly, in that AI, machine learning world.

I’m gonna ask one or two more questions. We’re gonna have to go. And by the way, going onto that last quote, I’m gonna have to add this to the article. Jeff, Vineer has a great graphic from one of his papers. And it’s a “Time Magazine” ad from 1969, and I’ll read the headline. It says, “The ‘Fat Time’ of day. You’re really hungry and ready to eat two of everything. Here’s how sugar can help.”

And this is an article from sugar information that is trying to convince people to lose weight, and the way to do it is you eat a couple tablespoons of sugar because it only has 18 calories. It’s just funny how information changes. That’s not a question. I just love this. We’ll add it to show notes. But I’m sure there’s a lot of those that we probably look back and are, kind of, embarrassed about.

Okay. Two more questions, and then we’ll wind down. Great post recently on spot up, vol up. You know, I think a lot of people assume that the vol kinda only goes up when markets puke. And you had a, you know, kinda challenged a traditional view, this inverse view between market direction and volatility and talking about Japan. You wanna make a quick comment on that, on what you were writing about?

Vineer: Yeah. No, that’s another interesting dynamic. So what happens is, you know, and I’m glad you brought up the sugar example, is that a lot of times, investors start to believe what’s told to them, repeated to them enough times. And in this case, well like, you know, sugar is good for you to lose fat. And that kinda view stuck with people for a very long period of time. And I think it took many, many years before people realised that was exactly the opposite of what reality was. Well, who knows? I mean, maybe that is the truth, but who knows?

But the point is that things that get repeated enough times, and got thought enough times, it becomes conditioned and institutionalised and so on. And in the volatility markets, one of the similar things that have happened, since 1987, is this assumption that when markets go down, volatility rises. When markets go up, equity markets go up, volatility falls. It started since 1987 because generally in the sell-off, illiquidity increases and people find that they cannot hedge. So there’s an extra premium that you pay for the downside. So that’s the traditional way of looking at it is spot down, vol up, spot up, vol down.

Now, what happens in a market that is totally off sides, meaning there is a lot of bad positions both on the upside and the downside, is that can get totally flipped. It happened in China about two years ago, when there was a lot of excess buying of call options, and there was a speculative mania on upside.

And recently, over three or four days ago, it happened in the Nikkei market, the Japanese stock market, where exactly the opposite of this traditional directional move happened. So the Nikkei market rallied about maybe one and a half or two percent overnight, and the VNKY, which is the analogue to the VIX in the Nikkei equity options market, actually rose almost six or seven points.

So what happened was something broke. And the reason something broke, in my view, comes back to something that we spoke a few minutes ago about selling off options in order to generate yield. So there is a lot of systematic structural selling, institutional investors and retail investors have been convinced that selling options is a consistent way of making money. So you sell a put option and you sell a call option. At inception, you don’t see any exposure because the delta or the put option and the call option, meaning they essentially cancelled out. But the call options itself are at a much lower price so you have to sell more of them.

So what I believe has happened is that there is a very severe imbalance in the marketplace where there are a lot of not so well-managed, or well-hedged positions, on the upside.

And the point in my paper was that if you come in one day and you have an unanticipated shock on the upside, like what happened in the Nikkei, you know, the U.S. could be, kind of, a bigger example of it, where you come in and suddenly, maybe there’s a tax deal or maybe there’s a tweet or something that, you know, convinces people that the market should be up. You come in, and the market is up a few percent. You could easily be in a situation where there’s a mad scramble to buy those options that have been sold on the upside back. So you could be in a situation where the equity markets are up and volatility is up.

And that could create very significant disarray because the spot up, vol down, and spot down, vol up is so deeply embedded inside of so many systems, risk parity, dynamic risk balancing, volatility targeting etc., etc., that it could cause a lot of disarray in the markets.

And I just finished a paper with Larry Harris from USC that, it’s actually on the SSRN today on this topic of what can create this shadow insurance market to unwind? And again, it’s not a high probability scenario, but if it happens. It would because one of these types of correlations breaking down, not unlike the stock, bond correlation. You know, things that are assumed but are not really severely tested with lots of models.

Meb: Yeah. Let’s have a good melt-up. I love a good bubble. There’s not enough good bubbles these days, only in some places. I miss the…late 1990s was a lot of fun until it wasn’t. But Vineer, one more question. We ask this to everyone. If you look back in your career, what do you think has been the most memorable, and it could be good, it could be bad, most memorable trade or investment that you can think of?

Vineer: Oh, boy. There’s been so many bad ones. I mean, I think I’m one of those who, you know, I remember…I think, I remember very few of the really good ones. I remember all the bad ones where I, you know, kicked myself.

I think one of the best ones and, you know, fortunately, I didn’t make the same mistake twice was the internet bubble, I fought it, I fought it, I fought it. So it’s not a trade, but rather an investment policy or philosophy. And I kept over-thinking it and kept, you know, thinking about my, you know, own economic and rational reasoning and, you know, talking about why the market shouldn’t be going up.

And I fought it. You know, I didn’t lose any money on it, but I didn’t make any money on that bubble either. And I kinda promised myself, you know, the next time an asset bubble happens, yes, I’ll challenge it and, you know, be cute it about it and questions it and so on, but I will ride it.

And fortunately, in the last few times it has happened, I’ve been able to do so because, you know, the markets can behave irrationally for a very long period of time. And part of being an investor is, you know, not to over-think it and try to, you know, overlay your own, you know, [inaudible 01:03:53]

Meb: I wonder if that experience kinda… So we didn’t even get into it today, but Vineer has written a lot of great papers on trend following and managing trend following funds and still does. I wonder if that experience kinda sowed the seeds of trend following for you. Was the kinda the beginning…was that an influential event, do you think or was a…?

Vineer: Yeah. You know, what I found is that it’s a very different thing…you know, intelligence supplied in the markets to a certain degree is good, but beyond it, you know, it’s actually very counter-productive. And a lot of people have written about it. I’m not the first one, but it’s very easy to ride the trend.

And, you know, I guess, you know, one thing I’ll say is, and I’ve written a paper, again, on this topic, but, you know, after having done this for 30 years, you know, there are kinda two very simple factors that I have found to have just a very good long-term structural predictive power in terms of your own performance, you know, for your portfolio.

And any investor can do this. This doesn’t have to be an institutional investor, or you don’t need to use fancy derivatives. And I think the paper you’re referring to is the one where, you know, it’s called “Trend and Carry in a Lot of Places.” And the idea is very simple. Do you wanna be on the right side of the market? And what does that mean? It means, you know, you just see, you try to look at that market and say, which way is it going? Don’t try to figure out which way it’s going to go, but which is it going and be on that right side. So that’s, obviously, been the most profitable long-term strategy as tested by a lot of people.

And the second basic tenet is, you know, don’t pay too much for it. And there’s various ways to doing it, you either don’t pay too much fees, you know… And a more sophisticated way of looking at it, you don’t pay too much negative carry.

So if you can combine a strategy which has positive carry, or low cost, and is on the right side of the market, over a long period of time, that’s gonna, you know, do well for you. And again, it’s not a secret. You know, most people know it, but it’s just so darn hard, you know, day after day to come in and just do the right thing and do these right things and not get undisciplined. And, you know, start to, you know be too cute or too smart in the marketplace.

And I think that’s, ultimately, probably been the best lesson that I’ve learned over the last 30 years of doing this.

Meb: Vineer, we didn’t even get into your screenwriting or piloting jets. Do you got any good, long races coming up? Vineer, for the listeners that aren’t familiar, one of his hobbies is causing a lot of pain to himself? What do you call that again? But it’s ultra, ultra long races. You got anything coming up for 2018?

Vineer: Yeah. You know, I’ve done about six or seven, yeah. It’s 100 milers. I’ve done western states five times. I’ve finished it and then the Ultra-Trail du Mont-Blanc. And I just recently did a very slow Angeles Crest 100 about a couple of months ago up north of us, in LA. And it was very slow because it was the first time I was doing a long race solo, meaning with, you know, basically no aid and no help.

And again, I had to plan for it because it’s a totally different ball game and you have nobody to, you know, console you at various aid stations. But yeah. So I am signed up for a couple more 100s next year, and I’m not as competitive as I used to be, but I’ll try to get them finished.

Meb: I did one marathon, and it was kinda one and done. I think I may be done with the long races though…

Vineer: I do much more.

Meb: Yeah. Wes Gray at Alpha Architects, he’s doing this annual 28 miler hike/run, I guess you could run it if you want that I may try to do next year. I missed it this year. Very cool, Vineer. Look, if people wanna follow your writing, your fund management, everything else you’re up to, where’s the best place listeners can follow you?

Vineer: The www.longtailalpha.com is a place where most of the shorter pieces are. A lot of links to the research pieces are also on our website, if the people wanna read them. And then, you know, if you want, you can shoot an email. I’m usually pretty responsive about interesting questions and so on. Obviously, I am in the markets because I love them and, you know, great, interesting questions are always welcome.

Meb: All right. You asked for it. You’re gonna get a ton of reader responses, listener responses, I warn you. Look, it’s been a blast. Thanks for coming out. Listeners, thanks for taking the time today. It’s been an awesome episode. Send us feedback at themebfabershow.com. You can always find the show notes. We’re gonna post all Vineer’s books, papers, all that good stuff, mebfaber.com/podcast. Remember to subscribe to the show on iTunes. Leave us a review. Thanks for listening, friends, and good investing.

 

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