Episode #234: Harindra de Silva, Analytic Investors of Wells Fargo Asset Management, “Just Because A Factor Hasn’t Been Working For 3 Years…Don’t Ignore It…Continue To Evaluate It”
Guest: Harindra de Silva is president and portfolio manager for the Wells Fargo Asset Management Analytic Investors team where he focuses on the ongoing research effort for equity and factor-based asset allocation strategies.
Date Recorded: 6/24/2020 | Run-Time: 50:01
Summary: In today’s episode, we’re talking factors and long/short investing. We discuss factors as anything that can help explain return, and the all-important task of assigning weights to factors in portfolio construction. We get into short selling, and some of the challenges that need to be carefully navigated, from risk management to asymmetric return distributions, to the cost of borrow.
As we wind down, we cover the appetite institutions have for factor investing and how they seem to be a lot more interested in general, however, they’re less willing to pay for strategies they can get cheaply.
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Links from the Episode:
- 0:40 – Intro
- 1:43 – Welcome to our guest, Harindra de Silva
- 4:04 – Harindra’s shift from engineering to finance
- 7:17 – How Harindra thinks about factors
- 10:11 – Most popular factors
- 11:58 – How to put together a portfolio using factors
- 14:09 – Weighting factors
- 18:07 – How factors evolve over time
- 19:54 – State of factor investing today
- 19:55 – Risk Management and Optimal Combination of Equity Market Factors (Clarke, Silva, Thorley)
- 20:59 – Shorting
- 24:11 – Adding short positions to a portfolio
- 26:20 – Approach to global investing
- 28:59 – How factor investing has changed over the past 10-20 years
- 32:58 – General thoughts on the state of the current markets
- 36:07 – Most common mistakes investors make with factor investing
- 40:55 – Things that have Harindra excited today
- 40:45 – Link to Harindra’s writings
- 43:25 – ESG investing
- 44:51 – Most memorable investment
- 49:05 – Connect with Harindra: Wells Fargo, SSRN
Transcript of Episode 234:
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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.
Meb: Hey, podcast friends. We got an awesome show for you today. Our guest is one of my favorite quants. And as we learned today also a neighbour, president and portfolio manager for the Wells Fargo Asset Management crew but you’ll likely know him from his many days at Analytic Investors where he focuses on the ongoing research effort for equity and factor-based asset allocation strategies. And today’s episode we’re talking racing cars, but also factors and long/short investing. We discuss factors as anything that can help explain return and the all-important task of assigning weights to factors in portfolio construction. We get into short selling and some of the challenges that need to be carefully navigated from risk management to asymmetric return distributions to the cost of borrowing stocks. As we wind down, we cover the appetite institutions have for factor investing and how they seem to be a lot more interested in general, however, they’re less willing to pay for strategies they can get cheaply. Please enjoy this episode with Analytic Investors’ Harindra de Silva. Harindra, welcome to the show.
Harindra: Thanks, Meb. Nice to be here.
Meb: It’s a strange time we live in, 2020 during quarantine because you’re probably the closest podcast guest I’ve ever had that’s not in person. I think we’re probably 100 or 200 yards away today.
Harindra: It’s strange that this is the first time we met and we live literally a few hundred yards apart. But I guess this is a sign of the times because it’s almost like learning to live in this new environment.
Meb: It’s probably a good thing that you’ve never seen me in the neighbourhood because I sort of look like Jeff Bridges in Lebowski wandering around in my pajamas because I walk our dog at least twice a day, half the time I have on headphones and listening to podcasts. So I look like a crazy person. Anyway, before we get started, we’re gonna go deep on all things quant and factors today. I wanted to ask you a question first, are you still car racing?
Harindra: I am. There isn’t a lot of car racing going on right now just because of the social distancing and the challenges with putting on events. But I’m hoping to do an event this weekend at Buttonwillow which is a local SCCA event. It’s a small crowd and you’ve got to make sure when you’re passing another car you have to be at least 6 feet apart, but apart from that, it will be pretty much the same.
Meb: What does racing mean for you? Are you doing NASCAR? Are you doing go-karts? Are you doing figure 8? What’s the style?
Harindra: It’s road racing in open wheel cars. Formula Three would be the best way to describe it. It’s a Formula car with wings and slick tires. And it’s driving on a road that’s conventionally referred to as a road course. And what I enjoy about it is one of the few things you can do where you’re completely focused in the moment and everything else sort of disappears. Somebody characterised it as cheap zen.
Meb: I did one of those Las Vegas ones about a year ago. I took out I think it was like a Ferrari on the track and it was so much fun, but they’d also had a Baja racing track. One of the best experiences I’ve ever been a part of where you’re in these huge trucks with monster wheels that just absolutely launch off this dirt track. So listeners, if you ever have a chance, find yourselves in Vegas, check out the Baja racing experience. It is out of this world. Super fun. Okay, let’s talk investing. You’re a fellow engineer, although you were mechanical. You then shifted at some point I see in your origin story to grad school econometrics. What was the reason you decided to move over to finance and the investing world?
Harindra: Well, I realised when I was doing engineering or studying engineering that what I really enjoyed was the design aspect of engineering, not the maintenance aspects. So the whole idea of looking at something and trying to figure out, A, what made it work, and then B, how to make it work better. And I realised when looking for a career in engineering, that most of the jobs at least in mechanical engineering are mostly maintenance oriented. As I looked around, I decided that it was not so much the mechanical part of it, but the design and the ability to kind of come up with new ideas and incorporate new ideas into a product or a portfolio or think about things that way that kind of excited me. And that was originally why I went into econometrics because the whole idea of econometrics is building models that reflect how the world works in economic terms. And that sort of really excited me. And then that slowly migrated into finance because the natural application of econometric models is modelling financial markets.
Meb: And so you guys have been managing billions in sort of these econometric models for a long time and analytic which is now a part of, I believe, Wells. What was the starting point for you? Was analytic first stop or was there some prior stops?
Harindra: There was a prior stop. So when I finished grad school, I joined a friend of mine. He had a consulting firm called Analysis Group and that was an economic consulting firm. And I was incredibly lucky because I started off doing some investment consulting. And one of the first big projects I did was helping a very large brokerage firm pick the managers that went into their SMA, you know what’s called the SMA back then, it was called the rep program. And as a relatively young person, I got to visit literally hundreds of different investment firms, some were boutique and some were very large, some were fundamentally oriented, some were quant, some were fundamental.
And it was in that journey that I sort of realised that often when you looked at a group of managers, so for example, you looked at value managers generically, at a particular time, you would visit all the ones that were doing well as part of the search and then you’d notice a commonality in the investment process. So in the early ’80s, all the value managers that were doing well were anybody who had a yield focus or equity income focus. And that’s what got me thinking too, “Well, is it the manager or is it the factor that they loaded up on?” So that was my first start actually into thinking about investing and modelling what’s going on in markets from our econometric or factor standpoint.
Meb: You probably spent more time, and I actually remember reading some of your academic work, pre-financial crisis. I might even have it saved in my desk somewhere. You’ve written a lot of papers on SSRN. Most of the focus tends to be around this concept of factors. Maybe give the listeners who may not be as familiar with markets in history just a little overview of how you think about factors, what that means to you. And then we’ll start to drill down and some more applications and questions and ideas.
Harindra: That is anything that can help explain return. For example, you can look at stocks with high dividend yield versus low dividend yield and say, “Hey, this is interesting because this is the factor that helps explain why in certain environments certain stocks beat other stocks.” For example, look at how sensitive a stock is to interest rates. And there are some stocks that are very sensitive to interest rates and others that are not. So that’s a way of looking at a stock and saying, “Hey, this factor, this characteristic explains why one stock is different than another.” So in a very crude way, you can think about a factor as just being a characteristic.
So if somebody came to you and said, “Hey, how much is this house?” You know, your first question is, “How big is it? How many bedrooms does it have? How many bathrooms does it have?” And so on. So you have a series of questions that basically ask you…the individual the characteristics of the house and then based on that and the zip code, you can come up with a pretty good guess of what the house is going to be worth. And then you can ask more detailed questions like, “Does it have lead paint? Does it have asbestos in the insulation?” And all these things kind of help you analyse why a house is worth more or less than others. So just like that, you can do that for a house, you can do that for a stock. And what you notice is when you start putting stocks together in baskets of portfolios, often the characteristics will dominate the individual stock stories.
Meb: I was smiling or frowning, I’m not sure which as you’re describing that because here in the beach, that is, the black mold and termites would be the use case that I was thinking about which, when we had them last year, it certainly made me a little happier that I’m a renter and not an owner of this place.
Harindra: That’s a great example, right? Because Southern California, especially termites is a very relevant factor in how you price a house. If you’re buying a house in Europe, in Germany, it’s a relevant factor. The importance of a factor will vary based on the geography often. And when you’re looking at a global portfolio, it’s really important to think about what factors can be important globally versus ones that are relevant locally.
Meb: So you mentioned one in kind of the beginning of the discussion being simply yield, which is probably one that most investors are intimately familiar with, dividend yield, certainly. What are some main factors? Most people will probably be familiar with the French-Fama sort of framework, but what are some of the most popular factors that you think of and then we can start to drill down on your favourites too?
Harindra: I would put them into kind of broad groups. So you have a set of factors and you can think of measures of valuation so things like P/E, price to book, price to cash flow, trailing P/E. You can have measures of growth, things like the asset growth of the company, the growth in the market cap or the growth in sales are particularly kind of some of the more commonly used ones. You can have measures of financial risk. For example, the debt to equity ratio of the company, beta of the company in terms of the beta of the equity portfolio, the riskiness of the debt, the risk group. It can have technical factors. You know, has the stuff done well over the last year or the last three months? Are the returns to the company skewed? In other words, does the company have a big chance of a big positive return?
So some other… Cruise lines, for example, right now have very skewed returns. They have a big chance of a very big positive return. So you have technical factors like that. And then you have measures of profitability. Things like ROA and ROE and operating margin. I like to think of things in terms of groups, but within a group things do vary a lot based on the business cycle.
Meb: How does one go about putting these factors together? Being not just a researcher, but a practitioner for many years in this world, how do you think about putting together a portfolio? And we can start with long only and maybe then move on to long/short, but for long only investors, say, I want to get away from market cap weighting, how should you think about putting together kind of the ideal combination of factors?
Harindra: So the first thing you need to do is come up with a way to rank all the stocks in your universe, right? So say you start off with S&P 500. So you have 500 stocks and you need to rank them. In order to do that you first need to go out and basically collect the fundamental data for each of those 500 stocks. So just suppose you have access to Value Line or Morningstar or something like that, and I would…obviously we use Compustat and other institutional sources, but there’s a variety of other sources available. For each stock, go on and collect maybe 30 or 40 different characteristics that reflect the company in terms of its profitability, its growth, its valuation, and its risk.
So once you have the fundamental data for each company, the next thing you need to do is assign a weight to each one of those. So think about 30 different characteristics. And you could, just as an example, rank each company from on a scale of 1 to 100 in terms of where they are in the distribution, and then assign a weight to each of the characteristics and then come up with a score. And that score would be relative to others. The trick with it is how do you come up with the weights? I mean, what’s changed in the last 30 years or the last 40 years is it used to be that you’d have to do a lot of work to get at the data on each company. And now the data is free. And the trick is coming up with the weights. And I think that’s where if you go back even to the writings of Ben Graham, he says the role of [inaudible 00:13:59] is to actually assign the weights to the different pieces of information you collect. And I think that’s what distinguishes or differentiates one manager from another.
Meb: So what’s the secret sauce there, Harindra? You got to tell us. Maybe not give us the recipe but how do you think about the weighting? I’ve seen you mentioned a few things in passing and other times whether it’s the sort of debate between factor timing or factors throughout different regimes or cycles. But also you alluded to the fact that all the PhDs and CFAs have many of the same tools today. So how do you sort of put the puzzle pieces together?
Harindra: I can kind of tell you personally for myself, my set of beliefs so let’s first talk about that. So my set of beliefs is that what works changes. So the factors, the market rewards changes over time. And basically what you have is that factors get rewarded or this factor persistence up to about a three-year horizon. So if a factor has been working well over the last year, over the last month, you need to give it a higher than average weight. And if it hasn’t been working well, if it’s had negative returns for the last three years, you need to give it less weight. So, for example, if you were to take price to book as a factor in the U.S., it’s worked very negatively over the last three years so I would give it a very small weight.
Whereas asset growth as a factor has worked quite well or growth generally has worked quite well so it would get a higher than average weight. The whole idea is to look back at the recent environment, ask yourself if it’s relevant to what’s going to happen going forward and then assign the weights accordingly. And I’m a big believer in using something systematic that recognises that investors are constantly responding to changes in the market environment and using recent factor payoffs to forecast the future.
Meb: What do you think is accomplished there? Do you think it’s picking up a little bit of momentum of the underlying markets? Or do you think it is picking up the regime of the economic cycle as to what’s working? What’s the general theory do you think on why that’s a good idea versus just sort of a static approach?
Harindra: My personal belief is that what’s going on is you’re capturing changes in investor preferences. And that may be due to a change in the market environment caused by the business cycle or just investor risk aversion. You know, for example, as we’ve gone through this year, if you started this year, nobody was paying attention to the leverage ratio of companies. I mean, that was a factor that was completely ignored until March came around. And as of March, everybody realised that it’s not only the leverage ratio, but the cash on hand that’s a really, really big factor in the survivability of this company. So this is a fact that that came to favor very, very quickly.
For [inaudible 00:17:08] factors, you look at it and say, “Yeah, this is important. And it makes sense given the current environment.” You know, it’s very unusual to get that to be important in a falling rate environment. Usually when rates are falling, that means, hey, that’s cheap, you can load up on that. So what was really unusual about what happened this year is that debt to equity became important given the change in the economic environment. And it’s hard to tease out whether that’s caused by risk aversion or changes in investor preferences or just the feel of the economic environment. I think it’s a combination of all three. There’s some…a little bit of animal spirits but there’s also a lot of economics going on there.
Meb: You mentioned in reference to price to book one of the old school factors that many firms and strategies have as their foundation going back certainly to a lot of the work that dimensional has done, but even before that, we mentioned French-Fama and then even Ben Graham. How do you guys think about factors evolution over time? I mean, there’s some people that put out papers that say, “Look, you shouldn’t be using price to book because the world’s changed and it looks different than it did 10, 20, 30, 40, 50 years ago.” Are there times when factors totally fall out of the toolkit and replaced by others? And how do you make that determination that it’s just out of favor versus broken?
Harindra: Yeah, I think it’s purely to me an empirical question. So if we take price to book and you say, “Isn’t that an irrelevant factor?” It’s easy to test that. All you have to do is in econometric speak, run a regression of returns for a given month for 1,000 stocks and price to book and say, ask yourself, “Is price to book useful in explaining these returns?” And the answer unambiguously is yes. Its power may have fallen over the last eight years but it’s not zero. And what happens is factors come in and out of favor. I mean, just think about 10 years ago when everybody was talking about buyback yield. The general view was dividend yield didn’t matter. It’s all about buyback yield. In other words, you’ve got to look at stock repurchases.
So there’s always a reason to ignore a factor. So my recommendation to investors is just think of a factor that hasn’t been working for three years. Don’t ignore it. Continue to evaluate it. And if it starts being important again, there’s a huge advantage to being one of the first people to notice it. Adjust your portfolio accordingly because as more and more people start to notice it and respond to it, you’ll be rewarded for the early adoption.
Meb: You have another paper coming out talking about optimal combination of factors where you’re talking about at the beginning of this decade, 2020, factor investing in the public equity markets has fallen on hard times, performance failures by a number of prominent quantitative portfolio management firms has been attributed poor implementation of multi-factor strategies as well as lower negative returns to popular factors like value and size. What do you sort of think about the state of factor investing? Today market cap has stomped most everyone out there. A lot of the growth these sort of concepts have just run roughshod all over many active managers. What’s your general just lay of the land of factor world here in 2020?
Harindra: I guess I’d agree with the statement that factor investing has been a huge disappointment from an investor standpoint. I think the expectation was probably unrealistic.
Meb: You guys have long used the short side of the toolkit. How do you guys think about that implementation? Because for most investors shorting is challenging, esoteric, difficult, whatever you want to put under the heading. It’s fraught with behavioural problems, execution, operational issues. How do you guys apply it? Do you just flip the ranking model and say, “Take the worst rank,” or do you do a totally different approach? Do you even out the numbers of shorts on a gross level? Kind of what’s your general thought of how the shorting fits in?
Harindra: So generically, we don’t do anything different. You just short the boring stocks. And if we look at any historical academic or practitioner study, you’ll see there’s a lot of value to be added from the short side. So that part’s easy. The difficult part really is that there’s three very difficult components. One is the risk management component in that it’s really kind of a…there’s a big behavioural effect. And if I can take a few minutes and explain it. So when you buy a stock, if you’re wrong, the stock doesn’t appreciate by as much as the other stocks in your portfolio or your client portfolio. So your mistake is kind of self-correcting in that your position is getting smaller as your mistake gets worse and worse. So you don’t have to step up and admit that you make a mistake and correct it. With shorting the reverse happens.
If you short a stock and it starts going up, you need to admit that you made a mistake and resize your position accordingly. So the risk management component of shorting is really, really critical. And it needs to be, in my view, something that’s automated in terms of establishing a maximum position size for every position and then rebalancing the portfolio daily or even more frequently than that for very active stocks so that you don’t have too large a position. So that’s the first thing that’s really, really difficult about shorting. The second thing that’s difficult about shorting is that distribution of returns is asymmetric. Stocks will never go down by more than 100% but they can go up by more than 100%.
So your short book needs to have smaller positions and be way more diversified. And the third thing about shorting people kind of often don’t take into account is when you short, there is a cost of borrowing the stock because you basically borrow the stock. You don’t physically have to go out and borrow it. Usually the broker will do that for you. But you do pay the cost of the borrow. And there are certain stocks like Tesla, for example, which are very, very expensive to borrow. And so you need to figure that out to say, “Okay, I’m going to pay 6% a year or 20% a year in a bad case to borrow this stock. So do I think it’s going to decrease by more than that?” So capturing that component is important, but not as critical as the first two.
Meb: And what’s the general approach when you look at a portfolio? I know you guys have done sort of one of the pioneers but also market neutral. Like what’s the general kind of summaries of ways do you think this is a useful addition to a portfolio and exactly how?
Harindra: So I think shorting is a wonderful way to control risk in the portfolio. And I think the best way to manage it or to use it is not in a market neutral way but very much in a long/short framework. So very much if you look at the history of the guy who came up with the first hedge fund, which was A.W. Jones, his idea was, “Look, if I short stocks that are going to go down, I’m going to reduce the risk profile of the portfolio and I’m going to add value.” So I think a long/short framework is the best way to do it. What you need to do is identify shorts that are going to do worse than the rest of your portfolio. So shorts that are expensive, stocks that have maybe high levels of risk in terms of their beta or high potential for bankruptcy, or just use the shorts to bring the risk down to the level that you want.
And so just to kind of give you a concrete example, you have two options. Consider someone who’s looking for a conservative portfolio right now, they might put 60% in stocks and 40% in cash. And so you’d bet 60% in the S&P SPDR and 40% in cash. The alternative to that is to put $100 in stocks in a long portfolio that you like and then short 40% of stocks you don’t like. Both those have the same asset mix. They’re both 60% equity. But this long/short portfolio has a much greater potential for return because the short book should underperform the long book. So that, to me is the advantage of using a long/short approach, which is just an asset mix approach. So to me the best application of shorting is to actually accomplish both goals, which is adjust your asset mix as well as reduce risk in the portfolio without reducing the return.
Meb: As you think about this approach. You know, the U.S. is obviously the world’s largest capital market, but half the world’s market cap is also outside of our shores. How do you guys think about global investing? Is there any major differences you have to account for structurally? Are there any other approaches that you guys take into account or is it sort of a carbon copy of what you guys do in the U.S.?
Harindra: There’s a lot of commonality, Meb, but there are some important regional differences. So for example, in the Japanese market, it’s quite difficult to short stocks for domestic investors. So you do have an advantage as a non-U.S. investor to go out and short. Borrowing stocks that are part of a major index like MSCI World is quite easy. So when you’re shorting it’s important to make sure that the stock is well represented in the indices that are commonly used to index those funds because then you can go out and borrow that stock and use it to short. Some of these countries have peculiarities is probably the best way to describe it. So for example, in Japan, there are some airline stocks where as part of owning the stock, if you are a long-term holder of the stock, you get coupons from the company for airline tickets.
So when you short the stock, just as an example, you have to reimburse the owner of the stock for those airline tickets. You know, that kind of thing doesn’t happen in the U.S., but those are all things you need to worry about when you’re shorting kind of around the world, that each country has its own little idiosyncrasies. And there are other countries like where I’m from with like Sri Lanka or India where it’s actually virtually impossible to short. So some countries it’s very hard to do, in other countries it’s quite easy. So there are a lot of peculiarities in each market that one needs to be aware of.
The most important thing if you are shorting globally, my view is that shocks to countries happen on a country by country or regional basis. So from a risk management standpoint, it’s really important to manage country exposure. So it’s a bad idea to be long U.S. and short on Japan and not be aware of the relative size of the trade because if there’s a shock in one country versus another, you’re exposed to country selection as a huge factor. And what they’re trying to do in these portfolios is exploit stock specific risks, not country risks.
Meb: How has factor investing changed for you over the past, say, 10, 20 years? We’ve had quite a few different market events with the dotcom crash and global financial crisis and pretty quick this decade of pandemic. Is there any things you’ve certainly changed your opinion on or you approach differently that you had over the past 10 or 20 years? And one of the ones I’m thinking about as you’re talking about globalisation, countries with various domicile may or may not be as relevant or sector to a stock that may get revenue from anywhere in the world today. Anyway, any general thoughts over the past 10, 20 years?
Harindra: I’m not sure I can think back to 20 years.
Meb: Too much car racing. But anything you’ve changed your mind on?
Harindra: The Alzheimer’s hasn’t set in yet. But it’s been a huge change. When I think back to 25 years when I first started at Analytic, I think the whole idea that you could tilt to a factor and add value was not common. I mean, I would go in and talk to consultants and potential clients, and they’d kind of give me this quizzical look. We’ve gone from that to an environment where I would say five years ago when everybody started using the word smart data, the dominant belief was, “Look, you don’t need active management, you can just build a portfolio with these passive tilts and that’s going to add value.”
So I would say there’s been a huge change in the way people view factors as an acceptance that they’re important in driving returns. And there was almost an oversimplification as to how important it is to actually have some experience in the way they’re put together. So just because they go out and buy Thomas Keller’s cookbook on The French Laundry doesn’t mean I can cook like him. I can buy the same ingredients but it still doesn’t work. I draw the analogy between factor investing and California winemaking where in France, the winemaking is surrounded by all this mystery and in Californian wines there’s a sense that, yeah, here’s an easy way. If you want oak do this, if you want a buttery shot, then they do this. There’s all these formulas that you can use but there’s still an art to how you put it together.
And I think somewhere we kind of lost the idea that, yeah, there is an art on how you put this together and it’s not purely formulaic. So that to me is kind of the evolution of factor investing or investing in general over the last 25 years. The big takeaway for me for versus when I started 25 years ago was how long the famine or the fact of famines last. I think about dotcom bubble and how much value got pummeled in that time frame, I think about some of the crashes in momentum and it seems like everybody seems to forget that a factor doesn’t work for a long time and then it works really suddenly which is why you need to have consistent exposure to it.
Meb: You mentioned chatting with institutional investors. How has sort of their thoughts on factor investing…and this can apply to investors of all stripes, but from someone who’s interfaced with real money institutions for a long time, how has their mindset changed around the factor portfolios and many of the approaches that you guys employ, more receptive, less receptive, confused, disinterested? How are they thinking about it?
Harindra: Yeah, I would characterise them being as a lot more interested and a lot less willing to pay for something that they can get cheaply. So 25 years ago, you could go to someone with a three-factor tilt and say, “Look, I have this database, here’s the tilt. I’ll charge you just as a rough number for a large institutional mandate, 15 basis points for it.” And that 15 basis points is now 3.
Meb: We’ve long been saying that this barbell of market cap weighted exposures that essentially are free, and you mentioned short lending probably even have a negative expense ratio for some of these, that if you’re going to do moving away from market cap weighting and still pay more, then you need to be concentrated exposure to some of these ideas. Otherwise, like you said, people will just pay zero. Here we are in 2020. It’s the start of the new decade in a year. It feels like an entire decade has already transpired in six months. What are your thoughts on current markets, if you have any? We find ourselves in a world that looks a lot different than what they taught us in university and probably in the CFA curriculum. We’re in a world of negative sovereign interest rates at one point this year, crude oil futures are trading negative, all the stuff going on. Any general thoughts on the state of current markets in 2020?
Harindra: Some things are similar in that the level of uncertainty is maybe higher than it has been historically, but it’s not unusual. I think there’s still the same concerns about which factors work and which don’t. I think what’s unusual about the current environment from a risk standpoint is how quickly risks migrated. So if you think about the start of this year, you had…I’d kind of give you an example even though I don’t like using stock examples. If you compare Netflix and Disney, these are two companies that are kind of in the same industry. One of them has a very diversified revenue source and has been around for a long time, that’s Disney. And the other one is relatively new and has a very undiversified revenue source. But in the current drawdown, the more mature company was the one that turned out to be more risky. The perceived risk of companies has changed very, very dramatically.
So I think in the current environment, it’s really, really important to be aware of where risk is migrating to and what the risk you’re taking in the portfolio and how that risk is going to manifest in your portfolio because it’s very different than it was a year ago. I mean, a year ago if you look at country factors, you mentioned earlier this domicile matter, I would say a year ago, domicile didn’t matter. But now domicile really matters because the country in which you operate and its policies towards the virus are going to have a dramatic impact on your ability to operate as a company. So I think it’s a wonderful time for active managers. It’s a great time for somebody who’s willing to look at the portfolio and say, “Look, what’s changed in the world? Am I willing to migrate in a way that reflects it?” So I think from that standpoint, it’s a very exciting environment to be involved in active management because the risks that are slowly coming out are much different than have existed in the last 5 or 10 years.
Meb: What are some of the best practices that you recommend to investors when applying a approach that involves factor investing and active management? And this can apply to individual, institution, anything like…and within that same question as best practices, what are the some of the main mistakes that you see you just got to avoid?
Harindra: The most common mistakes are all fitting. So people will always look at factors and say, “Look at this factor return and I can get this factor return historically.” And what they don’t seem to realise is they’ve looked at 100 factors and found some combination of 2 that work really well and they believe that’s going to provide them with a great return going forward. So that’s a very common mistake. So avoiding kind of loading up on one or two factors I think is a really good thing to do.
The second thing is, from our investment standpoint, be careful about how much factor exposure you build in your portfolios because every factor exposure involves some risk. And the best way to think about it is to almost use a risk parity approach where you allocate a certain amount of risk to each factor and then rebalance frequently. So that’s very important, the rebalancing component. And along with the rebalancing, the third thing that’s important is to measure factor exposure on an ongoing and consistent basis. So don’t just build a portfolio or don’t look for a process that builds a portfolio and leaves it alone and…because the exposures can change really, really dramatically.
So for example, there are some ETFs out there that are…call themselves low volatility ETFs but they only rebalance once or twice a year. So when we had this shock in March, these portfolios didn’t rebalance. And these ETFs if you look at their trailing volatility over the last 30 days, they’re actually higher than the market even though the word low volatility is especially highlighted in the name of the ETF. And that’s because by design, they only rebalance twice a year. And they weren’t built for an environment where the shock arrived so sharply and so suddenly. Somebody who was factor investing needs to be aware of the fact that if there’s a shock all the exposures in your portfolio likely changed. And you need to be looking at your portfolio. And just because your ETF says it’s low volatility value doesn’t mean it’s low volatility value if it wasn’t rebalanced to reflect the shock.
Meb: The construction as well as the implementation is super important. A lot of investors, same as consuming the news today, they just sort of read the headline, read the name of the fund and accept it for what it is but you really have to dig down, not just through the fact sheet but prospectus to see what these funds are doing. We talk a lot about some of these really, really large factor funds. And God bless them, I love Vanguard’s, you look at some of these that are $20 billion, $30 billion, $40 billion, $50 billion, and then actually look at an X-ray of their portfolio and the characteristics of what the fund says it’s going to be doing is almost totally impossible with that size. And then you look at the characteristic and the factors and it turns out that it’s not at all what people think it is, but it sounds good. It’s good branding, good marketing. By the way, you also mentioned Thomas Keller, his fried chicken recipe is the single greatest fried chicken I’ve ever had in my life. So pro tip to listeners, check out that recipe.
Harindra: So, Meb, have you tried replicating it?
Meb: I have. It takes like two days. You have to brine the chicken ahead of time for like a day which I think was a bit different.
Harindra: And fundamental, right?
Meb: I think so. And I’m half Southern so he’s got a great collard green recipe too. It all went together and, man, it was awesome. Two thumbs up.
Harindra: I love the cooking analogy because I think you can use the recipe book and get close, but you won’t replicate the exact same thing.
Meb: A hundred percent. We actually did a post. I paid a couple guys in Poland to scrape all the recipes. I’m a novice chef and most of what I try turns out terrible, but I like to experiment and that’s how I learned. But I paid a couple guys in Poland to scrape all the recipes on the top 10 food sites on the internet, “The New York Times,” and I at least wanted to develop like a rating for…a consensus rating like a Rotten Tomatoes for cooking because my theory was, look, if this universally has 10,000 reviews and it’s 5 stars, it’s probably a decent recipe versus something that has 2 stars. And kind of went through a fun period where we were trying a lot of these recipes. But agreed, there’s certainly user input as well. My abilities are pretty pedestrian. You have a curious mind. You’ve been in this business for a while. You’ve written a lot of wonderful papers. We’ll add links in the show notes. What’s got you curious, interested, excited today? Anything that you’re scratching your head about or you’re thinking about or you’re writing about on your mind?
Harindra: The big thing for me right now is thinking about risks that are suddenly gonna materialise that we haven’t quite factored into our portfolios. And it seems that every decade or so there’s a new risk that shows up that we hadn’t quite thought about. So one of the things I’m looking at right now is carbon emissions. So if you look at a company, there’s three different types of emissions a company can have. One is emissions they produce. The second is emissions that are produced as part of the production process. And then the third is incidental emissions. So if we take a company, for example…I mean, suppose you’re making shoes and you’re making shoes in Norway versus Japan, just to pick two unusual countries, what’s unusual about Norway is all the electricity you use comes from hydro. In Japan, all the electricity use after the Fukushima incident, almost all of which is coal powered.
So one of the set of shoes you’re going to use is going to be very carbon intensive. The other set of…pair of shoes is not going to be carbon intensive. And as we move to a world where people start to price the carbon you produce in terms of consumers avoiding the products or governments taxing them, that’s increasingly going to be a risk factor, right? That’s going to be, just like in the U.S. we avoid lead paint in houses where 20 years, many years ago we didn’t care about it, that’s going to be the lead paint of companies and people are going to avoid companies with this kind of footprint. And the question is how do we quantify it and how do we avoid it in a systematic way in a portfolio? And I think cap weighted portfolios are particularly susceptible to this type of risk. And the current low carbon environment we’ve lived in with emissions falling off has made people even more aware to this.
So that’s something I’m really wrestling with in terms of how do you measure it and how do you quantify it and how you build it into portfolios and it’s something we at Analytic and Wells Fargo are kind of wrestling with and we hope to have it incorporated as a factor into our portfolios by the end of this year.
Meb: And it’s somewhat related, you guys have written a little bit about ESG. Any quick thoughts on that before we start to wind down?
Harindra: Yeah, ESG is increasingly kind of priced. If you look at the current prices, you’ll see companies with good employee practices have had significantly less volatility. Companies with good governance have increasingly less volatility. So we think it’s something that needs to be incorporated into portfolios. It’s something that historically has been missed. It’s not in most risk models. But ESG is very much like carbon in that it’s hard to measure. It’s clearly very, very important. But it reflects the risk that is not priced properly in terms of the way society responds to it. And what seems to happen in the market now is as soon as people stopped being aware of it, you suddenly reached a tipping point. And what was acceptable 10 years ago, people just run away from. And the risk seems to rear its head much faster than it did historically. So I think that’s why as a quant you need to be able to think about what’s going to be the next factor in terms of exposure is how do we measure it and how can we tilt our portfolios away from it so when it shows up you’ve adjusted the portfolio before it shows up?
Meb: Question we ask all of our guests, do you have a most memorable investment that you’ve made at some point in your career? It could be positive, it could be negative, it could be when you were young, it could be more recent. Anything come to mind?
Harindra: Most memorable in terms of return or most memorable in terms of kind of the experience?
Meb: Traditionally it’s the latter. And we have a pretty wide spectrum of how people respond. So it’s really just whatever is most seared in your brain that pops into your head.
Harindra: My most memorable investment centers around an old Formula One car, and it was an unusual story because it was an old Formula One car. And somebody told me that that was a replica of a Formula One car for sale. I looked at it and the first thought that went through my head was, “Why on earth would somebody build a replica of a Formula One car in 1972 because you could go buy a real one?” But it was priced like a replica. So I looked at it very closely and I didn’t want to appear too excited so I bought it. And then when I took it home and took it in the garage and I took it apart, I realised that it was not a replica, it was actually the real thing. And somewhere in the history of the car, somebody had used the word replica to describe it. It was quite a thrill in terms of discovering something about something that no one had kind of thought about and earning a pretty good return as well.
Meb: What’s the real versus replica premium? Is it like double, 50%, [crosstalk 00:46:26]
Harindra: No, no, it’s about 400%.
Meb: Wow, that’s awesome. I have the opposite experience, which is buying…I had a, you’ve probably seen in the neighborhood, a 1960s Land Cruiser which was stored rumbling around, but like many classic cars, they’re expensive to maintain. I was actually on Twitter yesterday because a buddy, Jason Calacanis, had done an episode with the corporate venture capital group at Ford, and they were talking about how there’s so many classic cars that Jason was curious why they didn’t just put those very similar models into production. You have the relaunches of Defender recently, you have the Bronco coming out in July. And so many times it’s such a subpar rendition of just the actual classic.
And so my business idea, listeners, feel free to steal it, I don’t want to do it, but I said, “I’m surprised there’s not a national resto mod brand. Meaning, hey, I want a 1960s Corvette but with better brakes, engine, etc. You have very niche ones all over the country but it seemed like an opportunity. We have the Land Cruiser version in LA called Icon but I’m a cheap bastard. I’m a value investor and so they’re way out of my price range, but it seems like an interesting business opportunity in efficiency as people particularly pined for some of the cars of their youth.
Harindra: Yeah, it is. There hasn’t been a national attempt to do it. It’s interesting that some of the manufacturers like Porsche and Mercedes…I mean, Mercedes has their Mercedes heritage centre down in Orange County where they can take a car and have it restored and have it restored but with better brakes and a better gearbox and halogen lights to make it usable. So some of the manufacturers are trying to do it. And that seems like the best way to do it. It seems like something manufacturers need to hop on. But Toyota certainly hasn’t made any attempt to exploit this loyal following of FJ users.
Meb: I know. One of the saddest when they put out their Cruiser 10 years ago, whenever it was, and it was not at all what my hopes and dreams look like. They actually put out a replica anniversary of the Land Cruiser, but only in Japan and whatever the really complicated, convoluted import laws are, you couldn’t import that particular model. So, anyway, I have a three-year-old now. Like I can’t drive half these cars anyway if I wanted to so I’ll probably be shopping for a minivan soon. Harindra, this was a lot of fun. Where do people find more info about what you’re up to, you’re writing, what’s going on with all your professional world? Where do they go?
Harindra: Well, you can find more about me if you just Google my name, it’ll show up as part of the Wells Fargo asset management team or on SSRN. Everything I do is on SSRN from a purely research standpoint, and that’s probably the best place for the more academic-oriented papers.
Meb: Awesome. Harindra, thanks so much for joining us today.
Harindra: You’re welcome, Meb. Thank you.
Meb: Podcast listeners, we’ll post show notes to today’s conversation at mebfaber.com/podcast. If you love the show, if you hate it, shoot us feedback@mebfabershow.com. We’d love to read the reviews. Please review us on iTunes and subscribe to the show anywhere good podcasts are found. My current favourite is Breaker. Thanks for listening, friends, and good investing.
