“I wasn’t as interested in finance originally, just because I didn’t understand how important finance was for the world.” – Kathryn Kaminski (Tweet)
Our next guest is different than any guest we’ve had before, as she is not a fund manager but has spent much of her life’s work researching and writing about the topic of trend following. She is a true thought leader in the managed futures industry and you’ll learn a lot from the animated discussion we have regarding the history of trend following and how she co-authored her latest book on the subject.
Thank you for listening and please welcome our next guest, Kathryn Kaminski.
In This Episode, You’ll Learn:
- About Kathryn’s upbringing in Nashville, Tennessee.
- About her time at MIT where she went for electrical engineering.
“Everything started for me with my severe interest in mathematics.” – Kathryn Kaminski (Tweet)
- How her internship at a bank in France got her on the path to work in the financial industry.
- About her teaching financial engineering with Andrew Lo.
- Through her teaching and research, she became interested in technical analysis and trend following.
- How Kathryn went to the Stockholm School of Economics.
- When she left academia and joined RPM in Sweden.
“You meet all the CTAs and get to hear their stories, and you get to analyze what they do from the outside.” – Kathryn Kaminski (Tweet)
- How she met Alex Greyserman and how she came to write a book with him.
- The history of trend following as she lays it out in her book.
“Most investors would like to have an all-inclusive, objective guide to trend following.” – Kathryn Kaminski (Tweet)
- How trend following at its core is quite simple.
“The art of trend following is what makes one manager different from another.” – Kathryn Kaminski (Tweet)
- What Kathryn likes to do outside of work.
- Her work life balance and her life in Sweden.
- Her view on the building blocks of trend following.
- Her quest for acceptance of trend following in the academic community.
- Where the term Crisis Alpha came from and what it is.
- About Convergent and Divergent strategies.
“Trend following is just a systematic example of a divergent risk-taking strategy.” – Kathryn Kaminski (Tweet)
- About the Adaptive Market Hypothesis that she writes about in the book.
- What the CTA Smile is and what it really means.
- What she would look for when building or critiquing a research team.
Resources & Links Mentioned in this Episode:
- Kathryn’s book is: Trend Following with Managed Futures.
- Learn more about Andrew Lo and MIT.
- The 3 building blocks of trend following that Kathryn mentions:
- History + Data
This episode was sponsored by Swiss Financial Services:
Connect with The Institute for Financial Research, Stockholm (SIFR):
Visit the Website: www.sifr.org
Call SIFR: +46-8-736 91 01
Follow Kathryn Kaminski on Linkedin
“As we continue to tell the story of trend following in an objective, constructive and non-biased way, then more people will understand, and hopefully smile.” – Kathryn Kaminski (Tweet)
Katy: I'm very friendly, and a very approachable person, but I actually used to play college hockey - so women's ice hockey. So whenever I'm in tough situations, and I've got that smile on my face, I'm just thinking about, "Katy, put the helmet on." So I tell myself to put my hockey helmet on and then I get in that zone. I played hockey in college as a previous figure skater, so I'm very eloquent, but I have a tough edge to me as well, so that's what most people don't know.
Niels: So sometimes we meet people who appear to us in one way, but once we get to know them, they are, in fact, very different. Someone who, when allowed, goes into their creative cave, spending months, if not years pursuing their quest, only to emerge with the work of genius that may change the way that the world perceives a particular subject. Well, that is what we are talking about in today's episode of Top Traders Unplugged.
Introduction: Imagine spending an hour with the world's greatest traders. Imagine learning from their experiences, their successes, and their failures - imagine no more. Welcome to Top Traders Unplugged. The place where you can learn from the best hedge fund managers in the world so you can take your manager due diligence or investment career to the next level. Here's your host, veteran hedge fund manager Niels Kaastrup-Larsen.
Niels: Welcome to Top Traders Unplugged, where my goal is to give you the clarity, confidence and courage you need to invest like, or invest with one of the top traders in the world. It is the stories that you never get to hear, set out as the most honest and transparent account that I can make of what goes on inside the minds of some of the best investors in the world delivered to you via a one-on-one conversation.
Today you are listening to episode 41. If this is the first episode you've heard, you might want to go back and listen to all the other conversations. On today's show, I'm talking to Kathryn Kaminski, but instead of me doing the introduction why don't I let her do it. Katy: Either I work in finance, and maybe I'll say hedge funds after that; otherwise I tend to say I teach finance. But if people ask more specific questions about trend following or hedge funds, I say, "well I work in systematic trading and systematic investing. Niels: Thanks for doing that Katy, and by the way, if you want to read the full transcript of today's episode, just visit the Top Traders Unplugged website where you can find great details from today's conversation. Now let's get started with part one of my conversation, I hope you will enjoy it. Katy, thank you so much for being with us today. I really appreciate your time.
Katy: Nice to be here, Niels.
Niels: Good. Now Katy, you're a bit different from my usual guests which so far have been hedge fund managers or CTAs running their own firms and strategies, but I think that you bring such an important perspective on the systematic trading world in general, and the managed futures industry in particular, that I wanted to make an exception to my usual lineup and bring you on for an in-depth conversation on a number of topics relating to this. Now people in the alternative investment industry are very familiar with you and your work, but before we get into your story, I wanted to ask you a slightly different question, a question that I believe a lot of people in our industry find difficult to answer, including myself. So it goes something like this: imagine you are invited to a cocktail party with people who don't know you and after a few minutes someone will come up to you and ask, "so Katy, tell me what you do?" How do you respond to that? How do you explain what you do?
Katy: Well, to be honest, I usually just smile and say, well, either I work in finance, and maybe I'll say hedge funds after that; otherwise I tend to say I teach finance. But if people ask more specific questions about trend following or hedge funds, I say, "well I work in systematic trading and systematic investing and what this means is that it's just a process which systematically allocates investments across a broad spectrum of different types of investments in the financial markets."
Niels: Sure, fantastic, well let's stay with you for a little while longer because what I'd like you to do is to tell me your story. How you got into this field in the first place, and perhaps a little bit about what you were like as a little girl growing up and feel free to go back as far as you want.
Katy: Well I actually came originally from Nashville, Tennessee, and I would say everything started for me with my severe interest in mathematics. I, for some reason, had always loved math, and I spent... and I still do math puzzles before I go to sleep, so it's kind of a geeky thing. Back in high school in Tennessee I was such a fan of math that the only place in the world that I wanted to go was MIT. So I moved up to Boston and started as an undergraduate at MIT studying Electrical Engineering. When I was doing Electrical Engineering, I got interested in signal processing and sort of cell phones, and how do all the electronics that we have work? I thought it was so fascinating to understand how to build your own MP3 player, or how does a cell phone work, and how does it work down to the last circuit? So that was my original passion was actually in Electrical Engineering. I spent some time working with Qualcomm and other firms and also studying in France. After that, I wasn't as interested in finance originally, just because I don't think I had the... I didn't understand how important finance was for the world, and how much it impacted the industry, and how prevalent it was and how it was the force that drives our entire commerce globally. But then, as I got into graduate school, I still liked math so much I didn't even want to leave MIT. I wanted to stay there forever. I decided to do a doctoral degree in operations research, which is basically math applied to everything practical. I did my first internship in finance actually, and I decided to do it in France for a French Bank because I thought, well if it's in French too that's even more exciting. So I worked on a quant team in France in a credit risk group, and we coded in French and it was very exciting, and I just fell in love with finance. I thought, "this is exciting, this is so fun, this is so"... to be honest I had very little finance experience. They just gave me the books and said here's an “obligation” [bond], and I said, "OK, that sounds good. What are the cash flows?" And I just looked at the math models and programmed them in and I later…it was more hybrid capital, and subordinated debt modeling and, if you'd asked me that before I walked into that job, I had no idea what it was.
Niels: Sure, I think most people feel that way still.
Katy: Still probably, yeah. I worked at Societe Generale that summer and after that decided that I still wanted to do math, but I wanted to work in the area of finance and math. Then I got this fantastic opportunity to meet Andrew Lo, who is definitely a quantitative finance guru at MIT and in the meeting he asked me, he said, "do you want to teach Financial Engineering?" And I said, "Yes, of course!" So that's how we actually ended up working together, is that he asked me to help him teach a financial engineering class and then I ended up teaching with him for about five years and doing research with him at MIT. He and I worked on the topic of financial heuristics, and most of my thesis was about stopping rules and understanding heuristics that investors use and practice. To be honest, these days that's a very popular topic, but fifteen years ago it was sort of a little bit taboo because it wasn't what would be published in a top journal. But after spending some time working also for a hedge fund, and working for a bank, I just knew that this was what people do, so granted it wasn't the best alignment for the perfect... for academia, but now, these days, I actually find that heuristics and systematic rules is actually a very big field in finance, although fifteen years ago it was not, or ten years ago it was less popular in the academic community. So that's when I first got interested in things like technical analysis and trend following and that was more an interest in heuristics in general. Then, after finishing my thesis and my thesis was on stopping rules, which also was very applied in the trend following industry. Then I went to the Stockholm School of Economics. I was working at the Stockholm School of Economics and after about a year I decided to go work in the industry. The academic job work was a great experience, and I enjoyed working at the Stockholm School of Economics, but I wanted to get my hands a little dirtier. So I left academia partway; still taught and visited the school often, but I joined a Swedish Fund the Funds, which works in CTAs. So the fund is RPM. It's a well-known Fund the Funds who you know very well, as well. The great thing that I loved about being at RPM was that if you're in a CTA Fund the Funds, you meet all the CTAs. You meet the Winton’s, the Campbell’s... every single manager out there you get to meet and you get to hear their story and you get to analyze what they do from the outside. Given that perspective, you can sort of learn a lot about both what the CTAs are doing, but also we spent a lot of time the Fund the Funds business talking to the pension funds, and talking to institutional investors, and trying to answer the questions for them, because they expect us to know all the different managers and to know all the different strategies and how they are put together. So that was a really great experience to move into the CTA world. Following that I did a startup and was doing some research, and I ended up back in academia. That was sort of an unexpected move and decided to go back to doing research on managed futures. Then in the summer - I think it was at some point back, I knew of ISAM because I had done due diligence on them, and I knew several different people from their team, and I had never met Alex Greyserman before, but I had a friend named Randy Warsager from CME who's a good friend of mine who would send me articles whenever he thought that would make me very excited, because I love the research on CTAs. So he sent me articles from Alex. Alex had been writing about crisis alpha, which is something that I spent a lot of time doing research on. When I read his articles, I decided to go and visit him. Yeah, I know, it was kind of a funny random. I was at MIT visiting Andrew Lo, and I hoped on a train and I went down to New York and had a meeting with Alex with the intention to write a paper on CTAs. On the way down there, after a few minutes of talking to Alex, and Alex is... for anyone who knows Alex, he knows so much about this industry and he's a veteran of implementation - of trend following strategies and after just a few minutes of talking to him I kind of said, "we shouldn't write a paper, we need to write the book, Alex." And we kind of looked at each other across the table and said, "sure, let's do it!" It really sort of happened exactly like that. There was no premeditation. It was just there on the table and we said, alright, because we're on different continents, so what we would do is occasionally meet up in London or New York, when possible, and besides that we would basically talk on the phone regularly and catch up. I spent a lot of time talking on the phone here is Scandinavia, late at night, or early in the morning, his time. That's how the book came about. The point of the book for our sake is that I was always really frustrated with the fact that academics...that academia in general had somewhat ignored the field of trend following as a sort of viable strategy until very recently - about 2012 in the work of AQR and Peterson and his co-authors, and I felt, after talking with so many investors that there's tons of white papers out there, but most investors would...especially the sophisticated investors would really enjoy having an all-inclusive objective guide to trend following. Alex and I, given that we both have an academic side of us, felt that this was a good way to come about this project.
Niels: It's extraordinary. That story in itself is extraordinary that you, more or less on your first meeting decide to write what may turn out to be the definitive work on managed futures and trend following. It just shows that life is sometimes very unpredictable and fascinating. As I said, it's fascinating to hear that and how it came about, and stories are important. I think that it was Lady Thatcher that once said that if we don't understand history, we might be condemned to repeat the mistakes. So why don't you take the stage now and tell us the history of trend following? Obviously based on the research and the studies you and Alex did, in writing the book, and maybe I should just clarify that the book is Trend Following with Managed Futures: The Search for Crisis Alpha.
Katy: Yeah, I think if I go back, for just a second, this concept of trend following is something that has been passed on throughout the ages. I think we start our book by saying find a trend and follow it, is a common adage that has been passed on throughout the centuries. This is quite, sort of, one of the points that we begin the book with, is that people have been using and following the curve, following the crowd for as long as anybody ever has imagined. Essentially trend following is simply following a trend that you may see. If you look across history, this particular approach, if done the right way, can actually be very stable over time. That's what we see in the beginning of the book, is there's an 800 year analysis. Granted that any of these analysis are not empirically hardcore research, but they give us some perspective on, "wait a minute, is this something that I could have done throughout the ages?" I think if you take that, and you think about what trend following is about: trend following is about following something that looks like it's going up and cutting your losses when you think it's not. It's very simple. Granted the way that we do it today is much more sophisticated, and much more systematic and sophisticated, but the concept is really simple.
Niels: Sure. I think that, in a sense, that's quite interesting to me because I think sometimes managers over complicate the message of trend following because they want to sound like that what they do is really sophisticated, but in reality it's not that hard.
Katy: Definitely not. I think I spent a lot of my research time thinking about stop loss, and why do people use stopping rules, for example? There's a lot of behavioral reasons for this, and trend following is exactly the same. You create some systematic rules to help you control your behavior - to help you make decisions. So for something like stop loss, as an example, we use a stop loss because we know that we may not be able to get ourselves to stop the loss without making the decision a priority. Trend following strategies, and the concept of trend following is about creating a simple set of rules - a simple heuristic for how do you actually profit from moves - up or down? If they exist, how do you handle them? So when we started our book, actually, one of the interesting graphs... the first graph that we have is actually performance of the S&P 500 for the last twenty odd years, and then performance of trend following. If you just look at that graph, there clearly are trends. Long trends that exist in history and different markets. So if we have that approach, there may be some ways to develop heuristics to help us to handle the ups and the downs over time.
Niels: I want to try and stay with the theme of the history and trend following and just ask you how did you find evidence of trend following taking place going back so many years? We obviously, many of us remember the last five, ten, twenty years, but once you get past that and for most investors we're not in the markets fifty years ago, or a hundred years ago, how did you observe or identify signs of trend following back then?
Katy: Well I think in the beginning... the beginning of our books starts with an 800 years analysis. That data... you have to think of it as an abstraction. Imagine that 200 years ago that you're sitting there, looking at prices for rice, or lean hogs, there's clearly maybe dealers that are selling these particular prices, so you have to abstract that the historical record that we have of those prices represents an aggregate view of how those markets behaved over history. If you see it that way, then you take this abstraction with the idea that, "what if I was the type of person that just said, if I see things that are going up in the last 12 months, I buy. If I see things are going down, I sell if I can." Do that simple thought analysis, not complicated rules, but basically just looking at history - 12 months buy, or sell. You do that over history, equal weighted, and then we examine how that performs, and the performance is relatively stable. Intuitive to me was what you see with modern day trend following, but modern day trend following is obviously much more sophisticated, but the concept is exactly the same.
Niels: Yeah. I think also you.. am I right in saying that you found, actually, some quotes from some, I don't know what it was, was it a politician or something like that who actually used words that I think we use now-a-days in describing trend following?
Katy: Yes. This quote is from David Ricardo, who was a legendary political economist, and this is sourced from a book called The Great Metropolis, in 1838. He said, "cut short your losses, and let your profits run on."
Niels: Sounds very familiar doesn't it?
Katy: It's almost 200 years old, but it's the same concept.
Niels: Now, lots of things to go into our conversation today. Clearly you've been very busy writing your book and teaching students, and educating them about trend following. That's a big part of your life, but what do you do when you're not doing this? What does Katy like to do when it's not about trend following?
Katy: Outside of work?
Katy: OK, I really like sports. I'm a big sports fan. I like not watching them but actually doing them. I like anything sports related. I think that's why I like finance too, because it's a little bit more of an exciting challenge. I also have two children, so that's why I laughed... what do I like to do? I'm pretty busy with that too. We like to be outside a lot here, in Sweden. It's a beautiful country here, so, we try and get outside in the Swedish Archipelago and things like that when we can.
Niels: Sure, fantastic. Now, before we go into the next topic, as such, I want to stay with the theme of history, but in a broader context. We talked about the history of trend following, but I think it's fair to say that trend following, perhaps you could say, is built upon three things: data which relates to history, then there's some science, and then there's the art. Talk to me about what you think about these three building blocks when you hear them?
Katy: Well I think that this is an important concept because in our book we focused on all three: history, science, and art. I think you of the things that often we academics tend to forget is that history is very important, because history provides, and sort of shapes how we perceive things and it builds contextual relevance. It gives us contextual relevance for what we do. So we started with history in the book well knowing that historical analysis is fraught with issues, but we thought that it was important to tell that story. On the other hand, we also focused a lot on how do you create a science, a structure around the art... which then turns into art? So I think our book, in some sense, is much more about the science, and then we give details in terms of how art can be added to it. So I would say that the science of trend following is understanding how to build the system; what properties are important in building that system; what statistical properties to expect of the strategy; how to understand how to combine different components of a trend following system; and I'd say that the art is actually in the application. So if you imagine any sort of trading strategy or any hedge fund strategy in general. The science is simply how they construct their process, but the art is what makes one manager different from another.
Niels: Exactly, yeah. Now I think it's fair to say that science, and art, and looking at that in terms of your work, you've clearly put a lot of time into filling what maybe I could call a lack of academic acceptance of trend following, which you alluded to earlier. Is it fair to say maybe that this has become a bit of a quest for you that you want to set the record straight in the academic world about trend following?
Katy: Yes, I would say so, in the sense that as a graduate student I had a funny anecdote as I was studying stop loss rules. I sat down with one of my colleagues at MIT and he basically told me that people maximize their expected utility functions. I just got so infuriated, because I said, "no they don't. It's not true." My father is a clinical neurologist, so I spent most of my life hearing about how the brain works, over breakfast, which kind of effects the way that you see things. From that point, even as a grad student, I've always believed that it's really sort of life is about applying heuristics and rules and we need to understand the implications of these rules, and these sets of rules, in order to understand what to expect and which rules are good and which are not. From that perspective it was very obvious to me that the study of heuristics and trend following, as one of them, is just part of the entire investment management process and the fact that we dynamically, over time, make decisions, and we use heuristics that we adapt over time to do so, means that sort of a static frameworks in the academic world don't cut it to explain things like we do. The academic community is really opening up to this. In the last few years, basically the fact that we can now be called momentum, means that suddenly we now have this buzzword which means that we fit into a bucket which is accepted in the industry. Industry has accepted us, but without the acceptance of the academics we have to understand that those academics train most of our... the academics and the education trains the people who are in the investment management field today. When we learn about finance, we create a framework for what we understand, and what we think is OK and not OK, and how we can think about risk and we sort of have the ability to understand things in that context. If you take a context like the Efficient Market Hypothesis, unfortunately for something like trend following, it doesn't... it's not possible. I think in some sense that was sort of the quest, was to explain both... that's why we go into theoretical foundations. We talk about risk taking, and we try and see what framework does explain why this might work.
Niels: I use the word quest. You've used the word quest, and as you know, a quest is really striving towards a goal, but part of that is enduring a certain amount, for lack of a better word, suffering it seems. Has there been any suffering in your journey? It's perhaps a bit philosophical in this case, but if there has been obstacles or difficulties, how would you frame that when you have a quest to achieve what you wanted to achieve, and which you seem to have achieved in putting this book together?
Katy: Well I think I this is an important philosophical point. I often think that if you don't fail, you will never succeed. So something that is easy to do is often less exciting over the long run to achieve. I think that from the beginning I always knew that this is the answer. I've continually always believed that I will find a way to explain it and over the years, the more that I asked myself these questions, the more the interesting answers come up. I think I'm just kind of the person who somebody asks me a question, and if I don't know the answer, I will be irritated until I figure it out. So it means that I'll spend a lot of time thinking about stuff. In the end, I always have to have the answer in some sense. I think actually spending a lot of time at MIT really helped me with that because at MIT it is sort of like training. You do lots and lots and lots of hard exercises all the time, and you learn to continue to fight towards your goal. So a quest is always fun to follow. It gives you a direction.
Niels: Absolutely. Now, I want to stick with the cover of your book and especially the last part of the title: The Search for Crisis Alpha. Now, I know you are responsible for coining this term "crisis alpha" and I want to talk to you about this. Before I do so, I also want to offer a slight concern that I have about the perception of the role of trend following in a crisis and it goes something like this. The way I see trend following being positioned, and this is not new. This is something that has happened for many, many years. It's kind of a hedge against equity markets if and when they run into trouble, and that always gets labeled as we're in some kind of crisis and that's obviously where the crisis alpha is linked to, but there are far more bonds than equities in the portfolios of investors and I never really hear any debate about trend following as "a hedge, or a protection" against periods where bonds might run into trouble. Especially in a time where bond prices are, to say the least, very high, how do you think about that and is there a concern that when we hear the word "crisis alpha" and trend following, that people automatically think that this is relating to equities?
Katy: Yes, we actually take that point up in the book. I think, maybe if I sort of step back and talk about where crisis alpha came from - where this original paper came from to give some contextual reference for that. I was in a meeting with Hans Fahlin, who's the CIO of AP2, and Hans turned to me and said, "I don't understand. Tell me why does this work during this period of time?" I stepped back... everybody knew that trend following tends to do well during a crisis period and I just was so irritated that I couldn't answer that question that I actually thought about it for some period of time and I went back and did some analysis and did some research and I said, "my goodness, this is pretty incredible, on certain days, when things are really bad for equity (and I'll get back to the other markets in a second) things are... something is happening." It's not just happening in equities. Most of it is happening outside of equities, and it's not just happening in commodities, it can happen in rates, or FX, or here, or there. I started looking at these days where there's these big moves in equities and I found that (and this is going to be a geeky point) the days during these periods of time actually first orders to castically dominated the other days. Now what that means is that cumulative distribution of these particular days is actually before the distribution of the days outside.
Niels: Break that down for me, please.
Katy: OK. I'll try it again, OK, so imagine... imagine I'm trying to explain this to one of my MBA students. So if I take the days where equity markets go down, and I look at a simulated trend following system, and I take something which is called the cumulative distribution function. So how that works is you think of it as building. When you build a cumulative distribution function, it's as if you take the values and put them into a bag, and so you start collecting them. So if something has a big fat tail, you're going to see a lot of mass on the left side, and then it's going to grow up less slowly. So what you can do, actually... one particular statistical test you can do is you can look at if one dominates the other. What that means is that the cumulative distribution is farther to the left... the one that dominates to the right, and then you have another to the left. So if you have two distributions: one that is to the right of the other, completely. Then it's considered first order domination. If you take stocks and bonds, this relationship doesn't hold, because they cross and why is this the case? It's because stocks have fat tails, which means that they end up collecting more of these worse scenarios first before bonds, but then they have much better performance latter, so their distributions actually cross. So it makes sort of a loop. But when I looked at trend following returns in a certain... some of the daily analysis that I looked at, based on a sort of a filtering rule that I use, I could find periods where there was first order stochastic dominance and I have basically never seen or very rarely seen that in financial data. I said, "there's something here that's just different." So I thought, OK, these particular moments... something is happening where these strategies are adapting to the scenario of sort of a crisis scenario in a way that is not expected. Then if you go back and you think about the Efficient Markets Hypothesis, futures markets should be so competitive that you can't make money, right, because they're obviously the most liquid, sort of the most efficient. Then I thought, wait a minute, maybe it's actually the case that they're a little bit like Buffet, that they're liquid when others are not, so the fact that they are so liquid and adaptable and in futures is what gives them an advantage over the others in these scenarios. That's where I said, OK, so what are they getting at this period of time when things are sort of a mess? Well, they're getting alpha, because they're finding opportunities that are up and beyond the sort of normal risk measures. So, I said, ah ha! Now I have a buzz word, it's "crisis alpha". The content of crisis alpha came out of that entire story. It originated from a question that someone asked me that I couldn't answer, and then I went back and did a research report on it, which I actually have never published but then I wrote a short article for the CME group to compliment this research paper, which was meant to sort of be for the entire industry, and that was the original paper which was meant to be for the entire industry, and that was the original paper which is called A Short Guide to Investing in Managed Futures: in Search of Crisis Alpha a Short Guide to Investing in Managed Futures, that was in 2011. So now going back to your point about bonds and commodities. That's something that really bothered me as well, because I kept getting that question all the time. So in the book we talked about crisis alpha for commodity indices. We talked about bond crisis alpha. We talk about commodity crisis alpha, but over the course of writing this book I actually had moved more towards a new idea, and this is the idea of divergence. What we do in the book is we explain that trend following strategies are long divergence. What that means is that the most divergent moment in history is always crisis, wherever it comes from. Yeah, so crisis alpha is part of that. That's extreme divergence. The story is a little bit more clear to me now that it's really about being long divergence in markets, and divergence can be driven by many things. The reason that equity is the central point is that most of us have a home biased equity markets. Our focal point from an emotional standpoint, are equity markets, so they have a little bit more impact on the psychology of the general marketplace, and that's why they can be more extreme, but they're in no way the only thing that drives divergence.
Niels: Sure. I want to talk about the convergent and divergent strategies, and I'd love for you to explain this, but I have to say, I think certainly that many investors are perhaps not... and maybe we don't have enough data, but it will be interesting to see how trend following may actually also be very, very useful in a period where we get a massive crisis in the bond markets, which, on a personal note, I would say looks very likely in the next few years. But let's take you back to the story about divergent and convergent strategies and let's be sure that we're mindful that not all listeners are familiar with these terms, so maybe you can break it down in your usual good explanatory way?
Katy: OK, so if you step back for a second and you think about risk as a concept, risk is really sort of what we face every day in every aspect of our life. It's sort of a dynamic process. How we handle risk depends on both what our frame of reference is as an individual, our experiences over the past, and also our beliefs. So if we think about that, those three things come together to give us an idea about which type of strategy we're going to use, in any risk situation, whether it's personal or financial. Convergent risk taking strategies are used when we believe that the world is somewhat stable, knowable, and understandable, and quantifiable. Many, many risks in life actually are somewhat convergent, or quantifiable. When we believe that the world is like that, then we tend to apply one set of strategies, convergent risk-taking strategies. Now on the other hand...
Niels: Can you give me an example of a convergent?
Katy: Yes, so I'll get there in a second. Let me explain the two first, and separately and then I'm going to show you some examples of both. I'll explain some practical examples and also a trading strategy.
Katy: So the difference between convergent and divergent is that we all know that Taleb has made this very famous with his "black swan", is that life is about risk, but it's also about uncertainty. So uncertainty is when the conditions and situations you are facing are unknown to you and unquantifiable. So when we feel that the world is governed by uncertainty, we have a very different approach to how we handle risk taking. So let me explain the difference here and give you an example. So if you're a convergent risk taker, you have a particular view. Let's say that you view that equity markets are going to go up, as an example. If equity markets go up, you tend to take profit on that. When they go down, you'll tend to do the opposite. You'll say, wait a minute, I know that equity markets go up over the long run, this looks like a buy opportunity. I should actually double my bet, or at least hold my bet and not sell it. So in that sense, over time, when you're convergent, when you win it reaffirms to you what you believed. When you lose, it actually goes against your fundamental belief structure which is sort of a threat in some sense, causing you, in some sense, to often reaffirm your beliefs. Now divergent is the opposite. If you imagine a scenario where you have no idea if A, B, or C is going to do better than the others, what you'll do is you'll invest, or put a small amount of investment in each of them, and if one of them starts to do well, you'll say, hmm, this could be it, I don't know, but A could be the one. So you'll double your bet on the thing that's going well. Every time you lose you don't have any prior expectations about a particular position or particular view, so you'll cut your losses. So those two philosophical views are very different. For those of you who know... you yourself being a trend following manager, you know that trend following managers, in general are divergent. When they're asked what their view is about the dollar, they may give a view, but they don't... they would change their view as soon as their indicators said something else. Global macro investors are not the same. Same with value investors, they believe in the value of a particular company. It really depends whether they work - if the world is actually governed by risk or uncertainty. So, let me give you some examples. Let me give some examples outside of finance and also some examples in finance. One of my favorite sort of analogies is actually social networking. I have a lot of Swedish friends who, I think in Sweden it's very focused on having a good, close network of friends over a long horizon. If you're socially a convergent risk taker, that means that you find a small group of people that you know, that you believe in and you nurture that: those relationships, bringing in some new, but not as many new. A divergent risk taker, socially, actually is one of those social butterflies, who goes from table to table knowing everybody and waiting until the next big opportunity comes. So they cut their losses very well. They have very good strategies for that. They find a way to go to the next table very easily. So that's an example in sort of your personal life, but another good example that I have used with some consultants and with other investors that I think is a good one, is the world of private equity. In the world of private equity there are two common strains: one is venture capital, and the other is the more mature leveraged buyout stage investing for private equity. The predominant strategy type in the mature world of private equity is actually more of a convergent approach, which means that you find the companies that you believe in; that you believe are undervalued; and you invest a lot in those companies, and you do a lot of the fundamental analysis to confirm your beliefs and make sure that you are doing the right, prudent thing.
On the other hand, the world of venture capital and entrepreneurship, there is so much uncertainty, so what successful venture capitalists do is they go out with a small amount of initial investments, and they invest across a basket of many interesting and possibly exciting entrepreneurs. They do analysis, but they just can't do the same type of analysis of cash flows and potential earnings that their friends in LBOs do, because it's just not possible. So in that case, where you're dealing with risk and uncertainty: things that are hard to predict, it's much better to put small investments, which means you limit your losses on the downside, hoping that one of these new startups will be the next big LinkedIn, or Skype, or Facebook, and the profile of these is very consistent with what we see in our world, which is the trend following world. Trend following is just a systematic example of a divergent risk-taking strategy.
Niels: Yeah, absolutely. Now, can we talk about convergent and divergent strategies without touching upon what you also write about, which is the Adaptive Market Hypothesis?
Katy: The Adaptive Market Hypothesis is a... so maybe I can explain what the Adaptive Market Hypothesis is so that I can give you my frame of reference. Starting in around 2004, professor Andrew Lo, from MIT, put forth the idea of the Adaptive Markets Hypothesis. This hypothesis is an alternative and a complement to both the world of behavioral finance, which is really a world of psychology, and the world of efficient markets, which is more sort of a physics view of the world, where you see F=MA. If you look on a spectrum, psychology and physics are very, very far apart. What Andrew brought forth, which is a really fascinating way to think about it is that markets are much more like evolutionary biology - somewhere in-between, where the psychologist have some things to say, and the physics matters too. So if I want to give you a definition of the Adaptive Markets Hypothesis, it's an approach to understanding how markets evolve, how opportunities occur and how market players succeed or fail based on the principles of evolutionary biology. So the concept in that, based on Andrew's work, is to see the market as an ecology and to understand who succeeds and fails based on those principles. So competition will drive who succeeds; resources which are available will drive profits; and the evolution of our industry is a function of the players that are involved in the industry and the resources that are currently available. So you asked me to connect convergent and divergent. Well, what that means is that, depending on the environment, at some periods of time convergent makes sense. At some periods of time divergent, but if you want to be adaptable over a long horizon and survive, you need to be both following the herd and convergent, but you also need to be divergent so that you can innovate, adapt and sort of be more robust in times when markets are changing drastically.
Niels: Absolutely. I think you maybe mentioned this earlier, and I think it's an important point, because often people believe that trend following by definition is just a long volatility strategy, but what you're really saying is it's long divergent.
Niels: Of course divergence and volatility is somewhat related, but it's not the same thing.
Katy: Yes, divergence and volatility are correlated. They're positively correlated maybe at 20%. The reason is that... I was just giving a talk about this recently for the CME, and what I said was that if you have low volatility, you tend to have low divergence, but if you have high non-directional volatility, so that means where things are going up and down, and up and down, but they're not really going anywhere. This is actually a nightmare for a divergent trend following strategy, so there's no divergence in that. It's actually low divergent. But if you have high directional volatility, then you have high divergence. So divergence is more if you take... it's basically the amount of discernable trend in price. So if you take this, sort of over an horizon and you divide the amount of movements, you're actually taking the volatility out. So if you have lots of volatility, the divergence is really the signal to noise ratio in prices. So when there's lots of volatility there's lots of noise, and therefore divergence is not very high.
Niels: No, absolutely. Now Katy, I can tell you one thing from practical experience with these strategies, and that is in the last couple of years investors have not put on a big smile when you call them and you say you're a CTA, but in fact, you've written about something you called the CTA smile. So I want to find out a little bit about how CTAs can put a smile back on these investor's faces. What does a CTA smile really mean?
Katy: Well, a CTA smile comes from the fact that when you plot CTA returns, let's say as a function of equity markets, they tend to smile at you in a sense that when equity markets have done really badly, these strategies tend to do very well, and then when equity markets do well, they tend to do well also, but when we're sitting in a situation where we're in the middle, then we're at the bottom of the smile, which is less exciting. What I would say is that as investors understand the complementary relationship; for those who understand the complimentary relationship between convergent and divergent strategies then it's not really a question about the current time environment. It's more sort of a question of having a properly diversified portfolio. If you believe in the Adaptive Markets Hypothesis, one of the first things is that risk premia are time bearing and that strategies success will wax and wane over time. If you have a period, like the last few years, in the grand scheme of trend following over the centuries, it's just a small bleep in history, but we solve this with the long/short equity strategy which was very out of favor in 2008, 2009, 2010, and 2011. Then recently, I've just heard there was a huge... that's everything anybody could talk about.
Katy: Then as soon as something else happens again, we'll be in the favor again. It's behavioral cycles, and for those who are sophisticated investors, we have to just continually tell them that to do well over time, you need to have different approaches in your basket, and we happen to be one that's very complimentary to most of the things that investors are looking for. Actually someone was asking about this the other day. It was some of our Cambridge Associates was asking me a question about this and he was asking, a lot of people are invested in value and value is a great strategy, no problem. The problem with value is it doesn't always work. There are periods of time where it struggles, and it turns out that something like trend following has a negative 20% correlation or up with value. When you're creating a portfolio, you need to be able to add strategies that are complementary to the ones that you believe in. As we continue as you probably do as well, as we continue to tell the story of trend following in an objective, constructive and non-biased way, then more people will understand, and hopefully smile.
Niels: That would be nice to put a smile back on investor's faces with trend following. Now I want to jump back to some of the questions and topics that I normally talk to my guests about, and I know it's not straightforward to relate this to your work, but I'm going to do my best. The next topic I normally talk about is a little bit about how a manager will organize their organization and build a strong organization, but in your case I just want to focus on one thing and that's research because that's obviously your area of expertise. Investors put a lot of effort and emphasis; I should say, on the research capability of a manager, and rightly so. Research is very important, but if you were going to put together a strong research team, as a manager, what would you be looking for? How would you do that?
Katy: Well I think the most important... I spent a lot of time teaching also behavioral finance and I think the most important, ironically, to create a good research team, the most important thing to do is to be aware of your own personal biases. This is sort of rule number one. So we basically, to create a successful research team, you need to have a structure which is going to help you create heuristics which will help you to avoid some of the common pitfalls that we, as biased human beings have. One of the major aspects which is important in analysis to start with will be peer analysis of ideas, but also a very, very keen eye on the limitations of backtesting and understanding a priori post distributions in sample, out of sample, and how to get a framework that properly accounts for these biases. When you look at track records from managers, it's always... there's always a bias, because we as human beings only report the things that we succeed with. We don't often report the things that we don't. As a result, we need to have very, very strict guidelines to be objective on why this particular research may actually just be data snooping or data mining. I think that that is sort of still the greatest challenge in any research team is how do you find good results, make sure they're robust, and also be very aware of your selection biases over time.
Niels: What about this thing about fifty Ph.D.s versus one or two or none for that matter. How do you see that? I know you're a Ph.D. yourself, but how do you see that role that often is quite important when investors make their decision, to be frank, they look at the size of the research team and think, ooh, he's got fifty Ph.D.s he must be better, but how do you see that in the real world?
Katy: Well, as a Ph.D. myself, there are both pros, and there are cons, and I say that not all Ph.D.s are created equal. That's an important point. On the positive side, the one aspect of having a Ph.D. that is helpful is the fact that you have to sort of learn the peer review and critical process. So that's one of the advantages of doing a Ph.D. is that you have that practice. That doesn't mean that somebody else can't do that, but it is one of the advantages that you are trained in the peer review and sort of to be a little more critical. On the other hand, for those of you who work with Ph.D.s, we also can tend to be a little more stubborn. So I would say that I think that this fifty or a hundred Ph.D. thing is sort of... it really depends. This is where the science has to be done right, and the art has to be done right. So I would see a smaller firm... a smaller firm is more like a start-up company. You have a few people that can drive really innovative ideas. If you have a very large team of quants and Ph.D.s, it can work tremendously well as long as it's properly managed. It's sort of like, I think we had talked about this in the past, you and I, but when you take a small company versus a large company, you can have fantastic results with both. Both of them depend on how they're managed. This is something that I think investors, unfortunately... you know we have this bias in finance already that we see that people always invest in larger companies, and not always sort of the value companies. It depends, right, so I think that's a tough question to answer because there's both a yes and a no to that question, and I think it really requires an investor to actually ask some more questions about if you have fifty Ph.D.s how do you handle that? How do you collaborate all of those ideas at the same time? If you have none, so what have you done to get up to speed with some of those issues that Ph.D.s have training for - peer analysis, critical review, backtesting, and so further?
Niels: Sure, sure, I don't know. You obviously speak to both many managers and institutions and I just wonder, firms with big research teams and whether there're Ph.D.s or not doesn't really matter, but big teams, big budgets, how much do you think that researching methods of increasing capacity, how much do you think actually is spent on that particular point, which in my mind is not necessarily a benefit to the investor. It's not about creating better models or new strategies. It's really just about increasing the amount of money we can manage using the same strategy. What's your view on that?
Katy: This is where I have... there's not a clear-cut answer - both a yes and no again. What I'd say is that there's a spectrum. So as you have a larger team, there are some advantages to that because you have more people to compare your ideas with. You can innovate and go in new directions and maybe you have capacity to adapt your art of your strategy. Maybe you have a sophisticated risk management system and you have very sophisticated trading algorithms that you can differentiate yourself from a smaller manager, but I'd say one of the major issues with why sort of a larger manager sometimes has some appeal to the investors is operational. So from an operational due diligence standpoint, it's easier sometimes to have more established, but what's the barrier, is the barrier 100 million, or is it 150, or is it 500, and that I don't really know, but I'd say, if you look at a manager who has 100 or 200 million, it's a little harder for them to have as much of the infrastructure, although outsourcing, today has actually gotten much, much better. So I'd say that there's always an ability to pay for something that is trying to raise more capacity, but I'd say it's both logical and illogical at the same time.
Niels: Yeah, absolutely.
Katy: Investors are looking for safety, because they see a large brand and they hope that that will provide them also some safety themselves, because their peers are invested in those, and they have a lot of personal risk as well for their own careers.
Niels: Yeah, absolutely. Now you mentioned the word track record, and I just wanted to ask, from your perspective...
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Date posted: 03 Nov 20142 comments