”My comment to him [Bill Dunn] was that I had a really good thing going so I wasn’t sure that that would really be the right move to make, and his response to me was, ‘that’s fine, I’m not sure you can really handle it.’”
Our next guest is a partner in a firm that has enjoyed 40 years of trading success with a 30 year continues track record of their WMA program.
The track record of the organization, Dunn Capital Management, is world-class. The legendary Bill Dunn offered partnership to our next guest and he replied, “I’m happy with where I am.” Bill’s response will make you laugh.
We’re grateful to have your ears for episode 009 with, Marty Bergin.
In This Episode, You’ll Learn:
- The Story of Dunn Capital and the Evolution of Dunn Capital Management
- How Marty began working with the firm and how he became a partner
- The company culture of Dunn Capital and why it’s so important to their success
- An overview of the WMA program
“It’s only one number in the system, but I think, going forward, it’s going to be significant in our returns”
- How the Value At Risk (VAR) approach separates Dunn Capital from other CTAs
- Why Dunn Capital manages all tasks in-house
- About the 30 year+ track record of Dunn Capital
“We didn’t make a lot of changes to the system for a number of years, and I think we kind of got behind”
- The big research upgrades taking place in 2006
- About the change to using two separate “Algo Classes”
- About the adaptive risk profile (ARP)
- Dunn’s approach to diversification across sectors (for example; 23% in agriculture and 13% currency allocation)
“Basic trend following, you’ve got 2 parameters. Time and noise. Instead of taking one time variable and one noise variable for each market, now we’re looking at hundreds of time frames and noise variables.”
Resources & Links Mentioned in this Episode:
Q&A with Bill Dunn
“When we look at the adaptive risk profile, what we’re looking at is: is this a good environment for trend following or is it not. The better the environment the higher the targeting mechanism is, the lower that we determine the trendiness of the market to be, the lower we adjust our target.”
Sponsored by Swiss Financial Services and Saxo Bank:
Connect with Dunn Capital Management:
Visit the Website: www.dunncapital.com
Phone: +1 772 286 4777
“The whole concept is that everything is 100% statistical. We don’t use any fundamental data in decision-making. It’s all purely based on price data because there is no subjective knowledge in price data.”
Niels: You are listening to Top Traders Unplugged, Episode number 009, with Marty Bergin, President of DUNN Capital Management. This episode is sponsored by Swiss Financial Services.
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 is your host veteran hedge fund manager, Niels Kaastrup-Larsen.
Niels: Welcome to another episode of Top Traders Unplugged. Thanks so much for tuning in today. I really do appreciate it. On today's show I'm talking to Marty Bergin, the President of DUNN Capital Management. DUNN Capital is one of the oldest and most successful systematic managers in the world, and Marty shares his insight on the evolution of DUNN, and talks about some of the key research discoveries that has let them stay on top of the CTA industry through the last four decades. For those of you who are new to the show, I just want to let you know that you can find all of the show notes including a full transcript of today's episode on the TOPTRADERSUNPLUGGED.COM website. Now let's get started with part one of my conversation. I hope you will enjoy it.
Niels: Marty, thank you so much for begin with us today. I really appreciate it.
Marty: Thank you for having me.
Niels: Before we dive into today's small structured discussion, if you like, I just want to start out by saying that it's a really great honor for me to have you on today's pod cast. It's very rare, in today's world to find someone who, not only has been a pioneer in the investment management industry, but who has also been so successful as DUNN Capital has been, and even more so, to find someone who can say that they have done it over a 40 year period. And if I'm not mistaken, October this year actually marks the 40th anniversary of Bill's trading career, and the 30th anniversary of the WMA Program.
Marty: That's correct. I appreciate the compliment. Of course most of that is deserved due to Bill Dunn's efforts and I'm just here riding the coattails and trying to continue the success.
Niels: (laugh) So today's episode is really special, and I know that our listeners will take away a lot of great insights and inspirations from what can only be described as a unique story. Both on an individual basis, in the sense that Bill has done something only very few in our field will achieve. But, to me, it's also really unique that Bill, yourself, and your team have done it over a period of time that has seen so many changes to the industry that you're operating in, which could never have been imagined back in 1974, and which go to show that there's a great level of robustness in what you do. So perhaps a good starting point for you would be to take us back to the beginning. Tell us the story about how Bill and later yourself got involved in the business, and take us through the evolution of the firm, which I guess, at its core, apply technology to portfolio management.
Marty: OK well, I think we only have an hour so, I'll try to give the reduced version.
Niels: You take as much time as you want. (laugh)
Marty: (laugh) Bill, after he got his degree...you know he served in the military, he was actually a boot camp instructor at one point, and once he got out of the military, he used his GI Bill to go back to school and get his graduate degree. When he graduated he went to work for the government and was working in the Washington DC area, and was what we would call a Beltway Bandit, in other words he was working for the defense industry. And he came to the realization that there had to be a better way of making a living. (laugh)
So, he knew that there was a way of looking at markets and using mathematical or statistical data to determine when to buy and when to sell. And his whole philosophy was based on price data. So originally he was looking at equities, and you have to remember, back in the '80s...or back in the '70s when he started this, you didn't have personal computers, you didn't have the computing power that you have today, and it became very clear that the population of equities was much too large to accumulate all the data, process the data and then act on the data within a brief time frame. So, at the time there were only about a dozen commodity contracts being traded, and he found futures and thought, well this is perfect.
So in the '70s he would actually sit down with punch cards, computer punch cards, he and his son Daniel who is employed with us today, would punch the cards, enter all the data, they would take it down to either the library, or they would rent time on a main frame, and they would run the cards through the system to come up with the prices that they were going to execute on the next given day. And we still have a set of the punch cards that were used in the mid '70s on our wall in our conference room. So it's kind of some nostalgia.
It's an interesting period of time, and throughout the years, the whole concept is that everything is 100% statistical. We don't use any fundamental data in decision making, and it's all purely based on price data, because there's no subjective knowledge in price data. Everybody knows what the price is. We trade in highly liquid markets, so the prices is being determined every minute of the day, and is very easy to value where your positions are at any given time.
Niels: And did Bill...starting out at the time where he started, did he know early on that he wanted to turn this into a business and not just a hobby, and I'm also curious about how you, and I know you have a completely different background, how you got curious about this and what you saw in Bill, and in DUNN Capital that obvious later made you join them.
Marty: Yeah. So when Bill started out the whole idea behind it was to make money for himself and other people. And he actually went to co-workers and friends and family to put together the first seed capital that was used for trading. Those investors, which are in their 70s, 80s now days, are still with us today. They joined in back then. They set up a little partnership, and started trading. At the time Bill didn't realize that anybody else was doing such things. If you think back in the '70s, it was before the regulatory bodies were even put in place.
Niels: I guess I can only think of Keith Campbell, around the same time, doing this.
Marty: There was, actually there was a few other players out there. One of Bill's very first clients was somebody that had found two or three people doing what Bill did, and they knew that what Bill was doing worked, but of course Bill didn't know if what he was doing worked. (laugh) And that was the first sizable investment that he got, and from that point on the rest is history. I think all along Bill's idea was to find some other way to make a living besides what he was doing. So I think he always planned on this being his future endeavor.
The way I got involved was, I'm a CPA by trade, and I was in northern Virginia working for a CPA firm that just one of the founding partners of the firm was Bill's next door neighbor, and helped Bill set up all of his accounting procedures for the partnership when he started trading. So that's how I got to know Bill. Of course at that point Bill had already relocated to Florida. I went and worked there, and the first audit engagement I was on was to audit funds for DUNN Capital Management.
Niels: When was this in time? I know you joined in '97, but when was this in time?
Marty: Oh, it was in the mid to late '80s. I was a green accountant with a couple of years of experience and I worked at that firm until I became a partner, and once I became a partner, Bill approached me during one summer, and asked if I'd be interested in joining the firm. My comment to him was that I had a really good thing going, so I wasn't sure that that would really be the right move to make, and his response to me was that's fine, I'm not sure you can really handle it. (laugh)
Niels: And here we are today, the President of DUNN Capital.
Marty: Yeah, I came down to visit, of course I already knew all the players because I had been down many times, and it took me about 20 seconds to say yes. Mainly because of the quality of the people I'd be working with. That's the key to Bill's success, is that we've always been a small shop. We take a lot of time and effort in picking the pieces that make up the team, and they all have to fit together. Not just from an intellectual standpoint but also from a personality standpoint. So we have a great group of guys and gals. It's almost like a family. You work together as much as we do in such a tight knit group, you have to have the personalities that blend.
Niels: Yeah, absolutely. You kind of took my next question by going down that route, so I appreciate that. Could you tell me, if we look at DUNN Capital today before we jump to the next area I want to talk about. So today you run the WMA Program, could you just give us an overview of the aim you have in that program? I know you also do other things with that location, and other programs, but for today's conversation we are going to be focusing on the WMA Program.
Marty: Yeah, so we basically have to different versions of the WMA. The original WMA is geared to the risk profile that we've always targeted since the inception of the firm, which is a fairly high volatility, high return type program. What makes us a little different than I think most of the people in the industry is that we target VAR, we don't really target volatility, although, once you establish your VAR, you can kind of back into what the volatility is. When I say VAR it's basically a value at risk measure. We look at one month period, or 22 days of trading. When we first started Bill had set up the VAR as a 1% chance of losing 20% or more in any given month.
We stuck with that throughout the years until January 2013, which we had a research project where we were trying to see if we could target the VAR according to the given market conditions, and that's a hard nut to crack. We did come up with something proprietary measure of the trendiness of the markets, and currently we changed the VAR target every day based on market conditions. Given that 5% of the time we will be at what used to be the old VAR of 1% chance of being 20% or more. Now, so our VAR has come down overall, over a long period of time. But you have to understand that is over a large period of time. The volatility is reduced from somewhere in the mid 30s to 23%, 24%.
Now the reason we approached it that way is we didn't want to give up any of the upside profitability. A lot of people in this industry have reduced the volatility of their programs, but in doing so, they also reduce the upside profit. And by doing what we are doing, we can still maintain the upside profitability. We don't give that away even though we are able to reduce our drawdowns. So, it's been a significant change for us. It's only one number in the system, but I think, going forward, it's going to be significant in our returns.
The other program that we offer is just an institutional version of WMA, where we basically have 1/2 the VAR. This is the original system.
Niels: And how much do you run in this combined program?
Marty: Well, so in the high volatility program there's $300,000,000 allocated, a little bit more than that, and in the institutional product, which we only opened up to outside investment a few months ago, it's $100,000,000.
Niels: OK, fantastic. But as I said, I know you also do other things, so obviously the total for WMA is significantly higher than this. The next topic I want to briefly touch upon, which I think is important for people to understand is a little bit about how you've organized yourself as a company, because clearly things are changing in our industry, and technology allows companies to do some things in house, some things are done outside, how have you gone about doing that? Do you do everything in house today, or do you tend to outsource some of your functions?
Marty: So, we handle everything in house. Part of that is because it's the culture of the firm, the other part of it is we really haven't found any outside providers that we would have a comfort level with, that they would do things to the standards that we would expect. Now that makes it a little difficult sometimes because we are different than most firms. We do all our all administration. We do all our own accounting, we prepare our statements, we send everything out, we do all our own trading. In this world, today, where people are looking for third party administration...you know there's even talk now about having custodians holding the cash. I think it's a choice that people need to make. One of the things that we're able to do is things are much more timely. The investor can deal directly with us. They don't have to go to a third part to have anything done. The cost is significantly less because we don't pass through any cost to the investor to provide these services. They aren't that difficult.
When I hear the industry or the regulators talking about forcing firms to implement some of these procedures to protect the investor, it worries me a little bit, because what they're basically doing is talking the choice out of the investors hands. I think the regulators should be more focused on looking for the bad actors and handling that type of activity as opposed to putting restrictions on managers and how they do their business, which then creates a more costly environment for the investor. Our feeling has always been, as long as everything is disclosed to the investor, you let the investor make intelligent decision based on the information they have at hand.
Niels: Absolutely. Plus the fact that at the end of the day investors, they buy people, and if they don't trust the people they shouldn't invest with them in the first place. I guess a lot of this regulation and forcing people to use these external service providers, which in some cases are fine, but it does seem to concentrate a lot of the assets with a few service providers, and that in itself creates, perhaps, other problems that regulators haven't really thought about.
But anyway, that's obviously an entirely different discussion, but before we dive into the program, I wanted to take a big picture view. I call it talking a little bit about the track records, because a couple of things: from a general point of view, we know that the environment for these types of strategies has been somewhat different in the last four years. But of course, looking at your track record, you could say that perhaps you anticipated some of this because I know that you have made three key upgrades, if I can call it that, in the last eight years: 2006, 2011, 2013, so perhaps you could talk a little bit about that and what made you go in these directions, and so people have a better understanding of the track record itself, and how your program evolved from a big picture point of view?
Marty: Well, first off there is no way we could foresee what was coming, that was for sure. I haven't found anybody that knows the future, and anybody that tells you they do they're lying to you. Basically our research grows out of knowing that nobody has a holy grail to trading. And that there are things that can be done, or we believe that there are things that can be done to improve what you are doing. And as technology has advanced it's given us the tools and the speed to do things that we weren't able to do back in the '70s, the '80s, the '90s. I also think, in DUNN's case, we became somewhat complacent.
Historically we were one of the top two CTAs in the world with assets under management and even performance, and we went stagnant. We didn't make a lot of changes to the system for a number of years, and I think we kind of got behind. In '06 we had the most significant change that we had done and that was where we moved from..oh geeze...it was kind of an overview of everything. We went back and just reevaluated the way we approached the markets in total, and before '06 we looked at every market as an individual market, and we basically designed our system with a market by market basis. We determined our trading signals in each individual market, and then we put the whole portfolio together after the fact.
In '06 we took a totally different approach. We said, you know nobody cares about what happens in each individual market, all we care about is what happens to the portfolio as a whole. So we started looking at the markets from a portfolio as a whole basis, and we started designing the models for the whole portfolio. And therefore every market traded within the same model. And we even did it as far as our parameters selection process on a portfolio whole basis. That made the systems much more robust, and we also expanded from just the financial markets to all the commodities within the WMA program, because before that there wasn't the volume and you didn't have electronic markets, you didn't have the ability to trade real size in a lot of the commodities.
Niels: And how many models were you actually running up until 2006?
Marty: Well, we basically had three models for each market and they were contingency based, so we would determine before the next day what prices we would buy and sell at. And then if we hit that price, each model had its own price, we would either buy or sell during the day given those prices. After the changes we were trading upwards of 100 different models and what we did is we combined the models and just came up with a strength: either +1 or -1 of that market, and then we would trade on the open of each day. We already knew what we wanted based on the prior days activity.
Niels: So a lot of that expansion in term of models was really maybe looking at different time frames within the same market to build that confidence or strength within a market before jumping into it.
Marty: Right, so basically, in trend following you have two parameters: time and noise. So instead of just taking one time variable and one noise variable for each market, now we're looking at hundreds of time frames and noise variables, and the other thing that gave us the ability to do was to migrate between shorter term trends, and longer term trends, given the market place, and it made us a lot more adaptive. It made us a lot more flexible. And we weren't riding on signal bets. In 2008 we implemented a dynamic risk, where instead of targeting our risk based on some historic data, we basically started adjusting our risk every day. That was fairly significant thing that we did.
Niels: Sure, sure. In 2011 comes along and that seems to also be a significant year for the trading system.
Marty: Well, 2008 was the real good year. Everybody did well. I think 2011, what was nice about it is it kind of separated us from some of the other people in the industry. If you look back from 2006 forward, what you can see, as time goes, is when we do make these changes in research to the program, it's been validated by the performance. Now, you know any time I talk to somebody and say, hey, we've got this great change. They don't know what kind of research went into it. They don't know what kind of back testing went into it. They don't know if you know what you're doing when you're doing out a sample. You can say you were out of sample, but I know a lot of people who say they were out of sample, but by the time they do the out of sample test 10,000 times, it's not out of sample any more. So, you know, we can say these things, but nobody knows for sure if we really know what we're doing. But if you go back and look at when we started making changes, and look at what the performance was from that time forward, I think it's clear that our changes have been successful changes.
Niels: Yeah, no, we'll definitely come to that, but I agree. Would you say that '11 was an interesting year certainly for you, because you made some changes also in 2011, if I'm not mistaken, where you introduced some additional model class or models if you like?
Marty: Well, I think what you are referring to is when we switched to two Algo classes.
Marty: We have an Algo class that has a stop loss provision in it. And I use that term loosely, because that is what it does but it's not a stop loss like most people would think in terms of price movement loss, it's not based on price. So yeah, we have two different types of Algos that they do have some correlation, but not really tightly correlated. And the two of them together definitely provide better performance than either one of them standing on their own. That was implemented in that time period. We also added the meats to our portfolio at that point. You know that's a significant change because of you go from one model class to two, that's significant, but from a performance standpoint, I don't know really how significant it was. 2011 was a good year for us, no question. Especially when you compare us to our peers. You brought up earlier about the last 4 years, and I mean it's been a tough market for trend following. It's been a tough market for us. We were at a new high in December of 2012, but being at a new high versus, significant growth over that 5 years, it hasn't been significant. We were at a new high, but it wasn't significant. It's not like we've done in the past. It's been a struggle. I think it's been a struggle for everybody.
Niels: Yeah, I'd like to certainly circle back on that and ask you a little bit about that, because I think that is an important period to recognize. But before I do that I'd love to just finish the circle, because you mentioned earlier a significant change, or improvement came about in early 2013 with regards to...without limiting the upside, you managed to find things that could reduce the downside.
Marty: Right, so that's what we called the adaptive risk profile. And what I was explaining before is now, instead of targeting the same VAR every single day and adjusting accordingly to that target, we now adjust the VAR that we're targeting every single day. Basically we're looking at the market volatilities and the correlations, that is what we're using to size positions, but when we look at the ARP, or adaptive risk profile, what we're looking at is whether it's a good environment for trend following or not, and the better the environment, the higher the targeting mechanism is the lower that we determine the trendiness of the market to be, the lower we adjust our target. And, as an example, currently we're trading at a VAR of about 14, and like I said, when we're at the top we're trading at a VAR of 20 and we should get there at about 5% of the time going forward. This would be a reduced trending market.
Niels: And that number, is that derived from looking at all the markets in the portfolio and measuring the trend strength by market and aggregating that into a number?
Marty: Yeah, basically we're looking at three things, we're looking at each market, whether it's determined that it's trending or not, and then the correlation of that to other markets and the volatility of that given market.
Niels: You also mentioned that you expanded the number of markets back in 2006, how many markets do you actually trade now?
Marty: 53 markets.
Niels: So that stayed relatively stable in the last..?
Marty: Yeah, we added the meats and we dropped OJ out, and basically we look for two different things...well three different things: we want a market that is traded on a regulated exchange; we're looking for markets that have high consistent volume over time; and we're looking for markets that are uncorrelated to what our current portfolio is. So if it can give us diversification, it can be traded with low risk, and the viability of being able to get out of the position when needed, if all three of those things are aligned, then we can add that market to the portfolio.
Niels: And the 53 markets, they cover then all sectors, so you are fully diversified, compared to many of the large managers where they seem to be more concentrated in financials, I guess you are fully diversified over all the sectors.
Marty: Oh yeah, so we have 23% allocation just in agricultures. We only have a 13% allocation to currencies, and I think the larger managers are forced to trade more and more in the currency market, because that's the biggest market in the world.
Niels: In a sense it goes back to the point that you were raising before where you were starting to talk about the last four or five years, and I would love to hear your opinion about it, and that is has the last four or five years been all about sector weights, meaning that the people who have been overweight in equities tend to have done much better than the people who were fully diversified. With you will maybe be the exception to that rule, because you are diversified and you have done well.
Marty: Yeah, I think especially this year and last year, and probably the last three years. If you are overweight long equities, you had an advantage over most of the other players. I will say that in 2013, which we had a very good year, we made over 30%, those profits were generated in the financial markets for the most part. 2011 people look at us and say, oh, you must have made all your money in agricultures, because everybody else had a tough year. Actually no, that's not where we made our money. So it's not sector allocation. Sector allocation allows us to take on a little more risk sometimes, because we have a more diversified type portfolio, but we're truly doing something different, and I don't know exactly what it is we're doing differently because I have no idea how other people's systems are operating. All I know is what we're doing, and I know that the correlation in the last several years has been dipping between us and other trend followers. But I can assure you we're still doing 100% trend following.
Niels: Yes, this is obviously the interesting bit, because a lot of people have kind of diverted away from trend following. When doing trend following, you said that you have two Algos groups, just again, ballpark, how are they different? Is there anything, for example, some people use moving averages as a way of identifying trends, some people use price breakout channels, is that the kind of difference from an overall design point of view, just looking at the Algos?
Marty: Well, so, let's just look at what happens and I can show you the difference in the two pretty clearly. The original Algo which was something Bill designed in the '70s, we still trade the original system. That system is always in the market. It's either long or it's short. It's never out. It's a full rehearsal program. The other Algo is an Algo that is either long, short, or flat. The second Algo also has a function in it that acts as a stop loss function, so that's really the difference between those two Algos. The entry and exit points their different, but you know everybody's is different.
Niels: Do the algorithms rely on a feed of intra-day data, or are they in the day data reliant?
Marty: We're purely looking at high, lows, and close.
Niels: And when you talked about position sizing, and adjustments and trend strength, determining how convinced the models are, how does that work? Because that implies that you would, maybe not every day, but you would adjust your positions once you're in a trade, that it's not a static position size.
Marty: Right, so at the end of every day, we determine what position we want to be in given the data. We look at the positions we are currently in, and then we have a small threshold so that we're not buying one lot, selling one lot, selling one lot, and we adjust every day.
Niels: Interesting. So you mentioned that you have the two models and in terms of other performance drivers in your system, would you say that time horizon or system design, meaning your Algos being very different from others. Is there any of that that plays a role in the performance, which clearly has been superior to many of your peers?
Marty: I'm convinced it's risk management and portfolio development. I find it hard to believe that the actual Algos in trend following are really that much different than what everybody else is doing. But I could be wrong.
Niels: I think that there are certainly a lot of things to be said about, if you can identify the markets that are trending, and getting a full position in those markets, at the same time not having a full position in the market in the stock in ranges, I do think that has a significant impact on performance, and that, in a sense, is very much sort of the holy grail of what we are all trying to do.
Marty: Yeah, the only thing is you have to be careful. I agree with you and I think the key there is...
Ending: Ready to learn more about the world's top traders? Go to TOPTRADERSUNPLUGGED.COM and sign up to receive the full transcripts of the first 10 episodes of the show and visit the show notes, where you can find useful links to other amazing resources. Thanks for listening and we'll see you on the next episode of Top Traders Unplugged.
Become An Insider
Subscribe for free and be the first to receive new and exclusive interviews with the world's top traders. As an insider we'll also send insightful bonus content direct to your inbox.Free Instant Access »
You might also like:
Date posted: 30 Jun 20141 comment