“Carry is really about picking pennies in front of a steam roller. The greedier you get, the closer to that steam roller your going to be.” – Anders Lindell (Tweet)
Welcome back to the second part of our interview.
In this episode we dive into the negative effect of greed on the market. Anders Lindell again shows his depth of knowledge as he elaborates on the nature of irrationality though the ages and how our markets today, really are rather stretched. This is a powerful episode, I really do hope you will enjoy it.
In This Episode, You’ll Learn:
- How the IPM model profited by choosing to position against the carry frenzy in Japanese Yen during late 2008
- Risk factor analysis when selecting model attributes
- What the more reliable indicator in the global economy is
“We’re not interest in the absolute level of carry per market, we’re interested in the deviation from the longer term average carry being delivered by a specific market.” – Anders Lindell (Tweet)
- How their trading model works on overall, daily basis
- “Stop-Loss” Positioning in the IPM strategy
- Where IPM identifies value traps and optimizes their exposure to it
“When we design our risk factors, they are designed to be uncorrelated with each other.” – Anders Lindell (Tweet)
- The average length of trades at IPM
- What drives the relationships that Anders explores to build models around
- If Correlations structure matters when IPM decides on risk overlay to make market decisions
“I do like traditional valuation metrics. I think they are reliable, they make a lot of sense from a fundamental and theoretical perspective, but it can take significant time for them to play out.” – Anders Lindell (Tweet)
- Why timing can be the largest challenge for their strategy
- How Anders defines risk and how IPM controls the model and expected risk
- The biggest fear Anders have in regards to unexpected market effects
“People may trade in or out or create trends and prices may deviate, you know, it is just noise over short time spans. We’re trying to step back and avoid that by specifically trading and holding trades over long periods of time.” – Anders Lindell (Tweet)
- What is expected in regards to drawdowns in the IPM Global Macro Strategy
- How to convey the needed confidence to investors during drawdowns
- Risk Management/Risk Control model rebuilding
“Spend 1/3 of your time trying to understand what we do on the Alpha side. The other side you should spend on risk management and the other third you should spend on understanding our portfolio construction.” – Anders Lindell (Tweet)
- How Anders Lindell identifies research processes which will over engineer and cause return issues
- Succession planning as Anders sees it for IPM – Perception and Vision
“I’m not so sure that market/investor irrationality has increased over time. I think we feel that at the current time, but that’s only because our time window is so short. – Anders Lindell (Tweet)
- The challenges for IPM and how overcoming them has helped to make them stronger
- What Anders would suggest for investors to focus on
- What it takes to be a great hedge fund manager in today’s economy
“One of the reasons for being systematic in the fist place is to avoid exactly this emotional behavior.” – Anders Lindell (Tweet)
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“We need investors that have confidence in what we do based on knowledge of what we do and that can only be accomplished by complete transparency. The more client dialogue we have prior to the mandate, the better.” – Anders Lindell (Tweet)
Niels: You're listening to Top Traders Unplugged, episode number 024 with Anders Lindell, co-founder and Chairman of Informed Portfolio Management. This episode is sponsored by Swiss Financial Services.
Welcome back to Top Traders Unplugged. Where the best traders in the world come to share their experiences, their successes, and their failures. Let's rejoin the conversation with your host, veteran hedge fund manager Niels Kaastrup-Larsen.
Niels: Are there any of the types of strategies that you use within each theme that you could try and visualize for us. I know you've talked a little bit about it. For example, I'd like to talk a little bit about carry. I'm no expert, but obviously carry has been quite a big source of return for many people for a while. My guest last week was quite concerned about some of these trades that are being put on (in his opinion by large asset managers) to compensate for not making so much money in the directional arena. If we look at currencies, at least developed currencies, volatility has gone down dramatically in recent time. So, maybe talk a little bit about how you see, if you are going to drill down in your carry models, how do they work, what do they look for in your world?
Anders: Well I think that as a starting point, and this is, I don't know who said that first, but carry trading is really about picking pennies in front of a steam roller. The greedier you get the closer to the steam roller you are going to be. Typically it more often than not, it ends in tears. One typical example of that would be the carry game that started in 2006 and continued through 2007 and into 2008 involving obviously the Japanese Yen, and that ended ( I suppose for many of the people that continued pushing that trade all the way into first quarter of 2008), that certainly ended in tears for them. What our model did was go against this to a very large extent. So we paid a little bit on our positioning in Yen in 2007 late 2006 all the way through 2007 up until January, where the first bank came in March of 2008, when the second instance happened, when we profited quite a bit on the collapse of that carry model if you like. That's a general observation.
More specifically to our models, there's nothing fancy in what we do on carry. Obviously we have our own models trying to identify both carry in the traditional sense of the word, and changes in carry and few other things related to that. The most notable point with our model, again, is that it's relative. We're not interested in the absolute level of carry per market. We're interested in the deviation from the longer term average carry by a particular market and risk adjusted. So, just because we have a situation where statically over time Kiwi in Aussie has probably delivered better than most other markets over the past 10 years or 15 years, whatever. That doesn't mean in our books that we, necessarily from a carry perspective always have to be long in those markets, because we are interested in how much does carry in Australia, today differ from what it has been on average over time. That makes a big difference when you trade like that, or then try to evaluate these sorts of absolute opportunities.
Niels: So in a sense, it would almost be like (if I'm right) going the opposite way, so as this carry opportunity deteriorated, and some people levered up to get the same absolute return, your models would actually go the other way and de-lever, because the opportunity was going down.
Anders: That would be entirely reasonable, yes.
Niels: Interesting. In terms of these strategies macro valuation and risk premier and market dynamics, for example, are there any of these that are more dominant in the portfolio or the program structurally?
Anders: Not really. If you look inside each of those boxes, you will find a number of different factors. What we try and do is, here too, to try and be unbiased. When we design our risk factors, almost per definition they are designed to be uncorrelated with each other, central distribution of all that. They are designed, and we only introduce them given that they contribute enough in terms of forward looking sharp expectation, if you like. Typical risk factor may deliver something like .1, .2 in expected sharp. Now as they have qualified for the model, we believe they are sound, we believe they will continue to deliver over time this forward looking sharp, and hence, we think it is relevant to actually equal weight these risk factors. We don't believe in altering the way based on historic performance, or aching to increase the weight of stuff that's been successful in recent times and decrease weights on stuff that's been unsuccessful in recent times, because that again would lead you into situations where you basically increase your bet on everything that's gone well over the past time, so you become a mental trader.
Obviously if things continue to underperform over an extended period of time, you should start asking yourself the question, why is it? Is it not properly defined? Has this particular thing all of a sudden become arbitraged away? Or are we looking at it from the wrong perspective. Then those questions would go into the research process. So at a factor level everything is as a starting point, pretty much equal weighted. If you look at the main themes, value, risk premier, macro, and market dynamics, that strategy will come out as having a little bit of a value bias generally. This is pretty natural as we are trading on sort of mean reversion to longer term equilibria or value, and we're using fundamental information. So you should expect these to have some degree of value bias. Not a strong one, but a little bit.
Niels: Sure. Looking at, if I can define it like that, a model is something that could generate some level of signal and thereby some kind of scoring impact on the overall portfolio. How many of these "models" would you say that there is combined in the whole strategy, because it sounds like there are a lot of moving parts that can influence each of the markets and the themes?
Anders: There are a little over 40 different risk factors or sub models that go into this.
Niels: And given in all of your experience, just out of curiosity, is there any indicator when you look at the global economy that you like better than others that you think is more reliable than others?
Anders: It's a matter of horizon. Personally, I do like traditional valuation metrics. I think ultimately that they are reliable. They make a whole lot of sense from a fundamental and theoretical perspective, but it can take significant time for them to play out.
Niels: How frequently do you run the model? Because obviously some of these factors don't change every day, maybe let alone every week, how does it actually work when running the model on an overall basis?
Anders: It is actually run on a daily basis, and the model is re-estimated on a daily basis because what goes in...there might be an odd price here, there might be an inflation number from there. So, if you look at the world today and all of those markets that we trade, it's likely there's going to be a couple of new inputs at least, per week, even on a daily basis quite often. Obviously some periods are going to be more intense than others, but also as market prices move around, the model will observe this and try and adjust positions accordingly. What the model comes out with is the side exposures per market on a daily basis, and if the market has pushed us in a direction where exposure has grown or contracted, relative to what the model wants it to be, then some level of corrections will have to be done. So there's a little bit of trading actually going on, on a daily basis, but compared to most other managers in the traditional systematic space, I dare say our trading intensity and portfolio turnover is very, very low.
Niels: Now, if I'm not mistaken, you're not really using a traditional stop loss in the model as many people do in the systematic space, at least. Tell me philosophically a little bit about why that is and when not doing it that way, how do you...to begin with determine the risk for new trades, if I can put it that way, not so much for how you manage the risk overall, we'll get to that, but just sort of the sizing issue when you put on new trades, how does that work when you're not utilizing a stop loss?
Anders: Starting with stop losses, I think most of the people actually use stop losses are exactly people or firms that model individual instruments in their own right. So basically they are building a portfolio out of 40, 50, 100 traded instruments, and they can assign a stop loss to each individual position. So if they stop themselves out of soy beans, that doesn't change anything for their positioning in base metals. Or if they stop themselves out of Canadian "govys", that doesn't mean anything for the S&P futures. Whereas in our setting, everything is modeled against everything else, so the positions that we take are entirely dependent on all of the other positions.
So if we identify, or if we were to identify a particular instrument having taken significant losses over the past period, and we would say right, so let's stop ourselves out of that one. That will immediately change the entire portfolio because not only do we have to kill that particular position; we have to alter all of the other positions with wholly unpredictable results in the end. We may do something inherently smart by doing that, or it may be incredibly stupid. Additionally, the way this model works is that we have to accept the risk of drawdowns on individual instruments and indeed on the whole program for it to play out because what this model does is...take something very, very simple, to exemplify: if we're looking again at the PPP valuation model on currencies, and that one identifies a particular currency, let's call it the Swedish krona, that starts getting underpriced in relation to value. We would start buying that. In all likelihood that currency is going to continue, the Swedish krona is going to continue to become even further underpriced in relation to fair value before it starts mean reverting back. During that period, we would start almost immediately to buy and then we would continue buying and increasing that position all the way to the trough. That means in that period when we build a position, almost from the issue we've got to take losses - to be max long at the trough, and then start profiting from that.
Now this can play out over a couple of different scenarios. A typical scenario that would cause losses for any model like this, and this is certainly true for our model, is the traditional sort of value trap, which is almost exactly what I just described. These are things that we would play out over a longer period of time, and you will build your position and take further and further losses. We're OK with this, to a limit, or to a degree, I'll get back to how we try and compensate for that. But it wouldn't necessarily be meaningful to take a stop loss in such a scenario because what will happen is we are going to pay the price to build the position to be long when it starts mean reverting, but we'll kill the position before that starts happening. The other scenario is very, very fast moves in the markets. Let's say something like 1987 would happen again, or the Fed hike in 1994, or long term in Russia crisis in 1998, or whatever scenario that you can imagine, where all of a sudden this is typically centered around equities, markets sell off 10%, 15%, 20% in a very short period of time - August 2011 for example. So here is a situation where we are going to face a steep loss if we come into this sort of not in the correct position, we would face a steep loss and almost inevitably what happens on the back of that is that markets swing back relatively quickly. These are not scenarios that continue for quarters or for years typically. They swing back pretty quickly. So what you are going to accomplish with a stop loss in a scenario like that is that you are going to lock in profits, and you're position is going to be too small when it springs back. So from that perspective stop losses wouldn't be productive.
What we try and do though, to limit our exposure to various type scenarios is that we're setting limits as to how big we can be on each market - exposure ranges we set. We say, for the full risk program, we may never be longer than X% or shorter X% in any particular market. So that's a limit that the model has. Additionally, at risk factor level, and this is part of the portfolio construction process, we actually do limit how strong signals can go into the final portfolio construction stage. So let's say that you have a signal of, let's call it 1, and you would then take position in proportion to that 1, and the bond here, by the way, would be standard deviation. So it's entirely reasonable to take a position that lies X against a standard deviation signal. Now let's assume the opportunity was to become much more significant, so we end up in a 2 standard deviation signal, which would be immensely rare, but as we all know such things happen more often than statistics prescribe, so our model would then like to double its position pretty much.
Here's where it starts getting iffy. We're still OK with that, but if you double that again, let's move from 2 to 4 standard deviation events, they would have often happened in a person's life, would you be comfortable doubling up again? And here's where we start taking a step back and say, yeah the model is probably right. This represents a 4 standard deviation scenario, as the model is defined, and really we should take a decision based on that, however, knowing that that would be a very large position we would also expose the model to a significant risk of drawdown based on timing because the model may be off - this thing may not mean revert for another 2 months or 3 months. So the likelihood of a drawdown would increase dramatically, so here is where we start limiting at some point north of 2 standard deviations we actually start limiting the strength of signals that are allowed into the portfolio construction stage.
Niels: That makes sense, yeah. How long are your trades actually, on average, because they seem long term?
Anders: In general the average would be about a year. On the currency side a little bit shorter, 9 months let's call it, and on the asset side, a little bit longer.
Niels: What's the most difficult sector to trade based on your method do you find? You mentioned August 11, and we all know equities were tough in particular because of the uncertainty of the US default risk. Is that a particular difficult sector to trade when these things happen because they react quickly? Or...
Anders: Yes. Equities in general, in particular relative equities with our way of modeling is quite difficult. Currency market, I wouldn't say they're easy, but a little bit more straight forward when you get the responses that you are striving to get.
Niels: And what do you think drives these relationships that you profit from? Is it more economically sort of changes, or is it investor psychology, or is it just human behavior? I mean, you know, as I mentioned before things go in cycles, and we tend to come back to the mean. What have you observed over the years?
Anders: I would be inclined to say all of the above. Actually I think it's a combination of different things. One way to exemplify it would be to step back to the fall of 2012 when they started talking about the introduction of the quantitative easing program down in Japan. Obviously a lot of people were pretty quick to respond to that. The likelier it became to them, based on their analysis of the political and central bank situation, people started running ahead of themselves and take position on this. The running ahead of themselves probably is the wrong expression there because a lot of people do that with significant profit. As that continued, some of the people that were earlier in probably started taking their profits and saying that this has run its course, whereas others once it has trickled down to the more general investing community, they continued in that same direction. Whereas our models, they wouldn't hear the open mouth operations by bank of Japan. They would only note this when it starts materializing in our data. (Which means) Here's a trend in markets established by people trying to anticipate what Bank of Japan is going to do and how the currency market is going to react, how the fixed income market will react, and certainly how the equity market is going to react to this, and what corporate profit is going to be like in Japan going forward. So based on that (and this is something that typically happens) is that people extend what initially seems to be a reasonable trend, they extend them way too far. And then when the final realization comes through that hey, the corporate sector in Japan isn't going to be as profitable as they could have been based on these, and the Yen isn't going to 180 against the dollar, or whatever number they had targeted. Then you have a reversal of that, and this is typically what a model like ours would try and profit from. So in general investing behavior, people trying to not unfollow the trend, but people generally overextend it far beyond the point it has contact with underlying fundamentals. That is one major point.
Another major point that I want to mention is a time horizon or investment horizon. People may trade in or out, or create trends and prices may deviate, you know that's noise of the shorter time spans. We're trying to step back and avoid that by explicitly trading and holding positions a longer period of time.
Niels: A couple of things that come to mind when you say that. In one sense, it actually is a great injustice, not just to your strategy, but to many strategies. (The injustice) you could say, is for investors to look at these things on a monthly basis and kind of judge you based on what you did last month. Because what you're really saying is that part of the success is having the ability to take a much longer view and not be concerned about an adverse move, over the next few week because you know it's going to work out, maybe over the next few months. But I also wanted to ask you about position sizing, is that the secret sauce do you think, meaning that a lot of the themes that you end up in, and I imagine a lot of the strategies and positions you end up in would be somewhat similar to other global macro managers. But I do note that you've done quite well compared to your peers, and do you think position sizing is part of the success, that you simply manage the risk differently maybe?
Anders: Yeah, I think there are several parts to it and several moving parts here. But what I tend to say to clients that want to evaluate what it is that we are doing, 9 out of 10 clients, for good measure I'll throw in the consulting community here too, they are spending way too much time focusing on what we refer to as those risk factors. They want to know them all, and they're looking at purchasing power parity and they want to understand how exactly we built that particular factor while noting that, academically speaking, PPP has a mean reversion time of 50 years - clearly not investable. And they're spending all of their time trying to understand, do you have the right alpha sources? Are they advanced enough? Are they sophisticated? Do they differ from your competition? And, you know, that guy over there, they also have PPP factors. Well yeah, those alpha sources risk factors, yes they're important, obviously they're very important, but risk and portfolio construction respectively contribute to the same degree to defining the results.
I would say spend 1/3rd of your time trying to understand what we do on the alpha side. The other 1/3rd you should spend on risk management, and the other 1/3rd you should spend on understanding our portfolio construction. Because it is a combination that yields the final result, and in each of those areas I would say you will find differences between what we do and what a lot of other people do. Some people may have almost the identical set up when it comes to alpha factors, but in all likelihood, and to my knowledge they would differ in either or in both the portfolio construction and risk management, etc., etc. As you mentioned, position sizing, that's one area where we do things different from most of the investing community when we say that we want positions that are principally proportional to the perceived opportunity.
Another area where we're different, clearly, is the way we construct the final portfolio by way of transitioning signals into positions. Most people would use some form of more or less traditional optimization scheme that they are in the middle, and they would, for the most part, make use of the correlation structure when they construct their portfolio and here's where we differ. We don't use the correlation structure, and to exemplify: if you have positive views on both the Australian and New Zealand dollar, and we know they're strongly correlated. It is relatively likely that any traditional or almost traditional optimization scheme would like you to short one and to go long on the other due to the correlation structure. This is from the method wrong, we believe, for a couple of reasons, A) it will have a positive view on two assets, two currencies. We want to be long both, because we're not forecasting the correlation structure, and it would be fundamentally against our principles to short something we have a positive view on. B) That optimizer will, relatively often, push you into what is referred to as corner solutions, right? That means as something then changes over the next week or month; it is not unlikely to want to push you in the direction of another corner, and that will, if you take position based on that then, that will cause a lot of trading costs for you. You will change your positions quite a bit. Finally, if you do this shorting one going long on the other, your base concentration is going to increase quite a bit, and neither of these three are the sort of trades that we are very comfortable with. So indeed here, we don't use correlation structure, we transition signals into positions then when it comes to the risk overlay, then we're using the correlation structure.
Niels: It's very interesting because it seems to me that maybe unlike a lot of people doing relative value where I think to some degree they're trying to take out the volatility of their returns by doing relative value. What you're doing is saying we're doing relative value, but we're actually OK with having volatility in our returns because we can't remove volatility from inherently underlying assets that are volatile.
Anders: Yeah, that's an interesting observation. In other ways of looking at it is to say that the volatility that we get, and certainly some of the drawdowns that we and everyone else gets, they are the price you have to pay because you don't have obviously perfect insight. In our specific case, we believe that we have the right positions but the timing, we don't really know when the markets are going to start moving back to sort of a longer term equilibrium. So we have a problem of timing, and that's when we seem to say we start building positions, we increase positions as the opportunity increases to a degree, and meanwhile we're not happy, but we prepare to take the losses to build our position and we are happy to take, or we have to accept the associated volatility, because again we don't know where the market is going to turn.
Niels: Have you ever had to override the models?
Anders: Not the actual models. We wouldn't override the models in the sense that we would alter the positioning or such. What we can do, and we have done on occasion is that we can de-lever the entire program, and this is a measure that we would take after obviously careful consideration that risk management committee and it would basically be based on a view on the functionality of markets. So the best example here would be September, October 2008 when we de-levered quite a lot.
Niels: Now the next area and I probably won't spend too much time on it because you have already talked quite a lot about it which is great, and that is really risk management. I just have a couple of things I want to touch on, and that is how do you define risk? What to you is... what's a good measure of risk in your opinion, when you look at these types of strategies?
Anders: Well, there are sort of two answers to that, at least what we control for at a program level is actually the expected volatility. Inside the model, as I mentioned, we're limiting certain signal sizes, etc. This is based on tended drawdown, again really focusing on sort of tail behavior, which leads to expected shortfall type thinking. This is what we do. Now do I believe that expected volatility is really a good measure of risk, no I don't. What I would like to do, at some point, this is something that we talked about on and off for the past 8, 9 years, whatever, is really to start looking exclusively at the expected shortfall and really to build models up, I would take that and only that into account. The problem with that is that if you are targeting and controlling exclusively for expected shortfall the model may well find itself in a situation where it says the left tail is about 0 today, so I'm happy to trade a 40% or 50% expected volatility. So your volatility of your volatility is certainly on the upside of traditional volatility would increase dramatically, or has the potential to increase dramatically, and this is not something that would be immediately accepted by clients. So why we then target the expected volatility? Well, it is a measure, and for us it has actually worked, it is a measure to protect the model, because the model is very slow moving. The model is blind to political statements, central bank speak, etc., etc. and to sudden turns in the market, that cannot be predicted or measured by fundamental data. So the market model is slow moving, blind to a whole lot of things, so what we then need to do is to protect the model by using a method to pick up on peaks in, or dramatic or bigger increases in market volatility, because either way in a situation you have volatility it spikes.
Either we're in a position that we actually profit from that, in which case it's sensible to take some profit, de-lever a bit, and then wait for volatility to mean revert back down to start putting positions back on again. Nobody has ever gone poor by taking profit. So in those scenarios, it's probably a good thing. It could be that we come into a situation where we have the opposite positions. Where we actually lose too much on it, then it sort of resembles a bit of a stop loss. Because when volatility spikes we have wrong positions, then obviously we are going to start losing money, and the model will then start de-levering, so it will reduce sort of further loss of capital if you like. Unfortunately, it has the same characteristic as a stop loss. When markets turn back up again, because it will then have de-levered, so once markets start reverting back up again, it will come into that with too small positions. But that's the price to pay.
Niels: What keeps you awake at night, meaning what is the risk that you fear the most, because at some point there is obviously something that you can't guard against even with the most elaborate strategy and risk management, what would that be?
Anders: Generally speaking, I sleep very well. My wife would be the first to testify to that. But, what if anything would keep me awake at night...situations when markets quite apparently behave irrationally. Certainly when they continue behaving, and pretty much everyone would agree, they continue behaving irrationally for some time, because then we find ourselves in a situation where we cannot expect the model to act in a predictable fashion. Whether we make money or not, or lose money or not, is entirely random in such a scenario, and we're not in the game of sort of taking big positions, and we do take pretty significant positions in this program. It is not really built to connect on random behavior, and these scenarios they do occur from time to time - focus on something completely different.
Niels: Do you think the risk of markets behaving irrational, has that increased in the last few years with so much involvement from politicians and central banks?
Anders: I think most people looking at their life's trading experience at my age, we'd be talking about 20, 25 years, they would probably say that's true. On the other hand if you read whatever book on the topic and you go back to the Dutch tulip mania, or market crashes in the late 1800s, etc. I'm not so sure that market and investor irrationality has increased over time. I think we feel that at the current time, but that's only because our time windows too short.
Niels: I want to jump to the next topic just again, very briefly, it's about drawdowns. I want to ask you about what one should expect in terms of drawdowns from a strategy like yours? But I also want to ask you how you cope with being in a drawdown? I noticed that obviously your drawdowns are not that large, if I can put it like that, but the emotional roller coaster that we tend to go in if we are in a drawdown, especially if it's a deep one, but also if it's a long one, that's part of what's being hard I think about being in this business. I just want to ask you how you cope with these things emotionally and maybe that's not from a recent example, but maybe sort of over your career?
Anders: I think a main source of strength in these types of scenarios is that we are systematic. Had we been discretionary traders, and you would face some of the drawdowns that we have, then probably the August drawdown would have qualified for us losing the money that we had, we'd be on the prop desk almost immediately, or at least seeing it halved or whatever taken away. But as we are systematic, we have to seek comfort in the fact that we believe that the model is right, over time, we believe this is temporary and eventually it will come back. If we start tampering with the model, or we start adding to the de-levering by discretionary or measure, or such things then in all likelihood we're only going to make the situation worse. So, this is a program that we traded for a very long time. We put an enormous amount of manpower and brainpower into development of it. We believe it has proven itself, so the main thing here is really to seek comfort in the fact that we're systematic. This really comes down to one of the reasons for being systematic in the first place is to avoid exactly this emotional behavior. You will be most inclined to kill your positions just when it feels the most uncomfortable.
Niels: And this is often what investors do with the managers, in my experience, they often redeem right at the worst possible time, which is similar to us having a position or a period of negative performance. So the question is, Anders , and I know you've done, in my opinion, quite a lot of... and quite a unique way of bridging the gap, but how do we transfer this comfort and this belief that you have in your own system through the difficult times to the investors? Because I know you've got a special group of people inside your business working very closely with your investors in terms of transparencies. So is that the way forward, just being extremely open about it?
Anders: Yeah, I think so. We're the most comfortable when our clients have almost complete information. They know what we are doing. They know the model. They know how it works. We could go pretty far in that discussion with clients just to make them fully understand what it is we do, how we do it. Why the positions that we take, etc. I think that there is no alternative, really, for this type of strategy. We need investors that have confidence in what we do based on knowledge of what we do. That can only be accomplished by complete transparency. The more client dialogue, the more we have prior to initiation of a mandate and also ongoing, the better.
Niels: Absolutely. Now the next topic that I have is research, and now generally investors they want managers to innovate and come up with new things and evolve, but they don't really want them to change at the same time, which is sort of quite difficult. How do you balance these two things and what does research look like inside of IPM?
Anders: Well, I touched upon our frequency of changes just briefly earlier. Obviously we have to evolve the model. It has to improve. We have to add new components, but there's nothing built into it saying that we absolutely have to change just for the sake of it. What we are trying to do is to add where we find weaknesses; we have to add where we find interesting opportunities all within the same setup. So what we wouldn't alter is the fundamental way of doing things. We wouldn't take - to take something ridiculously extreme - we wouldn't take a trend following component and just add it, because it's outside of our self-imposed limitations on what we do philosophically. So there's going to be a few changes over time, but it's a gradual development and this really reflects the research process also, because the research process here is very, very thorough. It would be rare to find something newly introduced that hasn't been in the works for 6 to 18 months, at least 6. Just finding the right data sets, scrubbing all of the data, by the way it's starting even earlier, identifying what it is out there we think can fix whatever problem we have identified, coming up with a couple of ideas, identifying the prior assumptions that we want to lock away and measure the ultimate performance of this new thing against, to verify that it is actually doing what it was supposed to be doing, rather than just being a sort of general source of alpha. Then finding data that is reliable long term enough. We can't build something based on 3 or 4 years’ worth of data. It's got to be a long term history, and it's got to be clean data. Then building the model, testing it against all the other factors, all of this is very time consuming process.
Niels: Are there any particular interesting areas that you are looking at right now that you think could benefit you in the future? Without giving anything away, of course.
Anders: Then the short answer would be yes (laugh). There are a couple of areas. Generally speaking we're trying to broaden and deepen the model at the same time. So in terms of deepening the model, we'd be looking at new factors. This is probably less interesting for your listeners at this point. Broadening of the model - one good example is what we did last year, we introduced an emerging market currency model. What we're looking at right now is broadening the model by potentially soft trading fixed income curves or G curves explicitly. We do have commodities on the research agenda, although it's not the highest priority at the current time. In terms of risk management, as opposed to risk control, we're hard at work at the current time to be able to measure what sort of exposures we have in the dimensions of global risk factors. So what sort of data risk do we have? What sort of duration risk? What sort of inflation risk or exposures? All to just identify how we are exposed on a number of dimensions. Then in the next step, what and how can we do to control for that?
Niels: How do you make a back test meaningful, because there's never been a bad back test if you know what I mean? What is important when you look at the results from your research, and you look at the test of the model, what in particular are you looking for to verify and say yes, this is actually not just something that looks good, but is something that is robust? Because I get the sense that robustness is really important for you. How do you look at a back test and realize that this is pretty robust?
Anders: I think as a starting point we do what probably everyone else does, or in some instances claim they do, you test on a limited set of data. You lock away other sets of data, and then you verify your results by running on that part of the data that it didn't use to calibrate. Another aspect that we think is important is to not over calibrate and to not over engineer your model. One example of that would be that, as we mentioned earlier, we try to use as full of data sets a possible. We're not limiting ourselves to any particular window where their rolling short or long, generally speaking. Because it would introduce biases and it may amount to over engineering. That's also important, but I think in the end, the two most important things is to, I hesitate to use the words, scientifically but let's call it scientifically verify that your thesis is sound and robust. If you come up with a sound thesis and it's supported by theory, then yeah, if we have independent support and academic research, etc. etc. that this is sound and it is right, that's a strength.
Finally, trying to set up your assumptions and priors for the new factor. If we say that, I'm just going to use a bogus example: if we say that we've identified that our carry model is really bad. So then we set off identifying a new theory that we should be able to trade on. Then we need to verify that here's what we expect from it. It should pick up on carry. We should be able to verify that it picks up on carry. It should do X, Y, and Z. This is written down and locked away. Once we then build this factor and it's tested and calibrated and all of those things, then we need to take a look at the actual outcome. Does it deliver what we thought it was going to deliver from the very beginning? If it does, and it has passed all the other tests then it is probably a sound a robust factor. There's a good likelihood that it's going to be. If it doesn't, it may very well deliver strong alpha anyway, but if it doesn't then our hypothesis was actually wrong and then it shouldn't go into the model, at least not in that form and based on those results.
Niels: Now the business side of the firm, just a couple of things that I wanted to touch on, maybe not necessarily the usual questions that you get, but overall of course, you've done really well. The business is growing, and has grown a lot, but I want to ask you two different things, and that is "key man risk" - do you consider yourself as having a key man risk or have you managed to eliminate that also by being systematic, and the other thing I wanted to ask you about is, have you thought of or maybe even implemented some kind of business succession plan, even though I know you haven't even turned 50 but we need to consider these things from time to time?
Anders: I think there are, at least two aspects to key man risk that one should talk about. One of them is time, and the other one is probably confidence or perception. Given that we are fully systematic, given that there is a large number of people working on the models, etc. frankly speaking, if I or any other senior person in the firm were to walk out the door tomorrow, over the coming year to years at the very least, the firm is going to continue delivering pretty much the same results as one could have expected to deliver without those senior people having left. Over the longer term, you may have a question as to whether the organization or the remaining organization has the ability to continue developing the business and the models in the same fashion as earlier. But that means you, as an investor into this, shouldn't be too concerned about key man risk as it applies to the handling of your money in the shorter term. If X or Y or I or someone else senior were to leave today, you have a lot of time. You can sit down and take it quite calmly and evaluate the situation over the coming 6 to 12, 18 to 24 months and say hey, yeah, it seems that the organism is healing and repairing itself, or it's not. So there's no urgency in this.
The other aspect of key man risk, probable has to do with confidence and perception, and this is something that you cannot do anything about. Most investors out there, they would invest based on confidence in a number of senior people, frankly and if they leave then that confidence is gone and it's a process that will take a considerable time to rebuild for whatever people remain in the firm. So I'm sort of saying both yes and no. There is a key man risk, but I think if you look at the proper management and handling of client capital that's been entrusted to you, I think key man risk for this firm is not a big issue for you as an investor. You have a lot of time to evaluate the situation. You don't need to do anything immediately. You can sit down and evaluate over the course of several quarters before you take action. Succession plan, well not really, I know there's been a lot written about succession in hedge funds over the past few years, and I know a few of the investment banks have been writing analysis on this. I know of relatively few, personally, hedge funds that have successfully done this. The obvious well published example will be Caxton I suppose. There's no formal plan in place. On the other hand we just discussed the key man risk, and people can see what has happened at the firm, I've sort of left the day to day operative responsibility for day to day management of the firm, but I've certainly not left the firm.
Niels: No, No, and that is, in a sense a kind of succession planning. Last question on the business side I wanted to ask you. It's just that obviously you've had tremendous growth, but I'm sure it hasn't been necessarily plain sailing along the way, is there any challenges along the way that you can think back on as good example of things that was tough at the time, and sort of how you overcame them, or has it maybe been plain sailing all the way?
Anders: (laugh) I wish. No it hasn't. As with everything it goes up and down. I think one period in time when things didn't go the way we would have liked it to go was in 2011. We had this drawdown in August of 2011, or mostly in August of 2011. A lot of people started thinking, hey, is this reliable or is IPM indeed yet another of these systematic global macro traders that ultimately blow out. There's been a few of those examples. And in addition, my co-founding partner left the firm at the time. We worked together for a large number of years. He'd gone slightly more passive just prior to 2011, but in the end, late 2011 he more or less left the firm. He retained a position on the board, but not very active. So people held back given these changes and given the drawdown, people held back and we lost a couple of smaller accounts, but the losses aside, what it means is that your fund raising activities they're going forward, they do get delayed. So that's sort of disappointing, but to be expected.
Niels: Now you have obviously been in many, many meetings and due diligence and phone calls and had thousands of questions over the years, but what do you think is the question that investors should be asking you, but they never really do? Because you alluded to, earlier, that they all seem to be very focused on something trying to understand things that actually you didn't feel were so important, but what is really important for investors that they should be focusing and understanding do you think?
Anders: That's a tricky one. Again, over the past 15, 16 years I've had a very large number of questions. I honestly think you're touching really upon the most important part, I think people should really focus on trying to understand the components. You always get the questions, so how do you differ from your competitors. Well the competitors don't tell me what they do, so you're probably in a better position to tell me, for starters. I can't single out any one area, but you should take a more holistic view and look at the whole. How do all of these components that we're talking about contribute? How are they put together as a whole? Because what we're talking about is a system that is sort of purpose built to do just this, and all components have been tailored to fit this particular structure. We could principally have built these same alpha factors but traded instruments down the long, why don't we do that? So how do you put all the pieces together? It's like a puzzle, you may have excellent good looking pieces, shiny and all of that, but if they don't fit together, if they're not designed to fit together, than irrespective of how good the alpha sources are they're not going to deliver. So I think that's really critical, how do you put all of the pieces together?
Niels: Interesting. Maybe a little bit on that note, I'm just curious, sort of just spur of the moment here. If you were going to invest in another hedge fund, and maybe you do, but what would be the single most important thing for you to ask that manager? And I don't want you to go into any specific details, but just, you know, the hedge fund industry from the inside, so if you were going to invest with someone what would you focus on of all of the things that you could ask?
Anders: I'm not so sure I would focus on any one particular question. The most important thing for me would be to meet with the founder/the driving force in the company and really convince myself that this is a person that is sufficiently knowledgeable, and that my gut basically says I can trust. Is this a person that I would, irrespective of what he does, irrespective of the sort of strategy, I need to feel that this is a person that really knows it. That, same as we do, has put all of the pieces together in an intelligent manner, and for me also, he or she needs to prove that this is repeatable and why is it repeatable.
Niels: It's really interesting that you say that, Anders , because I think that those qualities that you mentioned there are probably completely lost in the normal due diligence right now, where maybe one or two analysts come out, they sit with you for not enough time, they ask standard questions, they use a tick box mentality where it's actually not so much about the gut feeling and the personal, it's more about do they fit these boxes, and then they have to convey it in a report to people who have never met you, or the manager and try to convey these important and which is quite sort of personal and emotional things, that I agree with you is really the important part. Because at the end of the day, whether you are systematic or not, investors buy people, it's the people behind it, so by hearing you saying that I feel strongly, interestingly enough, which is partly the reason why I do these pod casts, is for people to connect with the manager - hear the passion and get a feel for the person rather than just a written due diligence questionnaire. Interesting point.
Anders: With a firm like ours, obviously the person and the staff who's working here. Obviously I cannot go so far as to say that all of our clients spend too much time on, or focus on DDQs but indeed it has become a bit of a science or pseudo-science, if you like, where you tick all of the boxes, you do your own DD then you hire a consultant who comes and does his DD and they also tick the boxes, and then you know you just put it together. But as you and I touched upon, I think there's too little focus on (let's call it) the human aspects.
Niels: Last section, Anders. We're on the home stretch now. I call it general and fun, so it's a little bit about not specifically to your strategy, but just generally sort of what do you think now a days it takes to become a great fund manager or trader? What are some of the personal traits, as we alluded to before, these are the things that we look for in making a decision or in making a connection with someone. But what are the things that, what does it take now a days to become a great manager such as yourself?
Anders: I think the world as evolved quite significantly since 1998. Just one observation very sort of anecdotal, 15, 20 years ago you could start a hedge fund with coming out of a prop desk, or whatever, having a great strategy. You rented an office at Blumberg, two guys, and you got on with your trading with a couple of million dollars you may have got seeded 20, 25 and you could actually build a business from that point. Whereas today, the market has gone so crowded. The regulatory requirements are so high that if you don't start pretty much with a full setup of people and that may be anywhere from sort of 6, 7, 8 people up to 15, 20, with seed or starting capital in the order of magnitude of 100, 200 million dollars, then it's going to be very, very difficult for your business to take off, irrespective of how good your strategy actually is, and how smart you are, unless you have a confers event, you're coming out of a bank, and they actually gave you a couple of hundred as a parting gift, or you're being one of the sort of tiger cubs and you get seeded by Mr. Robertson himself, or such, but those would be the rare exceptions. In addition to start something today, given all of this, requires probably a lot more hard work, and probably a lot more discipline than was actually required 20 years ago.
Niels: And luck, I guess.
Anders: Luck is always there. You can help yourself to some luck too.
Niels: Yeah, yeah, the harder you work the luckier you get, as they say. Is there any personal habits that you have that you think have contributed to your success. We know that people like Ray Dalio puts a lot of emphasis on his daily meditation practices being a part of his success. Do you have any personal habits that you do that you think are important?
Anders: It's very hard. You should probably ask my wife. I think, generally speaking, and whether I'm better than most at this or not I'm not sure, but generally I am relatively disciplined. When I started taking up running and stuff again, a few years back I actually get out of bed a 5AM and do this because that's the only time of the day that I am 100% sure that I actually have the time to do it. So I have got nothing better to do - well, obviously sleep - I've got nothing else to do at that time - a little bit more probably than average discipline I would say, that's very helpful.
Niels: What's the most difficult thing that you have to deal with as a hedge fund manager today, do you think?
Anders: There's any number of things you can mention, ranging from the ever changing regulatory environment which is that sort of technical, that's principally a problem that you can solve by way of throwing money at it. What you cannot solve though, that is related to regulatory but that is also related to sort of perception and other things that's sort of on the investor side, where, if you are looking at the Dutch market as an example, where investors have, I wouldn't necessarily say being squeezed out of the hedge fund market by the regulator, but close to it, very close to it. That's very hard, how can we be without. We simply have to go to another market, and we have to start afresh in building trust and confidence with investors in other markets.
Niels: That's very true. On one hand you're a successful fund manager, on the other hand, you’re also an entrepreneur. You built a business from scratch; did you always have the entrepreneurial gene inside you? Did you know that one day I want to have my own business?
Anders: I couldn't say I've always known that. On the other hand, I probably could say that I have probably always been a non-optimal employee, and over the past 15, 20 years I probably have become even worse as an employee. I do like to do things in my way, and I do like to push things in the direction that I obviously prefer. Having said that, this is the one and only company that I've ever started up, so I couldn't very well call myself sort of a serial entrepreneur, or actually experience entrepreneur. There are a large number of people that started more.
Niels: And almost at the end. I ask my guests whether there is a fun fact that they can share about themselves. Something that even people who might know you don't really know about you, is there anything that springs to mind?
Anders: Well, I don't know how fun it is but, I tend to think about, probably about in excess of probably 75% of my valuable insights and ideas; they're actually generated between the time I wake up each morning and the time I step out of the shower. I actually read a book on a related topic just a couple of years ago, and it turns out the human brain actually works a bit much that way, but some people prefer evening times, I strongly prefer morning times. So I even have materials in the bathroom to take notes.
Anders: How fun it is I don't know.
Niels: I think it's pretty fun, but you know. Last question to you Anders, I said earlier to you that investors may not be asking the right questions. They fail to ask certain important questions, but what about today, what have I missed in our conversation and what questions should I have asked that I didn't?
Anders: We talked for 2 hours 20 minutes, (laugh) so you covered quite a lot of ground.
Niels: As long as I've done you justice and IPM justice.
Anders: Yeah, we talked a whole lot about business development and stuff, that's our doing, that's not necessarily too interesting for your listeners. We can take another 2 hours 20 next year and go to the bottom with certain things.
Niels: Now, before we finish, what's the best place for people listening to this, where can they reach and learn more about you and IPM.
Anders: Well the best way is actually to get in touch with us, and that's very, very simple, contact us via our web site, which is IPM.se and someone will be in touch with you.
Niels: Let me say to the people listening today that, for those of them that are on the mailing list, there is a link in this week's email, and you can just click that link to say thank you to Anders. Thanks for sharing his story, his expertise and I really do encourage everyone to do that, so let me be the first, Anders, to say thank you so much for all of your time. It's been fantastic conversation. I really appreciate your transparency and your willingness to share these insights and views on your strategy and your firm, and some personal stuff as well. So that's been amazing. I really appreciate that.
Anders: Thank you very much Niels. It's been a pleasure. It's rare to have such a conversation over 2 1/2 hours, almost, an interview with such insights into the business in general, so highly appreciate it, thank you.
Niels: Fantastic. Thank you so much and of course, the listeners can also find all the details that we've talked about today in the show notes on TOPTRADERSUNPLUGGED.COM. I hope we can connect at a later stage, Anders, and get an update on all of the great things happening in your firm.
Niels: Take care and all the best.
Ending: Thanks for listening to Top Traders Unplugged. If you feel that you have learned something of value from today's episode, the best way to stay updated is to go on over to iTunes and subscribe to the show so that you'll be sure to get all the new episodes as they're released. We have some amazing guests line up for you, and to ensure our show continues to grow, please leave us an honest rating and review in ITunes. It only takes a minute, and it's the best way to show us you love the podcast. We'll see you next time on Top Traders Unplugged.
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Date posted: 21 Aug 2014no comments