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independent things would react in the same way to an event.
In response to those kinds of increasing correlations in the markets and increasing propensity for shock effects we – both Aspect and as an industry – began to look for sources of diversification. Once you start to diversify, obviously markets is one axis and time scale is another, but once you start putting in other models, then how you bind them together, and that admixture becomes super, super, super-important. I’m sure this is kind of obvious. It’s been an area that we’ve focused a lot on. How do you put them together carefully? How do you make sure that you constrain, because just the simple thought experiment: if I take two models which have zero correlation between them and I leverage them up to achieve the same standard deviation of returns as one model on its own, well hurrah! I’ve just improved my returns, but I’ve also let the kurtosis creep out. It becomes increasingly important as you make the portfolio more complex that you deal explicitly with all of the edge cases – the risk management edge cases. That’s actually stood us in good stead as the markets have gone really into strange places since 2009.
NKL: Since you mention that, what have you learned in these last few years in terms of trading and systematic models and how the environment plays such a key role in all of this?
ML: I’m making note to come back to a question you asked earlier, but, oh gosh, this environment has had a... we could spend another session talking about this. Clearly in a period of underperformance for the strategy, we can... it’s human nature, why is it underperforming? What’s going wrong here? Ah, I invested in you, Marty, because I saw your 2008 performance, what are you doing? Have you all saturated the markets? Have market dynamics changed? Has trend following stopped working? It’s all of those questions, again, and you just hit the nail on the head. I don’t want to appear glib, so of course we investigate all of those things. We look at both our market footprint and what we think is the footprint of our entire industry to satisfy ourselves that we’re not... this isn’t shooting ourselves in the foot that’s happened here. We look at the low-volatility environment and what that is likely to do to both the opportunity set and to the risk management challenge.
It’s been a trying time, but then I guess in one sense I’m fortunate or cursed with having lived through periods like this before. After 1987 – a lot of parallels. There was a great... after the October crash of 1987 there was a huge run-up. Managed futures delivered its crisis alpha. We delivered our crisis alpha, and it went roaring profitable into 1988 and then basically hit the doldrums. The analogies
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between then and now in terms of recession, savings and loan crisis... remember that one? Government intervention, managing the yield curve, suppression of risk appetite – a lot of similarities. You’ve got to dig and scratch a little bit at the AHL track record, but it took from the high in the middle of 1988. I don’t think AHL was back in new highs until some time in about 1993 or 1994.
It was a similar length to the doldrums that we’ve been in here. It actually didn’t end neatly. It wasn’t just a sort of pleasant recovery of favourable returns. Just when you thought things were getting better we got kicked in the teeth by a surprise rate hike in 1994. But that sort of presaged... it almost felt like the tubes had been cleared, and the starting gun went off and the markets returned if you will, to some sense of normality, whatever your impression of normality is, and there was a great round of performance. I’m not predicting that, but what I’m saying is that I draw comfort from having been through it before that actually, provided the models are able to adapt to the fact that no two days are going to be the same, and you know that’s the beauty of what we do, because it’s not scenario- specific, so the models can adapt to whatever the markets present, number one. It does speak to the persistence and having confidence in the approach.
NKL: I think the other thing that people should do if they want to satisfy themselves about why these strategies shouldn’t actually have made money in the environment we’ve just been through is just look at the price range compression that we’ve seen. Just looking at what’s the high and low been for the last rolling three, or six-month basis, it is so clear what happens to the prices a few years back and when you do trade momentum and the price ranges compress as they have done, it’s very easy to visually see that we shouldn’t be making money. So it’s very interesting, and I completely agree with everything that you’ve said.
ML: Niels, the thread that I forgot there was just it reconfirmed my belief that a systematic approach is... I mean horses for courses. There are some great macro traders but I can tell you I’m glad I do what I do rather than be a macro trader, because how many times do you think folks have said, “Well, yields can’t go any lower than this.”
NKL: Tell me about the Aspect Diversified Programme today. How does it look, and sort of visually what does it look like?
ML: Well, I’m just going to tie in one other piece to an earlier question. By and large it has been very much a gradual evolution. If I look back, I think that the focus on risk management both as an activity in the business and as an implicit component to how we
build it and put it together and run it. That’s been a major feature of how the programme has evolved. The other thing is, actually, in the period of 2004, 2005, where the trend capture models transitioned from a binary implementation if you will, to an analogue implementation, and that’s interesting.
NKL: Can you explain that a bit?
ML: I think about break-out models: typically either your model is a long, short or out. The way we predominantly implemented, again there were varieties on this, but the early AHL and early Aspect models were a range of binary models across a range of different time scales. So that meant that as you’d scale in and out of a trend, you would trade in discrete chunks. So a model would essentially flip its sign, which meant that when that trade was delivered it sort of came out as a belch of a considerable amount of trading. We thought little of it, because that’s the way we had always done it. By 2004, in particular, a couple of trends converged, or effects converged. Number one, actually Aspect was doing reasonably well. We had had a run of good performance. We had managed to raise assets, so I think we were a fairly sizeable account for many of our brokers and market makers and when we’d hit one of those discrete trading points, I’m sure it was a very attractive piece of flow. So first of all we were noticeable. Secondly, there was an era of… I want to highlight in the FX markets that this was the era of disintermediation of the interbank market, do you remember that? As it became more democratized and everyone had access to the same price feeds, well the bank trading desks had to make a living and spent time understanding our models. So back to the early point about being picked off. What that told us was that we just had too much of a market impact. We were too visible to the markets, so around that period these were the same effects we were capturing, Niels, but in a different way that meant that our entry and exit to the markets was much, much, smoother and effectively invisible. THFJ
Part 2 will be published in the next issue. Listen to the full interview at
www.toptradersunlugged.com
ABOUT
TOP TRADERS UNPLUGGED PODCAST Top Traders Unplugged is a podcast created for the investor, trader or research analyst. As in the Market Wizard books, each week in Top Traders Unplugged Niels Kaastrup-Larsen talks to a current successful hedge fund manager or commodity trading adviser who shares his or her experiences, successes, and failures.
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