based strategies are basically the sale of a back-test. In this context, I wanted to focus on how over- reliance on some factors can be adverse, if you do not take into account other variables. For instance, certain parts of the value school are partially based on the fact that during the last 30 years, we have been in a decreasing rates environment. In this sense, many people have made the strategy of investing in bond-alike equities into the cornerstone of their career. The secular down-trend in rates has provided a huge tailwind for these strategies. The fact is that, at this point, this is not replicable any more, simply because we cannot have another 15% reduction in bond yields. So if we extrapolated raw performance data for that strategy, we would not be right.
Also dealing with the data, another dimension to be taken into account is the market participants. If you are looking at something that worked for a prolonged period of time and try to draw a trading strategy based purely on the data, you have to take into account that the market is different now, and that the participants do not operate in the 2010s as they did in the ‘90s. Back then in the ‘80s or ‘90s, systematic quantitative investing was about second-guessing how the fundamental investors were deploying money, but now you have a large portion of the market that is trying to apply those kinds of techniques. So, there is a phenomenon similar to multi-colinearity, as there is a larger proportion of participants trying to second-guess market behaviour in a market which is already heavily participated by second-guessers, and that creates some kind of noise.
From a commercial standpoint, I think that one of the key issues here is replication, defined as whether an investor can replicate the activity of a manager in a cheaper way. On many occasions, we have seen some long/short equity managers behaving like the index or like a very simple mutation of the index. You can even see that phenomenon at the most simplistic end of the systematic strategies, like a trend-following manager that follows just a raw moving average strategy. You probably do not need to pay somebody 2 and 20 or higher fees, for something that you can replicate with an index or with very simple code.
Ewan Kirk: That is true, but it’s not all about the models – it’s about the execution. We can all write down a nice, simple trend model, which in gross terms looks great and appears statistically indistinguishable from the best CTAs in the world, but that’s in gross terms. At Cantab, we execute 12 times a day with a lag of 0. The signal comes out and less than a second later we are starting to do execution at that price, and we are managing it, thinking about it and optimizing it to fractions of a basis point. A huge amount of effort goes into saving tiny fractions of a basis point. Again, it is all about the implementation.
The analogy that I use is that we all know how to make a table: it’s one flat piece of wood with four legs, and that’s all there is to a table. But neither you nor I can really make a table – there is a certain craftsmanship involved. Just because a simple trend- following model does well, it doesn’t mean that trend following isn’t worth money. It’s worth quite a lot of money. If I go back to my statistic earlier, one basis point a day translates into 2.5% per annum. If we can reduce our trading costs by one basis point a day, that pays for the entire management fee, and you get an extra 50 basis points back.
Nacho Morais: What I mean is that replication sets a boundary on the minimum net returns that a manager needs to provide. If I can take a simple trend-following model and a trading algorithm, and put it into an ETF, with very low costs, that would be the minimum benchmark that a manager that was to launch a trend-following fund has to beat.
Ewan Kirk: You probably assume that this ETF, with a simple trading algorithm, will cost you less than one basis point a day to trade. But more likely, it is not going to be one basis point a day. Simple trading algorithms don’t cost you one basis point a day, not across 100 different assets, with volatility weighting, execution at different times of the day, relative value execution – all of that is really hard to do. This means that this ETF is probably going to lose money, because it’s likely going to be paying around five basis points a day, which is 12.5%.
Nacho Morais: I agree with you, but you are focusing on the reality of your own specific implementation of the strategy, with your own expertise, size and trading frequency. Talking from the buy side, I can tell you that I come across much simpler models with poor execution being marketed to us. For instance, and I am not talking about something happening in 2005, but this very week, I got a call from someone who is setting up a fund that implements a very simple – directly observable – strategy, rebalances it every week, and puts it in a fund format.
I guess the point I am trying to make is that either from a fundamental or systematic standpoint, managers who are applying very plain-vanilla strategies, even if they make some money, can be beaten by something passive, either an index or a basic investment rule.
Ewan Kirk: Yes, of course. Probably everyone around this table has been beaten by something passive – by the S&P 500 last year. That was a nice, simple strategy. If you can get into a nice, passive strategy at the right time, then that’s a free strategy that can make you 30% a year, with no management fee, no performance fee. But you have to be able to pick that. THFJ
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“I think the best will always adapt, they will always be able to adapt, but the best are maybe 10% or less, not 90% of the discretionary trader bucket.” – Oliver Prock
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