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Akshay Krishnan: And on the second question about starting to invest in less liquid markets?

Stuart MacDonald: I don’t see that happening.

Oliver Prock: Right, I don’t see that happening either since CTAs do not just add a market for the purpose of adding a market. All these exotic markets are actually extremely illiquid and limited in terms of history.

Ewan Kirk: There are a few things to be said here. It sounds better to some investors to say we trade 250 contracts rather than we trade 70, but it’s not really changing your profile very much. If you are a big CTA, most of your risk is in the 10-year bond, the Bund, the Euro STOXX, the e-mini S&P and the euro. If you are smaller, you can afford to go into smaller things, and that’s ok. But if you are a large CTA, trading the rolled oats contract doesn’t move the needle. I don’t see a reason why CTAs shouldn’t trade less liquid things as long as liquidity-adjusted returns are not affected.

Oliver Prock: Well, actually I prefer being called a quantitative manager than a CTA.

Stuart MacDonald: I can give you a good alternative euphemism for the term, CTA...

Oliver Prock: Okay, I am curious! So, when CTAs get big, the commodity exposures will be lower, because that’s typically the illiquid stuff, as Ewan pointed out. I have a question for Akshay. In your multi-manager macro fund, are you just investing in discretionary traders?

Akshay Krishnan: As a macro fund of funds we look at both systematic and discretionary strategies but we don’t feel compelled to have fixed sub-strategy allocations between the two. We think of all our managers having the ability to add diversification to our portfolio. The decision to reduce our allocations to systematic trend-following strategies is a view we have had for the last 18 months, and it’s not something permanent. Further, it’s important to clarify that in our case it was also a bit more specific to one or two managers where we were uncomfortable with their levered positioning, and this obviously varies by manager. We have been investing in macro strategies since the late ‘80s as a firm, so we are very familiar with the space, but we don’t claim to foretell what the markets hold.

I think what I do worry about is when I talk to other allocators, a lot of people are using systematic trend followers as a hedge within their book, and I am just worried about how they are going to react when you have a replay or an inflection point like we had last May and June, because it’s something that’s


Oliver Prock: I think I can answer this from my perspective. We are a quantitative manager, and trading very sophisticated strategies. I have gained experience in the CTA space since the early ‘90s, and I have done all the mistakes you can do. The current environment is a conundrum. It is very hard to understand for discretionary traders. Typically, I receive a couple of questions from allocators like “if bonds would start to fall, would you adapt your trading model?”, and in our case the answer to them is: the model has run for 11 years untouched, so we think it is robust.

“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.” – Nacho Morais

But in any case, discretionary traders either need to adapt as well, or if they are not able to then they need to drop out. So why would it be bad to adapt a model? But as I said, in our case we believe we have a robust model for all market environments. So in fact we did not need to adapt the model, but what we had to change was the way we approach execution and slippage. We needed to make sure to not lose any alpha through execution.

Akshay, in your macro fund you invest in discretionary traders. I am having a hard time to find the ones that were really good, particularly during the last three or four years. With QE and all the central bank activity, the markets are in rather unchartered waters. When bonds go up, allocators

going to affect the entire industry, including macro in general. So it was just to throw out the question from that perspective.

want that we have bonds, right? So there is nothing wrong with making money in bonds when the price goes up, and I think there is nothing wrong to have a model that is robust and able to figure out when it’s the right time to short bonds. Having said that, our model forecasts prices and measures the forecast quality. It will short bonds definitely at the right point of time. However, I think it might take another year or so; who knows what the future really holds?

As a side note, I thought it was interesting hearing Ewan talking about Sharpe ratio. I thought physicists always say that the Sharpe ratio is a very stupid number.

Stuart MacDonald: People have a requirement to categorize things, and Sharpe is part of it.

Ewan Kirk: It’s not a bad measure of risk-adjusted returns.

Stuart MacDonald: It doesn’t have to work totally to be usable; there simply needs to be a common understanding of what it covers effectively and what it doesn’t.

Oliver Prock: We use a different measure of risk. It is called Conditional Drawdown at Risk and we optimize for that in one of our strategies. I actually think it is a good measure of risk, because it’s just focusing on drawdowns. We decided to focus on drawdowns since it is a number that actually matters for investors since nobody likes to lose money. If Sharpe is 0.7 or 1.1, this is secondary.

Coming back to the point whether models can adapt better to the environment or discretionary traders can. I have issues finding discretionary traders doing that. 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. As I mentioned, in our case we did not need to adapt the model, but we needed to get smarter in execution. If you have ever done a back-test, then you would have found that the price you input in your model is gone already due to lag 1 execution, i.e., on the next bar. But if you are able to get to lag 0 execution, i.e., on the same bar, your back-test or your trading will always be better than with a lag 1 execution, irrespective of what the model is. This is what we have basically done in our recent work. We have come as close to lag 0 as it is possible. And that really makes a difference in the current environment. We believe that execution is the part where some alpha is lost, which didn’t matter pre-crisis, but it definitely matters post-crisis, especially when the risk-free rate is at 0%.

Nacho Morais: I wanted to elaborate on something which we touched upon before, the fact that factor-

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