Best of TTU – The Importance of Asset Allocation & Patience

In 1987, 3 scientists, 1 from Cambridge and 2 from Oxford, were brought together by their shared passion for the markets and for computers.  Little did they know, that over the next 3 decades, this passion would lead them to build 3 world-leading multi-billion dollar Systematic Investment businesses.  Today, I would like to share another Golden Nugget with you, from my conversation with Michael Adam, David Harding and Marty Lueck, also known as the founders of AHL. In this post, we focus on how markets and the importance of Asset Allocation have evolved since the beginning; a crucial insight into what has made them so successful.  So enjoy these truly unique takeaways from my conversation with Michael, David and Marty, and if you would like to listen to the conversation in full, just go to Top Traders Round Table Episode 11.

The World's Biggest Neuron Network

Niels: Historically, at least, the role price of a market has been the only input in systematic models, certainly in the trend following space. The universe of markets have also been very well defined, being highly liquid, exchange traded, like futures on CME. Tell me, how have you evolved when it comes to the data you use and the markets you trade?

David: We trade a lot of equities and we use a lot of other data sources, basically.

Niels: What could they be?

David: You got me there. (Laughter)

Most of the risk is on endogenous variables like price, intra-relationships between markets, and various convolutions of price, sectors, and this sort of thing. Obviously, we have all the balance sheet data, all the fundamental data, all the weather data, there are all sorts of different types of data. We have a lot of experimental systems with small amounts of money on them. I expect we have one or two bigger allocations with key data inputs, but those I'm keeping to myself.

Niels: What about you Marty? Are you looking in new directions when it comes to data and markets? Maybe I can follow-up because that's my next point I want to ask, is about are you also moving off the exchange? What's the motivation for doing that and what are the risks you have to take into account if indeed you are?

Marty: Well, so the first question is data and the evolution of the trading programs. Of course, we have an appetite for new ideas, new influences on markets, new effects. As David says, "If we knew what the next big thing was we wouldn't tell you and it wouldn't be research."  I think there's a lot of hype these days with machine learning techniques and all this just explosion of new data sources that surely the answer is in there somewhere. If you just leave it to the folks at Google the answer will become immediately apparent. My view is it's a little bit harder than that. There's plenty of work to be done and there's plenty of opportunities. So, I'm not going to claim that we've got some fantastic new system that employs satellite data and engages recursive neural net and presto we know what's happening tomorrow and next week.

'I think all three of us have a healthy paranoia around operating in the markets, and that comes from the real experiences of thinking it was safe when it wasn't safe.'

So, no, it is overhyped. On the other hand, it is there. That data exists and there's more information out there than there's ever been, ever. You need to work out how to assimilate, how to digest and how to use that stuff.

David: One of the things that experience has taught all of us is danger of hindsight bias or over fitting to data sets. You saw this recently in a rich data set, or maybe 5 or 6 years ago. This Google Trends is a huge and rich new data set, obviously, a vast amount of data using Google's algorithm which forecasts when there are going to be flu epidemics. It made the front page of all the newspapers. It made the BBC News.