Hedge funds embrace machine learning, but humans are still in charge
Man AHL chairman Tim Wong backs machine learning techniques, but says there’s still a role for humans
Machine learning has become the topic de jour for hedge funds, but while Tim Wong, chairman of Man AHL and Man Group Asia, says they have had some success using such techniques, he doesn’t expect to put his feet up and leave all the decision making to machines just yet. What’s more, he warns that there are dangers that come from leaving humans totally out of the picture.
The term machine learning is a broad one, but generally refers to a range of algorithms that can identify repeatable patterns and relationships within data, and which, more importantly, can do so without having to be told explicitly what kind of patterns and relationships to look for. Once they have been “taught” what is the right kind of answer, they are able to find the best way of getting there themselves.
When it comes to hedge funds, the idea is that with a vast quantity of historic data available, algorithms are better able than humans to find patterns of behaviour in markets that offer investing opportunities. Already, human are becoming aware of their cognitive limitations. Fifty-eight per cent of respondents to a recent KPMG survey of hedge fund professionals said that they believed artificial intelligence machine learning would either have a medium or high impact on the way funds are managed in the future.
“While the term ‘machine learning’ is fairly new, the ideas behind it go back many years, and I remember using some of the techniques when I was an undergraduate,” Wong said.
“What has changed is that the available computing power is far greater now than it was, while thanks to the internet there is also far more available data.”
