An investment process that used artificial intelligence with no human involvement outperformed during a bear market and in the early stages of a recovery, according to an experiment conducted by Ryan Pannell, who runs investment firm Kaiju Worldwide.
Pannell said that while strategies which deploy machine learning tools have long existed, usually branded as “quantitative”, he said the limitation of these strategies was that humans tended to be excessively influenced by previous data and their own experiences, and these inputs can prevent the full value of the artificial intelligence being felt, “as what happens is the human builds a set of static rules for the AI to operate within, but that tends to mean the full potential of the machine learning is not harnessed.
The other issue is that quant strategies tend to be based around back testing, ie looking at how they would have done in previous market conditions, and from there, a static set of rules end up being created.
He says the key value that an AI can add is the ability to recognise patterns in how stocks are being bought and sold.
Pannell said the limitation of AI was that it "can’t creatively come up with a solution to something it hasn’t seen before, but it can adjust".
When he ran an AI programme to invest in US stocks, for example, it missed the sell-off in US bank shares caused by the collapse of Silicon Valley Bank.
He said this was because the machine could not understand the reason for the contagion impacting other bank shares, and so could not immediately understand why they were selling off, instead mis-identifying the sell-off as an opportunity to “buy the dip”.
Over the longer time period, Pannell said AI strongly outperformed in bear markets, losing around 20 per cent, when the US index dropped 35 per cent.
He believes the reason for this is that in a profound bear market, “stocks are sold off because sentiment is so negative, so even if there is no reason for a stock to fall, it will do, and that’s something an AI system can’t really understand".
"But the gains it makes will come, just as sentiment hits the bottom, and the market starts to recover, because that’s when, if a stock falls, it is easier to understand why it might be falling for the wrong reason, ie it might be artificial over-selling. That is really where the value is added by AI."
david.thorpe@ft.com
