The Risks of Using Investment Algorithms

The latest trend is to use algorithms to make as many decisions as possible. This article discusses the downsides of this approach, using Ray Dalio and Bridgewater Associates as examples. The article says algorithms aren’t as scientific and bias-free as their proponents would have use believe.

I saw the ease with which seemingly pure data could be biased when I worked at the hedge fund D.E. Shaw, where I created algorithms designed to make money in futures markets. In my group, we would periodically rate each other’s ideas along various metrics, such as their chances of working, how many countries they might work in, how long they might work and how much money they might make. The idea was to come up with an objective “expected profit” for each idea, based solely on its merits. If the score was high enough, it would be assigned to a quant to develop.

Yet certain people’s ideas inevitably carried added weight. Some proposals came from junior quants, while others came from the likes of Larry Summers, the former Treasury Secretary who worked at the fund in the 2000s. The ideas of men in positions of power naturally elicited higher marks: Maybe people gave them the benefit of the doubt because of the language they used, their reputation or even their body language. In any case, implicit bias that favored the alpha male was a real thing.