Trade-Offs in the Design of Financial Algorithms

We investigate trade-offs when trying to encourage adoption of stock-trading algorithms. We organize an artificial stock market experiment over three weeks where investors experience trading on their own and with the help of a financial algorithm.They then choose whether to adopt it. We vary the algorithm in terms of its trading strategy and whether its decisions can be overriden or not. We find that adoption rates are low, but investors are more likely to adopt an algorithm that trades actively and that they can override. The investor’s trading preferences, as revealed by their own trading decisions, does not consistently affect algorithm take-up. Rather, algorithm adoption depends mainly on how successful a trader was when trading on their own vs. when an algorithm was trading in their place. Analysis of an exit questionnaire matches those observations with the reasons given by individuals for rejecting or adopting a financial algorithm