Irene Aldridge has co-authored research on interpreting artificial intelligence and building trading strategies from data. A draft of the working paper can be found on SSRN.
Abstract: We show a simple way to let the data speak for themselves. Specifically, we show how a large mixed bag of data, potentially embedded with missing data points and collinearities, and therefore unsuitable for traditional econometric analysis, can be useful in building fast and meaningful big data and artificial intelligence analyses and predictions. What’s more, our technique helps the results of the analyses to be easily interpreted by researchers. We use these techniques to build a surprisingly profitable E-mini crude oil futures trading strategy with monthly reallocations, delivering annualized returns of 100%+ with Sharpe ratio exceeding 2.2.