Wall Street is too complex to be left to humans

A paper from researchers at hedge fund AQR Capital Management and Yale University addresses one of the most important questions in finance: Will artificial intelligence and machine learning replace human researchers and traders? In 44 pages of densely written theory and empirical results under the title “The Virtue of Complexity in Return Prediction,” Bryan Kelly, Semyon Malamud and Kangying Zhao claim that more complex models — far too complex for humans to process — outperform simpler models. As Bloomberg News reports, the backlash was swift, with at leastsix papers challenging the findings., which Kelly has subsequently defended. How will this shake out? My money is on Kelly and his co-researchers. The theoretical arguments are dauntingly technical, but the basic question is ancient and easy to understand. One approach to prediction is to look for a few key indicators with clear casual links to the thing you want to predict and combine them in simple ways. To predict next month’s stock market return, for example, you might look at this month’s return, interest rates, pricWeiter zum vollständigen Artikel bei Korea Times Weiter zum vollständigen Artikel bei Korea Times