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Bryan Kelly, Yale University and AQR - “Can Machines Learn Finance?”

 

Bryan Kelly’s Summary:

We synthesize the field of machine learning with the canonical problem of empirical asset pricing: Measuring asset risk premia. In the familiar empirical setting of cross section and time series stock return prediction, we perform a comparative analysis of methods in the machine learning repertoire, including generalize linear models, dimension reduction, boosted regression trees, random forests, and neural networks. At the broadest level, we find that machine learning offers an improved description of asset price behavior relative to traditional methods. Our implementation establishes a new standard for accuracy in measuring risk premia summarized by unprecedented high out-of-sample return prediction R2. We identify the best performing methods (trees and neural nets) and trace their predictive gains to allowance of nonlinear predictor interactions that are missed by other methods. Lastly, we find that all methods agree on the same small set of dominant predictive signals that includes variations on momentum, liquidity, and volatility. Improved risk premia measurement through machine learning can simplify the investigation into economic mechanisms of asset pricing and justifies its growing role in innovative financial technologies.

 

Bryan Kelly’s Bio:

Bryan Kelly is Professor of Finance at the Yale School of Management, a Research Fellow at the National Bureau of Economic Research, Associate Director of SOM’s International Center for Finance, and a consultant for AQR Capital Management, LLC. Professor Kelly’s primary research fields are asset pricing and financial econometrics. He is interested in issues related to volatility, tail, and correlation risk in financial markets, predictive methods in high dimensional systems, banking sector systemic risk, financial intermediation, and financial networks. His papers in these areas have been published in the American Economic Review, the Quarterly Journal of Economics, the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies, among others. He is an associate editor at the Journal of Finance and the Journal of Business and Economic Statistics. Before joining Yale, Kelly was a professor of finance at the University of Chicago Booth School of Business.  He earned a bachelor’s degree in economics from the University of Chicago, a master’s degree in economics from University of California San Diego, and a PhD in finance from New York University’s Stern School of Business. Kelly worked in investment banking at Morgan Stanley prior to pursuing his PhD.

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