Prof. Dr. Markus Pelger // Department of Management Science  & Engineering // Stanford University

Markus Pelger is an Assistant Professor of Management Science & Engineering at Stanford University and a Reid and Polly Anderson Faculty Fellow. His research focuses on understanding and managing financial risk. He develops mathematical financial models and statistical methods, analyzes financial data and engineers computational techniques. His research is divided into three streams: stochastic financial modeling, high-frequency statistics and statistical learning in high-dimensional financial data sets. His most recent work includes developing machine learning solutions to big-data problems in empirical risk management and asset pricing.

Markus‘ work has appeared in the Journal of Finance, Review of Financial Studies, Journal of Applied Probability and Journal of Econometrics. He is an Associate Editor of Management Science and also referees for several journals in the fields of statistics, econometrics, finance and management. Markus received his Ph.D. in Economics from the University of California, Berkeley.

16:10 – Keynote: “Deep Learning in Asset Pricing“

Markus Pelger and his co-authors use deep neural networks to estimate an asset pricing model for individual stock returns that takes advantage of the vast amount of conditioning information, while keeping a fully flexible form and accounting for time-variation. The key innovations are to use the fundamental no-arbitrage condition as criterion function, to construct the most informative test assets with an adversarial approach and to extract the states of the economy from many macroeconomic time series. Their asset pricing model outperforms out-of-sample all benchmark approaches in terms of Sharpe ratio, explained variation and pricing errors and identifies the key factors that drive asset prices.