Bio


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: statistical learning in high-dimensional financial data sets, stochastic financial modeling, and high-frequency statistics. His most recent work focuses on developing machine learning solutions to big-data problems in empirical asset pricing.
Markus' work has appeared in the Journal of Finance, Review of Financial Studies, Management Science, Journal of Econometrics and Journal of Applied Probability. He is an Associate Editor of Management Science, Digital Finance and Data Science in Science. His research has been recognized with several awards, including the Utah Winter Finance Conference Best Paper Award, the Best Paper in Asset Pricing Award at the SFS Cavalcade, the Dennis Aigner Award of the Journal of Econometrics, the International Center for Pension Management Research Award, the CAFM Best Paper Award and the IQAM Research Award. He has been invited to speak at hundreds of world-renowned universities, conferences and investment and technology firms.
Markus received his Ph.D. in Economics from the University of California, Berkeley. He has two Diplomas in Mathematics and in Economics, both with highest distinction, from the University of Bonn in Germany. He is a scholar of the German National Merit Foundation and he was awarded a Fulbright Scholarship, the Institute for New Economic Thinking Prize, the Eliot J. Swan Prize and the Graduate Teaching Award at Stanford University. Markus is a founding organizer of the AI & Big Data in Finance Research Forum and the Advanced Financial Technology Laboratories at Stanford University.

Academic Appointments


Honors & Awards


  • Reid and Polly Anderson Faculty Fellow, Stanford University (2015)
  • Eliot J. Swan Prize, Department of Economics, UC Berkeley (2012)
  • Outstanding Graduate Student Instructor Award, UC Berkeley (2011)
  • Institute for New Economic Thinking (INET) Prize in Economic History, UC Berkeley (2011)
  • Scholarship of the German Academic Exchange Service, DAAD (2009)
  • Fulbright Scholarship, Institute of International Education (2007)
  • Scholarship of the German National Academic Foundation, Studienstiftung (2004-2009)

Professional Education


  • Ph.D., UC Berkeley, Economics (2015)
  • Diplom, University of Bonn, Mathematics (2012)
  • Diplom, University of Bonn, Economics (2009)

Current Research and Scholarly Interests


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: statistical learning in high-dimensional financial data sets, stochastic financial modeling, and high-frequency statistics. His most recent work focuses on developing machine learning solutions to big-data problems in empirical asset pricing.

2022-23 Courses


Stanford Advisees


All Publications


  • Estimating latent asset-pricing factors JOURNAL OF ECONOMETRICS Lettau, M., Pelger, M. 2020; 218 (1): 1–31
  • Understanding Systematic Risk: A High-Frequency Approach JOURNAL OF FINANCE Pelger, M. 2020

    View details for DOI 10.1111/jofi.12898

    View details for Web of Science ID 000531023800001

  • Factors That Fit the Time Series and Cross-Section of Stock Returns REVIEW OF FINANCIAL STUDIES Lettau, M., Pelger, M. 2020; 33 (5): 2274–2325
  • ON THE EXISTENCE OF SURE PROFITS VIA FLASH STRATEGIES JOURNAL OF APPLIED PROBABILITY Fontana, C., Pelger, M., Platen, E. 2019; 56 (2): 384–97
  • Large-dimensional factor modeling based on high-frequency observations Pelger, M. ELSEVIER SCIENCE SA. 2019: 23–42
  • Large-dimensional factor modeling based on high-frequency observations Journal of Econometrics Pelger, M. 2018
  • Factors that Fit the Time-Series and Cross-Section of Stock Returns Working paper Lettau, M., Pelger, M. 2018
  • State-Varying Factor Models of Large Dimensions Working paper Pelger, M., Xiong, R. 2018
  • Interpretable Sparse Proximate Factors for Large Dimensions Working paper Pelger, M., Xiong, R. 2018
  • Change-Point Testing and Estimation for Risk Measures in Time Series Working paper Fan, L., Glynn, P., Pelger, M. 2018
  • Contingent Capital, Tail Risk, and Debt-Induced Collapse Review of Financial Studies Chen, N., Glasserman, P., Nouri, B., Pelger, M. 2017
  • Optimal Stock Option Schemes for Managers Review of Managerial Science Chen, A., Pelger, M. 2013
  • New Performance-Vested Stock Option Schemes Applied Financial Economics Chen, A., Pelger, M., Sandmann, K. 2013
  • Contingent Convertible Bonds: Pricing, Dilution Costs and Efficient Regulation Working paper Pelger, M. 2012