
Markus Pelger
Assistant Professor of Management Science and Engineering
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.
Honors & Awards
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Reid and Polly Anderson Faculty Fellow, Stanford University (2015)
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Eliot J. Swan Prize, Department of Economics, UC Berkeley (2012)
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Outstanding Graduate Student Instructor Award, UC Berkeley (2011)
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Institute for New Economic Thinking (INET) Prize in Economic History, UC Berkeley (2011)
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Scholarship of the German Academic Exchange Service, DAAD (2009)
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Fulbright Scholarship, Institute of International Education (2007)
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Scholarship of the German National Academic Foundation, Studienstiftung (2004-2009)
Professional Education
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Ph.D., UC Berkeley, Economics (2015)
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Diplom, University of Bonn, Mathematics (2012)
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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
- Financial Statistics
MS&E 349 (Win) - Investment Science
MS&E 245A (Aut) - Senior Project
MS&E 108 (Win) -
Independent Studies (4)
- Curricular Practical Training
CME 390 (Win, Spr, Sum) - Directed Reading and Research
MS&E 408 (Aut, Win, Spr, Sum) - Master's Research
CME 291 (Aut, Win, Spr) - Ph.D. Research
CME 400 (Aut, Win, Spr)
- Curricular Practical Training
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Prior Year Courses
2021-22 Courses
- Investment Science
MS&E 245A (Aut) - Senior Project
MS&E 108 (Win)
2020-21 Courses
- Financial Statistics
MS&E 349 (Win) - Investment Science
MS&E 245A (Aut) - Senior Project
MS&E 108 (Win)
2019-20 Courses
- Investment Science
MS&E 245A (Win) - Senior Project
MS&E 108 (Win)
- Investment Science
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Lin Fan, Xuhui Zhang -
Doctoral Dissertation Advisor (AC)
Junting Duan, Yang Fan, Sven Lerner, Greg Zanotti, Jiacheng Zou -
Master's Program Advisor
Mokshlakshmi Bhan, Nikhil Boddu, Wei Dai, Reynaldo Gomez, Luc Hudon, Michelle Lahrkamp, Lei Liu, Maximus Santosa, Rose Wang, Vincent Yeh -
Doctoral (Program)
Enrica Archetti, Lukas Fiechtner, Xueye Ping
All Publications
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Estimating latent asset-pricing factors
JOURNAL OF ECONOMETRICS
2020; 218 (1): 1–31
View details for DOI 10.1016/j.jeconom.2019.08.012
View details for Web of Science ID 000541723600001
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Understanding Systematic Risk: A High-Frequency Approach
JOURNAL OF FINANCE
2020
View details for DOI 10.1111/jofi.12898
View details for Web of Science ID 000531023800001
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Factors That Fit the Time Series and Cross-Section of Stock Returns
REVIEW OF FINANCIAL STUDIES
2020; 33 (5): 2274–2325
View details for DOI 10.1093/rfs/hhaa020
View details for Web of Science ID 000536040400009
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ON THE EXISTENCE OF SURE PROFITS VIA FLASH STRATEGIES
JOURNAL OF APPLIED PROBABILITY
2019; 56 (2): 384–97
View details for DOI 10.1017/jpr.2019.32
View details for Web of Science ID 000477856800003
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Large-dimensional factor modeling based on high-frequency observations
ELSEVIER SCIENCE SA. 2019: 23–42
View details for DOI 10.1016/j.jeconom.2018.09.004
View details for Web of Science ID 000454377800003
- Large-dimensional factor modeling based on high-frequency observations Journal of Econometrics 2018
- Factors that Fit the Time-Series and Cross-Section of Stock Returns Working paper 2018
- State-Varying Factor Models of Large Dimensions Working paper 2018
- Interpretable Sparse Proximate Factors for Large Dimensions Working paper 2018
- Change-Point Testing and Estimation for Risk Measures in Time Series Working paper 2018
- Contingent Capital, Tail Risk, and Debt-Induced Collapse Review of Financial Studies 2017
- Optimal Stock Option Schemes for Managers Review of Managerial Science 2013
- New Performance-Vested Stock Option Schemes Applied Financial Economics 2013
- Contingent Convertible Bonds: Pricing, Dilution Costs and Efficient Regulation Working paper 2012