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Mathematical Finance and Probability Seminars

Estimating Asset Pricing Factors from Large-Dimensional Panel Data

Tuesday, November 01, 2016 at 11:45am - 12:45pm

Markus Pelger, Stanford University: We develop an estimator for latent factors in a large-dimensional panel of financial data that can explain expected excess returns. Statistical factor analysis based on Principal Component Analysis (PCA) has problems identifying factors with a small variance that are important for asset pricing. Our estimator searches for factors that can explain both the expected return and covariance structure. We derive the statistical properties of the new estimator based on new results from random matrix theory and show that our estimator can find asset-pricing factors, which cannot be detected with PCA, even if a large amount of data is available. Applying the approach to portfolio and stock data we find factors with Sharpe-ratios more than twice as large as those based on conventional PCA. Our factors accommodate a large set of anomalies better than notable four- and five-factor alternative models.
Location   Hill 705

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Mathematical Finance Master's Program

Department of Mathematics, Hill 348
Hill Center for Mathematical Sciences
Rutgers, The State University of New Jersey
110 Frelinghuysen Road
Piscataway, NJ 08854-8019

Email: finmath (at)
Phone: +1.848.445.3920
Fax: +1.732.445.5530