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February 2018

Jose Menchero, Bloomberg: Solving the “Curse of Dimensionality” Problem in Multi-Asset-Class Risk Models

February 22 @ 12:30 pm - 2:00 pm
1011 Evans Hall Berkeley, CA 94720 United States + Google Map

Estimating a robust risk model risk for a portfolio that spans multiple asset classes is a challenging task due to the “curse of dimensionality” (i.e., the problem of estimating too many relationships from too few observations). While the sample covariance matrix is easily computed, it is susceptible to capturing spurious relationships that make it unsuitable for portfolio construction purposes. In this talk, we present a new approach for constructing risk models that span multiple asset classes. We also discuss the…

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March 2018

Kyong Shik Eom, UC Berkeley: The role of dynamic and static volatility interruptions: Evidence from the Korean stock markets

March 1 @ 12:30 pm - 2:00 pm
1011 Evans Hall Berkeley, CA 94720 United States + Google Map

We conduct a comprehensive analysis on the sequential introductions of dynamic and static volatility interruption (VI) in the Korean stock markets. The Korea Exchange introduced VIs to improve price formation, and to limit damage to investors from brief periods of abnormal volatility, for individual stocks. We find that dynamic VI is effective in stabilizing markets and price discovery, while the effect of static VI is limited. The static VI functions similarly to the pre-existing price-limit system; this accounts for its…

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Alec Kercheval, Florida State University

March 15 @ 12:30 pm - 2:00 pm
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Marco Avellaneda, NYU

March 22 @ 12:30 pm - 2:00 pm
1011 Evans Hall Berkeley, CA 94720 United States + Google Map
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Alex Shkolnik presents “The Dispersion Bias” at the Financial Risks International Forum in Paris

March 26 - March 27

The explosive growth in the area of data-driven risk factor identification elevates the importance of analyzing and, to the extent possible, mitigating estimation error.  Using random matrix theory, we show how a large, estimation-error-induced bias in the sample eigenvectors of factor-based covariance matrices affects portfolio construction and risk estimation.  We develop a bias correction approach for the first sample eigenvector which corrects the problems of portfolio construction and risk estimation.  Our approach is distinct from the regularization and eigenvalue shrinkage methods found in…

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Lisa Goldberg presents “The Dispersion Bias” at NYU

March 27 @ 5:30 pm - 7:00 pm

Abstract: Estimation error has plagued quantitative finance since Harry Markowitz launched modern portfolio theory in 1952.  Using random matrix theory, we characterize a source of bias in the sample eigenvectors of financial covariance matrices.  Unchecked, the bias distorts weights of minimum variance portfolios and leads to risk forecasts that are severely biased downward.  To address these issues, we develop an eigenvector bias correction.  Our approach is distinct from the regularization and eigenvalue shrinkage methods found in the literature.   We provide…

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April 2018

Rupal Kamdar, UC Berkeley

April 5 @ 12:30 pm - 2:00 pm
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Robert Anderson, UC Berkeley

April 12 @ 12:30 pm - 2:00 pm
1011 Evans Hall Berkeley, CA 94720 United States + Google Map
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John Wu, LBL

April 19 @ 12:30 pm - 2:00 pm
1011 Evans Hall Berkeley, CA 94720 United States + Google Map
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George Papanicolaou, Stanford

April 26 @ 12:30 pm - 2:00 pm
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