Asset Pricing with Extreme Liquidity Risk

Thursday, January 31, 2013 ( 3:00 pm to 4:00 pm )

Location: Babbio 430

Asset Pricing with Extreme Liquidity Risk

Ying Wu, Ph.D. candidate, Cornell University



Defining extreme illiquidity as the tails of illiquidity for all stocks, I propose a direct measure of market-wide extreme liquidity risk and find that extreme liquidity risk is priced cross-sectionally in the U.S. equity market. From 1973 through 2011, stocks in the highest quintile of extreme liquidity risk loadings earned value-weighted average returns 6.6% per year higher than stocks in the lowest quintile. The extreme liquidity risk premium is robust to common risk factors related to size, value and momentum. The premium is different from that on aggregate liquidity risk documented in Pástor and Stambaugh (2003) as well as that based on tail risk of Kelly (2011). Extreme liquidity estimates can offer a warning sign of extreme liquidity events. Predictive regressions show that the extreme liquidity measure reliably outperforms aggregate liquidity measures in predicting future market returns. Finally, I incorporate the extreme liquidity risk into Acharya and Pedersen’s (2005) framework and find new supporting evidence for their liquidity-adjusted capital asset pricing model.



Ying Wu is currently a Ph.D. candidate in Economics, Cornell University. She has an M.A. in Management Science and Engineering, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, and a B.A. in Economics, Peking University.

Her research interests include asset pricing, international finance, and financial economics.


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