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Theory-Based Illiquidity and Asset Pricing Many proxies of illiquidity have been used in the literature that relates illiquidity to asset prices. These proxies have been motivated from an empirical standpoint. In this study, we approach liquidity estimation from a theoretical perspective. Our method explicitly recognizes the analytic dependence of illiquidity on more primitive drivers such as trading activity and information asymmetry. More specifically, we estimate illiquidity using structural formulae in line with Kyle's (1985) lambda for a comprehensive sample of stocks. The empirical results provide convincing evidence that theory-based estimates of illiquidity are priced in the cross-section of expected stock returns, even after accounting for risk factors, firm characteristics known to influence returns, and other illiquidity proxies prevalent in the literature.

We thank Craig Holden for providing us with the SAS code for the Holden-Jacobsen (2014) algorithm, Lee-Seok Hwang and Woo-Jong Lee for useful advice on estimating the model parameters, Amor Galvez at Thomson Reuters for providing valuable information on the SDC Platinum database, and Denys Glushkov at the Wharton Research Data Services (WRDS) for assistance in calculating the earnings surprise (SUE) measure. Research assistance was ably provided by Seung-Oh Han. All errors are solely the authors' responsibility.

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