원문정보
초록
영어
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 for Kyle’s (1985) lambda for a comprehensive sample of NYSE/AMEX and NASDAQ 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.
목차
1. Estimates of Kyle Lambdas
1.1 The Link between Kyle Lambdas and Illiquidity Pricing
1.2 An Illiquidity Measure Without Noise in the Information Signals
1.3 An Illiquidity Measure with Noisy Information Signals
1.4 Estimation of the Illiquidity Measures
2. Methodology
3. Data,Definitions, and Descriptive Statistics
4. Empirical Results
4.1 Features of the Portfolios Formed on Illiquidity and Size
4.2 Cross-Sectional Regressions
4.3 Robustness Checks
5. A Horse Race with Alternative Measures
5.1 Selection of Alternative Measures and their Relations to the Theory-based Illiquidity Measures
5.2 Cross-Sectional Regressions with Alternative Illiquidity Measures
6. Conclusion
References
Appendix: Derivation of the Two Theory-based Illiquidity Measures