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.