The arbitrage argument extends to the case of many risk assets: the equilibrium leverage ratio will vary with the riskiness of the asset backing up the loan and variations in leverage will then substitute for variations in the interest rate. However, it can readily be shown along the lines of [Vernon L.] Smith that competition in leverage terms would be insufficient to correct the inefficient allocation of claims produced by the market when the interest rate is fixed.4

We infer motives for trade initiation from market sidedness. We define trading as more two‐sided (one‐sided) if the correlation between the number of buyer‐ and seller‐initiated trades increases (decreases), and assess changes in sidedness (relative to a control sample) around events that identify trade initiators. Consistent with asymmetric information, trading is more one‐sided before merger news. Consistent with belief heterogeneity, trading is more two‐sided before earnings and macro announcements with greater dispersion in analyst forecasts, and after news with larger announcement surprises. We examine the codeterminacy of sidedness, bid‐ask spread, volatility, number of trades, and order imbalance.

This paper models an individual's trading decision, given: (1) his/her demand function to hold shares of an asset, (2) his/her expectation on what the market clearing price will be, and (3) the design of the market which determines how orders will be translated into trades. The particular market design we consider is the batched trading (periodic call) regime. Assuming investors are distributed according to their propensities to hold shares, we model the aggregation of orders to obtain market clearing values of price and volume and to show the way in which, with trading friction, these solutions differ from Pareto efficient values. The importance of this analysis for various issues concerning market design is noted.

We present resiliency as a measure of liquidity and assess its relationship to expected returns. We establish a covariance-based measure, RES, that captures opening period resiliency, and use it to find a significant nonresiliency premium that ranges from 33 to 57 basis points per month. The premium persists after accounting for an extensive list of other liquidity-related measures and control variables. The results are significant for both value-weighted and equal-weighted returns, when micro-cap stocks are excluded, and for a sample of large cap stocks. The premium is particularly pronounced when trading volume is high.