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Abstract "The seminal literature on liquidity (Garbade (1982), Kyle (1985), and Harris (1990)) identifies three main dimensions of liquidity: spread, depth and resiliency. While there has been extensive research focussing on spread and depth, there has been little empirical investigation on resiliency, even though resiliency addresses an important question: when trades, especially those resulting from relatively large and uninformative orders, change market prices and lead to temporary pricing errors, how fast are these pricing errors eliminated through the competitive actions of value traders, dealers and others market participants. This paper investigates, for the first time, the main features of resiliency as a dimension of liquidity, and its effect on stock returns. Using minute-by-minute data for a sample of 100 NYSE stocks, resiliency is empirically estimated for each day for each stock as the observed mean-reversion parameter in the stock’s pricing-error process based on Kalman-filter estimation techniques. These estimated resiliencies are utilized to document several interesting results. First, the micro-structural time-series and stock-specific factors that affect resiliency are analyzed and it is found that trading activity, tick size, information asymmetry, and the stock’s unexpected intra-day volatility are all significant determinants of resiliency, and in the expected direction. Second, although these determinants are also related with spread and depth, resiliency is only weakly related with these two other price and quantity dimensions of liquidity, and provides significant new information on market quality as the time dimension of liquidity. Third, there is strong evidence of commonality in time-varying resiliency across the market, in the same manner as other is in the other dimensions of liquidity. Finally, and importantly, we find strong evidence that resiliency is priced in the stock’s required rate of return."

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