What Are The Best Liquidity Proxies For Global Research

TLDR: In this paper, the authors compare the performance of several cost-per-volume proxies to a cost-performance measure, namely the slope of the price function "lambda", and find that a new proxy, FHT, strongly dominates prior percent cost proxies.

Abstract: We compare liquidity proxies constructed from low-frequency (daily) stock data to liquidity benchmarks computed from high-frequency (intraday) data for 18,472 firms on 43 exchanges around the world from January 1996 to December 2007. We evaluate eight percent-cost proxies (including a new one) relative to four percent-cost benchmarks: percent effective spread, percent quoted spread, percent realized spread, and percent price impact. We examine eleven cost-per-volume proxies (including a new one) relative to a costper-volume benchmark: the slope of the price function “lambda.” We test these proxies on three performance dimensions: average cross-sectional correlation with the benchmarks, portfolio correlations with the benchmarks, and prediction accuracy. We find that a new proxy, FHT, strongly dominates prior percent cost proxies. It is highly correlated with percent effective spread, percent quoted spread, percent realized spread, and percent price impact. It captures the level of percent effective spread and percent quoted spread, but does not capture the level of percent realized spread or percent price impact. We find that the best cost-per-volume proxies are FHT Impact, Zeros Impact, and Amihud. All three are highly correlated with lambda, but do not capture the level of lambda. Finally, we find that lower synchronicity, higher disclosure, lower turnover, and greater likelihood of prosecuting insider trading lead to higher performance of the best liquidity proxies.