Abstract

We examine a general class of volatility over volume liquidity proxies as computed from low frequency (daily) data. We start from the Kyle and Obizhaeva (2016) hypothesis of transaction cost invariance to identify a new volatility over volume liquidity proxy “VoV(%Spread)” for percent spread cost and a new volatility over volume liquidity proxy “VoV(λ)” for the slope of the transaction cost function “λ”. We test the monthly and daily versions of these new and existing liquidity proxies against liquidity benchmarks as estimated from high frequency (intraday) data on both a global and US basis. We find that both the monthly and daily versions of VoV(λ) dominate the equivalent versions of Amihud and other cost-per-dollar-volume proxies on both a global and US basis. We also find that both the monthly and daily versions of VoV(%Spread) dominate the equivalent versions of other percent-cost proxies for US studies that cover pre-1993 years. In a case study, we find that our new VoV liquidity proxies yield different research inferences than the best previous liquidity proxies from the prior literature. The success of our invariance-based liquidity proxies across exchanges and over time supports the prediction of Kyle and Obizhaeva of a specific functional form for transaction costs across exchanges and over time.

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