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Information content of liquidity and volatility measures

Barbara Będowska-Sójka and Agata Kliber ()

Physica A: Statistical Mechanics and its Applications, 2021, vol. 563, issue C

Abstract: This paper aims to compare the mutual information shared by various liquidity and volatility estimators within each group separately. Our sample covers forty one blue-chip companies from the Warsaw Stock Exchange. In terms of their information content, volatility measures are much more coherent, while liquidity ones are more dispersed. The Garman–Klass volatility estimator seems to be the broadest measure of volatility, while Amihud illiquidity and Volatility over volume share the highest amount of mutual information among liquidity proxies. The latter proxy shares approximately the same amount of information with both volatility estimates and liquidity proxies. The possibility to forecast volatility or liquidity, measured by the transfer entropy, with the help of the other volatility or liquidity proxies is limited.

Keywords: Liquidity; Volatility; Causality; Information content; Mutual information; Transfer entropy (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:563:y:2021:i:c:s0378437120307627

DOI: 10.1016/j.physa.2020.125436

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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