Journal article · 2021

Information content of liquidity and volatility measures

Będowska-Sójka, B., Kliber, A.

Physica A: Statistical Mechanics and its Applications, 563, 125436

DOI: 10.1016/j.physa.2020.125436

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

Research topics: Market liquidity and its measurement

Cite

@article{physa2021_information,
  title = {Information content of liquidity and volatility measures},
  author = {Będowska-Sójka, B. and Kliber, A.},
  year = {2021},
  journal = {Physica A: Statistical Mechanics and its Applications},
  note = {563, 125436},
  doi = {10.1016/j.physa.2020.125436}
}