Entropy as a Measure of Risk or a Source of Information to Mitigate Risk: A Comparison Across Various Financial Assets

Abstract

Since the application of entropy in financial economics has been growing extensively as a measure ofvolatility, in portfolio selectionand to detect anomaliesin markets. It’s really complicated to establish that increase in entropy is asource of the usefulinformation for the financial markets that tantamounttomitigaterisk,or it is in fact anindicator of disorder reflecting the growing risk scenario in the financial market. To explore the more effective application of entropy in the field of financial economics, this study evaluates entropy in both contexts, as a source of information to mitigate risk and as an indicator of disorder reflecting volatility. Twelve years daily data of 29 financial assets have been used to measure the intrinsic entropy in addition to other eight volatility estimators and three GARCH models-based volatilities. Various assessment techniques are used to test the role of entropy in both contexts including, Run Test, Mean, Variance and Coefficients of Variation, Mean Squared Errors, Proportional Bias and Efficiency Estimator, in addition tospearman rank-order correlation.Results emphasis that entropy is more suitable as a volatility measure rather a source of information in the financial market.