Predicting Systemic Risk with Entropic Indicators

This paper concentrates on quantifying the behavioral aspects of systemic risk by using a novel approach based on entropy. More specifically, we study aggregate market expectations and the predictability of systemic risk before and during the financial crisis in 2008. Two underlying signals for estimating entropic risk measures are considered: (i) skewness premium of deepest out‐of‐the‐money options; and (ii) implied volatility ratio in regard to deepest out‐of‐the‐money options. The findings confirm the predictive and contemporaneous usefulness of our entropy setting in market risk management. The degree of predictability is closely linked to both the type of entropy and the nature of the underlying signal.