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A0288
Title: An entropy-based early warning indicator for systemic risk Authors:  Michele Costola - Ca' Foscari University of Venice (Italy)
Monica Billio - University of Venice (Italy) [presenting]
Roberto Casarin - University Ca' Foscari of Venice (Italy)
Andrea Pasqualini - Ca Foscari University of Venice (Italy)
Abstract: The purpose is the construction of an early warning indicator for systemic risk using entropy measures. The analysis is based on the cross-sectional distribution of marginal systemic risk measures such as Marginal Expected Shortfall, Delta CoVaR and network connectedness. These measures are conceived at a single institution for the financial industry in the Euro area. We estimate entropy on these measures and test if they show forecasting abilities in predicting banking crises. In this regard, we use a previously presented variable from European Central Bank. Entropy indicators show promising forecast abilities to predict financial and banking crisis. The proposed early warning signals reveal to be effective in forecasting financial distress conditions. In the analysis we consider Shannon, Tsallis and Renyi entropy measures and find that the values of the extensive index greater than one allow us to achieve better model fitting. This implies that entropy changes do to changes in the tail probability of the loss distribution are more important than changes in the common event probabilities in order to detect periods of high systemic risk level.