A Robust Hybrid DHMM-MLP Modelling of Financial Crises measured by the WhIMS

Abstract. This paper develops a hybrid model combining a Hidden Markov Chain (HMC) and Multilayer Perceptrons (MLP) on the Waveletheterogeneous Index of Market Shocks (WhIMS) to identify dynamically regimes in financial turbulences. The WhIMS is an aggregate measure of volatility computed at different frequencies. We estimate the model based on a French market stock index (CAC40 Index) and compare the prediction performance of the HMC-MLP model to classical linear and non-linear models. A state separation of financial disturbances based on the WhIMS and conditional probabilities of the HMC-MLP model is then performed using a Robust SOM.