Violent turbulences are often striking the financial markets and an Index of Market Shocks (IMS) was recently introduced in the attempt of quantifying these turbulences. Regime switching linear models have already been used in modelling the conditional volatility of returns. In this paper we propose a description of the IMS with hybrid models integrating multi-layer perceptrons and hidden Markov chains. After sudying the prediction performance of these models, we focus on the series separation and the index behaviour subject to the hidden states.