Forecasting turbulence in the Asian and European stock market using regime-switching models

An early warning system to timely forecast turbulences in the Asian and European stock market is proposed. To ensure comparability, the model is constructed analogously to the early warning system for the US stock market presented by Hauptmann et al. (2014). Based on the time series of discrete monthly returns of the Nikkei 225 and the EuroStoxx 50, filtered probabilities are estimated by two successive Markov-switching models with two regimes each. The market is thus separated in three states: calm, turbulent positive and turbulent negative. Subsequently, a forecasting model using logistic regression and economic input factors is selected. In an empirical asset management case study it is illustrated that the investment performance is improved when considering the signals of the established warning system. Moreover, the US, Asian and European model are compared and interdependencies are highlighted.