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

Janina Engel Markus Wahl Rudi Zagst

*Corresponding author: Rudi Zagst zagst@tum.de


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

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