Regime shifts in equity risk premium: international evidence

Abstract

Introduction. The academic discussion dedicated to the specific features of financial crises is focused on the analysis of historical volatility patterns. Most researchers point out that strong long-term fluctuations on stock markets are typical for financial crises. Similar reactions to economic crises can be found throughout financial history. Both academic communities and stock markets participants are interested in the search for driving forces that stimulate such kind of behaviour. Purpose. Studying the influence of the scale of national stock markets and various economic crises on the risk level of operations with financial instruments. Methods. Latent modes were identified using Markov switching models. The determination of latent market states was based on the ratio of the components of financial turbulence that characterise the isolated changes in correlated risks and volatility. The influence of the scale of stock markets on the profitability and risk of operations with financial instruments was assessed using the vector autoregression model. Results. The influence of economic crises on the quantitative characters of the excess returns of the world’s largest stock markets was assessed using two-mode Markov switching models and revealed significant differences in the behaviour of stock markets at different time intervals. It was established that the high volatility regime dominates the market during the periods accompanied by economic crises. Through the combination of typical and atypical values of the financial turbulence components we identified four latent market states that provide additional information on the further changes in the current market regimes or lack thereof. Unilateral causal connections are typical for markets with high capitalisation. Markets adapt to the USA market shocks almost twice as slower as compared to the shocks of developing markets. Conclusions. The identified dependences allow increasing the explanatory and prognostic potential of statistical risk analysis in national stock markets.