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Nonlinearities in emerging stock markets: evidence from Europe's two largest emerging markets

Recent developments in time series analysis allow proper modelling of nonlinearities in economic and financial variables. A growing body of research was dedicated to investigation of potential nonlinearities in conditional mean of many economic and financial variables, mainly concentrating in developed economies. However, nonlinearities in financial variables in developing economies have not been fully examined yet. In this article we investigate potential nonlinearity and cyclical behaviour of stock returns in Europe's two largest emerging stock markets, mainly in the Greek and Turkish stock markets. Specifically, we use STAR family models, which allow to model nonlinearities in the conditional mean, for modelling monthly returns on stock exchange indices of the Athens Stock Exchange and Istanbul Stock Exchange. Although we find no nonlinearity in conditional variance, we do find strong evidence in favour of nonlinear adjustment of stock returns. It is found that allowing for nonlinearity in conditional mean results in a superior model and provides good out-of-sample forecasts, which contradicts to efficient market hypothesis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Economics Informa Healthcare

Nonlinearities in emerging stock markets: evidence from Europe's two largest emerging markets

Abstract

Recent developments in time series analysis allow proper modelling of nonlinearities in economic and financial variables. A growing body of research was dedicated to investigation of potential nonlinearities in conditional mean of many economic and financial variables, mainly concentrating in developed economies. However, nonlinearities in financial variables in developing economies have not been fully examined yet. In this article we investigate potential nonlinearity and cyclical behaviour of stock returns in Europe's two largest emerging stock markets, mainly in the Greek and Turkish stock markets. Specifically, we use STAR family models, which allow to model nonlinearities in the conditional mean, for modelling monthly returns on stock exchange indices of the Athens Stock Exchange and Istanbul Stock Exchange. Although we find no nonlinearity in conditional variance, we do find strong evidence in favour of nonlinear adjustment of stock returns. It is found that allowing for nonlinearity in conditional mean results in a superior model and provides good out-of-sample forecasts, which contradicts to efficient market hypothesis.
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