Nonlinearities in the CAPM: Evidence from Developed and Emerging Markets |
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| Authors: | Serdar Neslihanoglu Vasilios Sogiakas John H. McColl Duncan Lee |
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| Affiliation: | 1. Department of Statistics, Faculty of Science and Letters, Eskisehir Osmangazi University, Eskisehir, Turkey;2. Adam Smith Business School (Economics), University of Glasgow, Glasgow, UK;3. School of Mathematics and Statistics, University of Glasgow, Glasgow, UK |
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| Abstract: | This paper examines the forecasting ability of the nonlinear specifications of the market model. We propose a conditional two‐moment market model with a time‐varying systematic covariance (beta) risk in the form of a mean reverting process of the state‐space model via the Kalman filter algorithm. In addition, we account for the systematic component of co‐skewness and co‐kurtosis by considering higher moments. The analysis is implemented using data from the stock indices of several developed and emerging stock markets. The empirical findings favour the time‐varying market model approaches, which outperform linear model specifications both in terms of model fit and predictability. Precisely, higher moments are necessary for datasets that involve structural changes and/or market inefficiencies which are common in most of the emerging stock markets. Copyright © 2016 John Wiley & Sons, Ltd. |
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| Keywords: | CAPM time‐varying market model co‐skewness and co‐kurtosis quadratic and cubic market model |
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