Nonlinearities in the CAPM: evidence from developed and emerging markets

Neslihanoglu, S., Sogiakas, V., McColl, J. and Lee, D. (2017) Nonlinearities in the CAPM: evidence from developed and emerging markets. Journal of Forecasting, 36(8), pp. 867-897. (doi: 10.1002/for.2389)

113217.pdf - Accepted Version



This paper examines the forecasting ability of the non-linear 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 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 which involve structural changes and/or market inefficiencies which are common in most of the emerging stock markets.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Neslihanoglu, Mr Serdar and McColl, Professor John and Lee, Professor Duncan and Sogiakas, Dr Vasilios
Authors: Neslihanoglu, S., Sogiakas, V., McColl, J., and Lee, D.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
College of Social Sciences > Adam Smith Business School > Economics
Journal Name:Journal of Forecasting
ISSN (Online):1872-8200
Published Online:25 January 2016
Copyright Holders:Copyright © 2016 John Wiley and Sons, Ltd.
First Published:First published in Journal of Forecasting 36(8):867-897
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher.

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