Evaluating volatility dynamics and the forecasting ability of Markov switching models

George S. Parikakis and Anna Merika
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George S. Parikakis: EFG Eurobank Ergasias S.A, Credit Division, Athens, Greece, Postal: EFG Eurobank Ergasias S.A, Credit Division, Athens, Greece

Journal of Forecasting, 2009, vol. 28, issue 8, 736-744

Abstract: This paper uses Markov switching models to capture volatility dynamics in exchange rates and to evaluate their forecasting ability. We identify that increased volatilities in four euro-based exchange rates are due to underlying structural changes. Also, we find that currencies are closely related to each other, especially in high-volatility periods, where cross-correlations increase significantly. Using Markov switching Monte Carlo approach we provide evidence in favour of Markov switching models, rejecting random walk hypothesis. Testing in-sample and out-of-sample Markov trading rules based on Dueker and Neely ( Journal of Banking and Finance , 2007) we find that using econometric methodology is able to forecast accurately exchange rate movements. When applied to the Euro|US dollar and the euro|British pound daily returns data, the model provides exceptional out-of-sample returns. However, when applied to the euro|Brazilian real and the euro|Mexican peso, the model loses power. Higher volatility exercised in the Latin American currencies seems to be a critical factor for this failure. Copyright © 2009 John Wiley & Sons, Ltd.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:28:y:2009:i:8:p:736-744

DOI: 10.1002/for.1135

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