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Dependence modelling of Malaysian Ringgit (MYR) and Thai Baht (THB): the Markov switching model with dynamic copula approach (DCA) and bivariate extreme value approach

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  • Prasert Chaitip
  • Chukiat Chaiboonsri

Abstract

This research was conducted to identify foreign currencies traded against the US dollar. A research question is how foreign currencies are traded in the case of bivariate extreme values that can bring perfect balance phenomenon and harmony in which the currency is recognised as currency appreciation or depreciation in value. Dependent structure and co-movement between daily data of Malaysian Ringgit (MYR) and Thai Baht (THB) during the period 2006-2013 were investigated. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) straightforward model selection confirmed that the elliptical copula fit for both currencies recognised currency appreciation or depreciation in value. The calculations based on the BEVA demonstrate there is harmonious dependence and balance phenomenon between MYR and THB against the US dollar. Finally, a developed multi-model approach to dependence modelling for variations in the price of a currency known as currency appreciation or depreciation meets the predictable needs of new financial opportunities and policy challenges.

Suggested Citation

  • Prasert Chaitip & Chukiat Chaiboonsri, 2016. "Dependence modelling of Malaysian Ringgit (MYR) and Thai Baht (THB): the Markov switching model with dynamic copula approach (DCA) and bivariate extreme value approach," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 6(2), pages 138-155.
    • Handle: RePEc:ids:ijcome:v:6:y:2016:i:2:p:138-155
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    References listed on IDEAS

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    1. Stuart G. Coles & Jonathan A. Tawn, 1994. "Statistical Methods for Multivariate Extremes: An Application to Structural Design," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(1), pages 1-31, March.
    2. Joe, Harry, 1990. "Families of min-stable multivariate exponential and multivariate extreme value distributions," Statistics & Probability Letters, Elsevier, vol. 9(1), pages 75-81, January.
    3. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    4. Hüsler, Jürg & Reiss, Rolf-Dieter, 1989. "Maxima of normal random vectors: Between independence and complete dependence," Statistics & Probability Letters, Elsevier, vol. 7(4), pages 283-286, February.
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