IDEAS home Printed from https://ideas.repec.org/a/ids/ijcome/v6y2016i2p138-155.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=75620
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bücher, Axel & Jäschke, Stefan & Wied, Dominik, 2015. "Nonparametric tests for constant tail dependence with an application to energy and finance," Journal of Econometrics, Elsevier, vol. 187(1), pages 154-168.
    2. Cooley, Daniel & Davis, Richard A. & Naveau, Philippe, 2010. "The pairwise beta distribution: A flexible parametric multivariate model for extremes," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2103-2117, October.
    3. Padoan, Simone A., 2011. "Multivariate extreme models based on underlying skew-t and skew-normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 102(5), pages 977-991, May.
    4. Kiriliouk, Anna & Lee, Jeongjin & Segers, Johan, 2023. "X-Vine Models for Multivariate Extremes," LIDAM Discussion Papers ISBA 2023038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Capéraà, Philippe & Fougères, Anne-Laure & Genest, Christian, 2000. "Bivariate Distributions with Given Extreme Value Attractor," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 30-49, January.
    6. Bücher Axel, 2014. "A note on nonparametric estimation of bivariate tail dependence," Statistics & Risk Modeling, De Gruyter, vol. 31(2), pages 1-12, June.
    7. Mothafer, Ghasak I.M.A. & Yamamoto, Toshiyuki & Shankar, Venkataraman N., 2018. "A multivariate heterogeneous-dispersion count model for asymmetric interdependent freeway crash types," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 84-105.
    8. Arbia, Giuseppe & Lafratta, Giovanni & Simeoni, Carla, 2007. "Spatial sampling plans to monitor the 3-D spatial distribution of extremes in soil pollution surveys," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 4069-4082, May.
    9. Boulin, Alexis & Di Bernardino, Elena & Laloë, Thomas & Toulemonde, Gwladys, 2022. "Non-parametric estimator of a multivariate madogram for missing-data and extreme value framework," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    10. Khreshna Syuhada & Arief Hakim, 2020. "Modeling risk dependence and portfolio VaR forecast through vine copula for cryptocurrencies," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-34, December.
    11. Abduraimova, Kumushoy, 2022. "Contagion and tail risk in complex financial networks," Journal of Banking & Finance, Elsevier, vol. 143(C).
    12. Małgorzata Doman & Ryszard Doman, 2013. "Dynamic linkages between stock markets: the effects of crises and globalization," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 87-112, August.
    13. Morettin Pedro A. & Toloi Clelia M.C. & Chiann Chang & de Miranda José C.S., 2011. "Wavelet Estimation of Copulas for Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-31, October.
    14. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    15. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2022. "Spillovers and diversification benefits between oil futures and ASEAN stock markets," Resources Policy, Elsevier, vol. 79(C).
    16. Tachibana, Minoru, 2022. "Safe haven assets for international stock markets: A regime-switching factor copula approach," Research in International Business and Finance, Elsevier, vol. 60(C).
    17. Luo, Weiwei & Brooks, Robert D. & Silvapulle, Param, 2011. "Effects of the open policy on the dependence between the Chinese 'A' stock market and other equity markets: An industry sector perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 49-74, February.
    18. Jammazi, Rania & Tiwari, Aviral Kr. & Ferrer, Román & Moya, Pablo, 2015. "Time-varying dependence between stock and government bond returns: International evidence with dynamic copulas," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 74-93.
    19. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    20. Oleg Sokolinskiy & Dick van Dijk, 2011. "Forecasting Volatility with Copula-Based Time Series Models," Tinbergen Institute Discussion Papers 11-125/4, Tinbergen Institute.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijcome:v:6:y:2016:i:2:p:138-155. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=311 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.