IDEAS home Printed from https://ideas.repec.org/a/wsi/afexxx/v04y2008i01ns2010495208500048.html
   My bibliography  Save this article

Volatility Dynamics In Foreign Exchange Rates: Further Evidence From The Malaysian Ringgit And Singapore Dollar

Author

Listed:
  • KIN-YIP HO

    (Faculty of Business and Enterprise, Swinburne University of Technology, Australia)

  • ALBERT K TSUI

    (Department of Economics, National University of Singapore, AS2 Level 6, 1 Arts Link, Singapore 117570, Singapore)

Abstract

The evolution of volatility and correlation patterns of the Malaysian ringgit (MYR) and the Singapore dollar (SGD) are analyzed in this paper. Our approach can simultaneously capture the empirical regularities of persistent and asymmetric effects in volatility and time-varying correlations of financial time series. Consistent with the results of (1997), there is only some weak support for asymmetric volatility in the case of the MYR when the two currencies are measured against the US dollar (USD). However, there is strong evidence that depreciation shocks have a greater impact on future volatility levels compared with appreciation shocks of the same magnitude when both currencies measured against the yen. Moreover, evidence of time-varying correlation is highly significant when both currencies are measured against the yen. Regardless of the choice of the numeraire currency and the volatility models, shocks to exchange rate volatility are found to be significantly persistent.

Suggested Citation

  • Kin-Yip Ho & Albert K Tsui, 2008. "Volatility Dynamics In Foreign Exchange Rates: Further Evidence From The Malaysian Ringgit And Singapore Dollar," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-27.
  • Handle: RePEc:wsi:afexxx:v:04:y:2008:i:01:n:s2010495208500048
    DOI: 10.1142/S2010495208500048
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2010495208500048
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S2010495208500048?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. KANTA TANNIYOM & Paponpat Taveeapiradeecharoen & Prapatchon Jariyapan, 2015. "Modeling Dependency and Conditional Volatility between Asian Economic Community (AEC) Country Exchange Rate and Inflation Using the Copula-GARCH Model," Proceedings of International Academic Conferences 2704733, International Institute of Social and Economic Sciences.

    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. Asai Manabu & So Mike K.P., 2015. "Long Memory and Asymmetry for Matrix-Exponential Dynamic Correlation Processes," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 69-94, January.
    2. Cavit Pakel & Neil Shephard & Kevin Sheppard & Robert F. Engle, 2021. "Fitting Vast Dimensional Time-Varying Covariance Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 652-668, July.
    3. Escobari, Diego & Garcia, Sergio & Mellado, Cristhian, 2017. "Identifying bubbles in Latin American equity markets: Phillips-Perron-based tests and linkages," Emerging Markets Review, Elsevier, vol. 33(C), pages 90-101.
    4. Papaioannou, Elias & Portes, Richard & Siourounis, Gregorios, 2006. "Optimal currency shares in international reserves: The impact of the euro and the prospects for the dollar," Journal of the Japanese and International Economies, Elsevier, vol. 20(4), pages 508-547, December.
    5. Cavit Pakel & Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," OFRC Working Papers Series 2009fe03, Oxford Financial Research Centre.
    6. Lukmanova, Elizaveta & Tondl, Gabriele, 2017. "Macroeconomic imbalances and business cycle synchronization. Why common economic governance is imperative for the Eurozone," Economic Modelling, Elsevier, vol. 62(C), pages 130-144.
    7. Diamandis, Panayiotis F., 2008. "Financial liberalization and changes in the dynamic behaviour of emerging market volatility: Evidence from four Latin American equity markets," Research in International Business and Finance, Elsevier, vol. 22(3), pages 362-377, September.
    8. Charlot, Philippe & Darné, Olivier & Moussa, Zakaria, 2016. "Commodity returns co-movements: Fundamentals or “style” effect?," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 130-160.
    9. Bouri, Elie & Gabauer, David & Gupta, Rangan & Tiwari, Aviral Kumar, 2021. "Volatility connectedness of major cryptocurrencies: The role of investor happiness," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    10. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    11. Małgorzata Doman, 2005. "The Co-movement Between Returns of Foreign Exchange Rates in the Central European Countries," FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making, in: Władysław Milo & Piotr Wdowiński (ed.), Acta Universitatis Lodziensis. Folia Oeconomica nr 192/2005 - Issues in Modeling, Forecasting and Decision-Making in Financial Markets, edition 1, volume 127, chapter 10, pages 157-175, University of Lodz.
    12. Sheng‐Tun Li & Kuei‐Chen Chiu & Chien‐Chang Wu, 2023. "Apply big data analytics for forecasting the prices of precious metals futures to construct a hedging strategy for industrial material procurement," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 942-959, March.
    13. Ralf Becker & Adam Clements & Robert O'Neill, 2018. "A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns," Econometrics, MDPI, vol. 6(1), pages 1-27, February.
    14. Mahendra Chandra, 2006. "The day-of-the-week effect in conditional correlation," Review of Quantitative Finance and Accounting, Springer, vol. 27(3), pages 297-310, November.
    15. Ülkü, Numan & Weber, Enzo, 2013. "Identifying the interaction between stock market returns and trading flows of investor types: Looking into the day using daily data," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2733-2749.
    16. Bruno P. Arruda & Pedro L. Valls Pereira, 2013. "Analysis of the volatility's dependency structure during the subprime crisis," Applied Economics, Taylor & Francis Journals, vol. 45(36), pages 5031-5045, December.
    17. Nicola, Francesca de & De Pace, Pierangelo & Hernandez, Manuel A., 2016. "Co-movement of major energy, agricultural, and food commodity price returns: A time-series assessment," Energy Economics, Elsevier, vol. 57(C), pages 28-41.
    18. Yilmaz, Tolgahan, 2010. "Improving Portfolio Optimization by DCC And DECO GARCH: Evidence from Istanbul Stock Exchange," MPRA Paper 27314, University Library of Munich, Germany.
    19. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    20. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.

    More about this item

    Keywords

    Constant correlations; exchange rate volatility; fractional integration; long memory; bivariate asymmetric GARCH; varying correlations; C12; G15;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    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:wsi:afexxx:v:04:y:2008:i:01:n:s2010495208500048. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/afe/afe.shtml .

    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.