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ARCH modelling of Australian bilateral exchange rate data

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  • Michael McKenzie

Abstract

A comprehensive examination is undertaken of Australian exchange rate data utilizing the ARCH family of models. Various econometric tests are performed in an attempt to identify the presence of ARCH effects in 21 daily Australian bilateral exchange rate series. Where appropriate, a number of ARCH models have been fitted and the results presented. Several issues are also addressed. The presence of asymmetry in the ARCH effects is tested, although little evidence is found of any such asymmetry, as well as criteria for selecting an optimal ARCH model from among those fitted. The ARCH effects present in less frequently sampled data are thought to diminish and this is tested for using a number of indicators. Finally, the impact is tested of modelling higher-order autocorrelation for the fitted ARCH models.

Suggested Citation

  • Michael McKenzie, 1997. "ARCH modelling of Australian bilateral exchange rate data," Applied Financial Economics, Taylor & Francis Journals, vol. 7(2), pages 147-164.
    • Handle: RePEc:taf:apfiec:v:7:y:1997:i:2:p:147-164
    DOI: 10.1080/096031097333718
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    Cited by:

    1. Michael McKenzie & Heather Mitchell & Robert Brooks & Robert Faff, 2001. "Power ARCH modelling of commodity futures data on the London Metal Exchange," The European Journal of Finance, Taylor & Francis Journals, vol. 7(1), pages 22-38.
    2. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    3. Heidi Aly & Rana Hosni, 2018. "Examining the nexus between exchange rate volatility and export performance: Empirical evidence from the Egyptian experience," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(3), pages 542-560, June.
    4. Stéphane Girard & Gilles Claude Stupfler & Antoine Usseglio-Carleve, 2021. "Extreme Conditional Expectile Estimation in Heavy-Tailed Heteroscedastic Regression Models," Post-Print hal-03306230, HAL.
    5. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    6. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
    7. Liu Zhentao & Kazumi Asako, 2009. "Transfiguration of the foreign exchange market since the Euro introduction," Applied Financial Economics, Taylor & Francis Journals, vol. 19(22), pages 1803-1812.
    8. Gilmore, Claire G., 2001. "An examination of nonlinear dependence in exchange rates, using recent methods from chaos theory," Global Finance Journal, Elsevier, vol. 12(1), pages 139-151.
    9. McKenzie, Michael D., 1999. "Power transformation and forecasting the magnitude of exchange rate changes," International Journal of Forecasting, Elsevier, vol. 15(1), pages 49-55, February.
    10. Ferhan Salman & Aslihan Salih, 1999. "Modeling the Volatility In the Central Bank Reserves In An Emerging Market Setting," Working Papers 9901, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    11. Chee Wooi Hooy & Hui Boon Tan & Annuar Md Nassir, 2004. "Risk Sensitivity of Bank Stocks in Malaysia: Empirical Evidence Across the Asian Financial Crisis," Asian Economic Journal, East Asian Economic Association, vol. 18(3), pages 261-276, September.

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