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Short-Term Dependencies between the Volatility of Currency, Money and Capital Markets: The Case of Poland

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  • Janusz Brzeszczynski
  • Robert Kelm

Abstract

The paper presents GARCH models for the Euro-Polish zloty and US dollar-Polish zloty currency rates. It applies the approach within which both the conditional variance function and the mean equation of the ARCH class model are expanded simultaneously. The basic regression equation incorporates causal dependencies between currency prices and the main characteristics of domestic and international currency, money and capital markets. The paper provides an insight into the currency market microstructure as the presented investigation takes into account the intradaily features of the market. Model selection and performance has been evaluated by the use of direction quality measures.

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File URL: http://www.sml.hw.ac.uk/downloads/cert/wpa/2004/dp0409.pdf
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Bibliographic Info

Paper provided by Centre for Economic Reform and Transformation, Heriot Watt University in its series CERT Discussion Papers with number 0409.

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Date of creation: 2004
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Handle: RePEc:hwe:certdp:0409

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Keywords: currency market; GARCH models; direction quality measures; emerging markets;

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  1. Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038 Elsevier.
  2. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  3. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  4. Richard K. Lyons., 1995. "Foreign Exchange Volume: Sound and Fury Signifying Nothing?," Research Program in Finance Working Papers RPF-243, University of California at Berkeley.
  5. Campbell, John Y & Grossman, Sanford J & Wang, Jiang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, MIT Press, vol. 108(4), pages 905-39, November.
  6. Pesaran, M.H. & Timmermann, A., 1990. "A Simple Non-Parametric Test Of Predictive Performance," Papers 29, California Los Angeles - Applied Econometrics.
  7. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-29, March.
  8. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  9. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
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