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Moments of the ARMA--EGARCH model

  • M. Karanasos
  • J. Kim

This paper considers the moment structure of the general ARMA--EGARCH model. In particular, we derive the autocorrelation function of any positive integer power of the squared errors. In addition, we obtain the autocorrelations of the squares of the observed process and cross correlations between the levels and the squares of the observed process. Finally, the practical implications of the results are illustrated empirically using daily data on four East Asia Stock Indices. Copyright Royal Economic Society, 2003

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Article provided by Royal Economic Society in its journal The Econometrics Journal.

Volume (Year): 6 (2003)
Issue (Month): 1 (06)
Pages: 146-166

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Handle: RePEc:ect:emjrnl:v:6:y:2003:i:1:p:146-166
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  1. Jung-Hee Lee & B. Wade Brorsen, 1997. "A non-nested test of GARCH vs. EGARCH models," Applied Economics Letters, Taylor & Francis Journals, vol. 4(12), pages 765-768.
  2. Joe Appiah-Kusi & Gioia M Pescetto, 1998. "Volatility and Volatility Spill-overs in Emerging Markets: The case of the African Stock Markets," Ekonomia, Cyprus Economic Society and University of Cyprus, vol. 2(2), pages 171-185, Winter.
  3. Andrew W. Lo & A. Craig MacKinlay, 1987. "Stock Market Prices Do Not Follow Random Walks: Evidence From a Simple Specification Test," NBER Working Papers 2168, National Bureau of Economic Research, Inc.
  4. Tse, Yiuman, 1998. "International transmission of information: evidence from the Euroyen and Eurodollar futures markets," Journal of International Money and Finance, Elsevier, vol. 17(6), pages 909-929, December.
  5. Andersen, Torben G. & Chung, Hyung-Jin & Sorensen, Bent E., 1999. "Efficient method of moments estimation of a stochastic volatility model: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 91(1), pages 61-87, July.
  6. Donaldson, R. Glen & Kamstra, Mark, 1997. "An artificial neural network-GARCH model for international stock return volatility," Journal of Empirical Finance, Elsevier, vol. 4(1), pages 17-46, January.
  7. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
  8. Kim, Suk-Joong & Sheen, Jeffrey, 2000. "International linkages and macroeconomic news effects on interest rate volatility -- Australia and the US," Pacific-Basin Finance Journal, Elsevier, vol. 8(1), pages 85-113, March.
  9. Andersen, Torben G. & Lund, Jesper, 1997. "Estimating continuous-time stochastic volatility models of the short-term interest rate," Journal of Econometrics, Elsevier, vol. 77(2), pages 343-377, April.
  10. 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.
  11. Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
  12. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
  13. C. Hafner, 1997. "Estimating High Frequency Foreign Exchange Rate Volatility with Nonparametric ARCH Models," SFB 373 Discussion Papers 1997,18, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  14. Kim, Dongcheol & Kon, Stanley J, 1994. "Alternative Models for the Conditional Heteroscedasticity of Stock Returns," The Journal of Business, University of Chicago Press, vol. 67(4), pages 563-98, October.
  15. Abadir, Karim, 1995. "An Introduction to Hypergeometric Functions for Economists," Discussion Papers 9510, Exeter University, Department of Economics.
  16. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
  17. Stilianos Fountas & Menelaos Karanasos & Marika Karanassou, 2000. "A GARCH Model of Inflation and Inflation Uncertainty with Simultaneous Feedback," Working Papers 0047, National University of Ireland Galway, Department of Economics, revised 2000.
  18. St. Pierre, Eileen F., 1998. "Estimating EGARCH-M models: Science or art?," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(2), pages 167-180.
  19. Lobo, Bento J. & Tufte, David, 1998. "Exchange Rate Volatility: Does Politics Matter?," Journal of Macroeconomics, Elsevier, vol. 20(2), pages 351-365, April.
  20. Koutmos, Gregory & Booth, G Geoffrey, 1995. "Asymmetric volatility transmission in international stock markets," Journal of International Money and Finance, Elsevier, vol. 14(6), pages 747-762, December.
  21. Menelaos Karanasos & J. Kim, . "Alternative GARCH in Mean Models: An Application to the Korean Stock Market," Discussion Papers 00/25, Department of Economics, University of York.
  22. Tse, Yiuman & Booth, G. Geoffrey, 1996. "Common volatility and volatility spillovers between U.S. and Eurodollar interest rates: Evidence from the futures market," Journal of Economics and Business, Elsevier, vol. 48(3), pages 299-312, August.
  23. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
  24. Hu, Michael Y. & Jiang, Christine X. & Tsoukalas, Christos, 1997. "The European exchange rates before and after the establishment of the European Monetary System," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 7(3), pages 235-253, October.
  25. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
  26. Allan D. Brunner & David P. Simon, 1995. "Excess returns and risk at the long end of the Treasury market: an EGARCH-M approach," International Finance Discussion Papers 522, Board of Governors of the Federal Reserve System (U.S.).
  27. Manolis G. Kavussanos & Amir H. Alizadeh-M, 2002. "The Expectations Hypothesis of the Term Structure and Risk Premiums in Dry Bulk Shipping Freight Markets," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 36(2), pages 267-304, May.
  28. Booth, G. Geoffrey & Martikainen, Teppo & Tse, Yiuman, 1997. "Price and volatility spillovers in Scandinavian stock markets," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 811-823, June.
  29. Hagerud, Gustaf E., 1997. "Modeling Nordic Stock Returns with Asymmetric GARCH models," SSE/EFI Working Paper Series in Economics and Finance 164, Stockholm School of Economics.
  30. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
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