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Estimating Smooth Transition Autoregressive Models with GARCH Errors in the Presence of Extreme Observations and Outliers

  • Felix Chan
  • Michael McAleer

This paper investigates several empirical issues regarding quasimaximum likelihood estimation of Smooth Transition Autoregressive (STAR) models with GARCH errors, specifically STAR-GARCH and STAR-STGARCH. Convergence, the choice of different algorithms for maximising the likelihood function, and the sensitivity of the estimates to outliers and extreme observations, are examined using daily data for S&P 500, Heng Seng and Nikkei 225 for the period January 1986 to April 2000.

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File URL: http://www.iser.osaka-u.ac.jp/library/dp/2001/dp0539.pdf
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Paper provided by Institute of Social and Economic Research, Osaka University in its series ISER Discussion Paper with number 0539.

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Date of creation: May 2001
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Handle: RePEc:dpr:wpaper:0539
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  1. Bougerol, Philippe & Picard, Nico, 1992. "Stationarity of Garch processes and of some nonnegative time series," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 115-127.
  2. Francis X. Diebold & James M. Nason, 1989. "Nonparametric exchange rate prediction?," Finance and Economics Discussion Series 81, Board of Governors of the Federal Reserve System (U.S.).
  3. repec:cup:cbooks:9780521634809 is not listed on IDEAS
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