Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/92706 
Year of Publication: 
2001
Series/Report no.: 
ISER Discussion Paper No. 539
Publisher: 
Osaka University, Institute of Social and Economic Research (ISER), Osaka
Abstract: 
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.
Document Type: 
Working Paper

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