Statistical Inadequacy of GARCH Models for Asian Stock Markets: Evidence and Implications

• Main Authors: Lim, Kian-Ping, Hinich, M.J., Liew, Venus Khim-Sen
• Format: E-Article
• Language: English
• Published: Sage Publications 2005
• Subjects: HB Economic Theory
• Online Access: http://ir.unimas.my/id/eprint/18640/2/Statistical%20Inadequacy%20of%20GARCH%20Models%20%28abstract%29.pdf; http://ir.unimas.my/id/eprint/18640/; http://journals.sagepub.com/doi/abs/10.1177/097265270500400303?journalCode=emfa

This study employs the Hinich portmanteau bicorrelation test (Hinich 1996; Hinich and Patterson 1995) as a diagnostic tool to determine the adequacy of Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models for eight Asian stock markets. The bicorrelation test results demonstrate that this type of model cannot provide an adequate characterisation for the underlying process of all the selected Asian stock markets. Further investigation using the windowed test procedure reveals that the violation of the covariance stationarity assumption as required by the GARCH process is due to the presence of transient epochs of dependencies in the data. The inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolios selection, development of optimal hedging techniques and risk management. JEL Classification: G120, C520 Keywords: GARCH, non-stationarity, data generating process, bicorrelation, Asian stock markets