A comparison of GARCH –Jump Models with Skewed Generalized Error Distribution for Asset Returns

• Main Authors: Chun-Chi Chen, 陳俊吉
• Other Authors: Ming-Chih Lee
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/85563055978979441558

碩士 === 淡江大學 === 財務金融學系碩士在職專班 === 96 === This paper adopts the GARCH jump model and ARJI model of Chan and Maheu(2002) that combine the skewed generalized error distribution of asset returns, in order to examine the jump, leptokurtosis and volatility clustering for the rates of returns of America and BRICs. We also employ likelihood ratio test for testing goodness of different models. In conclusion, we analyze different models’ capture ability for statistic features of mature market and emerging markets. The empirical results indicated that the five countries exist heavy tail and volatility clustering, but GARCH-JD and ARJI model with Russia and GARCH-JD with China can’t capture skewness. We also find these countries’ stock returns except Brazil with the two models have significant characteristic of jumping and jump process is provided with time varying. It’s better efficient when we assume that asset returns obey SGED. The ARJI model with SGED of asset returns develop that the diminishing efficiency for mature markets is faster then emerging markets while the earlier stage’s returns affect it at present. But mature markets’ nonpredictive volatility in early days for effecting upon at once is stronger then emerging markets. In the end, the likelihood ratio test demonstrate that these countries using SGED have more significant goodness of fit then using normal distribution. Totally, the ARJI model captures statistical property’s ability surpasses the GARCH-JD model and the ARJI model utilizes to the emerging markets compared with utilizes has the better explanation ability to the mature market.