A Positive Analysis on Stock Profit and Volatility in Shanghai Stock Market at Different Stages

Abstract

Abstract: Based on Generalized Error Distribution,this paper analyses the stock profit and volatility in Shanghai stock market at different stages,using the family of GARCH models.GARCH and GARCH-M models imply that the volatility is weakening,and investors who used to be risk preference have become risk aversion.The study of asymmetry using GJR-GARCH and EGARCH models shows that there is an asymmetric effect in stock market and the leverage effect is distinct gradually.The empirical results indicate that market speculate is reducing and the investors have become rational gradually.

Key words: profit, volatility, different stages, leverage effects, GARCH

CHEN Shou-Dong, MA Hui, CAI Yuan. A Positive Analysis on Stock Profit and Volatility in Shanghai Stock Market at Different Stages[J]. Journal of Jishou University（Social Sciences）, 2006, 27(4): 94-102.

References

[1] Nelson D B.Conditional Heteroskedasticity in Asset Return: A New Approach [J].Econometrica, 1991, (59): 347-370.

[2] Nelson D B., Stationary and Persistence in the GARCH(1,1)model [J].Econometric Theory, (6):318-334.

[3] Engle, R. F., Autoregressive conditional heteroscedasticity with estimate of the variance of United Kingdom inflation [J]. Econometrica, 1982, 50, 987-1008.

[4] Bollerslev T.Generalized autoregressive conditional heteroscedasticity [J]. Journal of Econometrics, 1986, 31:307-327.

[5] Gilbert, C. L., Professor Hendry’s Econometric Methodology [M]. Oxford Bulletin of Economics and Statistics, 1986, 48, 283-307.

[6] Robert F. Engle, David M. Lilien, and Russell P. Robins, Estimating Time Varying Risk Premia in the Term Structure: the ARCH-M model [J]. Econometrica, 1987,(55):391-40.

[7] Zakoian, JM, Threshold Heteroskedasticity Model, manuscipt, CREST, INSEE, 1990, Paris.

[8] Glosten L, Jagannathan R, Runkle D., On the relation between the expected value and the volatility of nominal excess return on stocks [J], Journal of Finance,1992,46:1 779-1 801.

[9] Engle, Robert F. and Victor K., Ng Measuring and Test the impact of News on Volatility [J]. Journal of Finance, 1993,48: 1022-1082.

[10] Fornari, F. and Mele, A., Sign-And Volatility-Switching Arch Models: Theory and Applications To International Stock Markets [J]. Journal of Applied Econometrics, 1997, 12, 49-65.

[11] Kahneman D. and Tversky A., Prospect Theory: An Analysis of Decision Making under Risk [J]. Econometrica, 1979, Vol. 47, No. 2, March: 263-291.

[12] 吴长风. 利用回归GARCH模型对我国沪深股市的分析 [J]. 预测，1999，(4):46-47.

[13] 陈千里，周少甫. 上证指数收益的波动性研究[J]. 数量经济技术经济研究，2002，(6):122-125.

[14] 陈守东，俞世典. 基于GARCH 模型的VaR方法对中国股市的分析 [J]. 吉林大学社会科学学报，2002，(4):11-17.

[15] 陈守东，韩广哲，荆伟. 主要股票市场指数与我国股票市场指数间的协整分析[J]. 数量经济技术经济研究，2003， (5):124-129.

[16] 陈守东，陈雷，刘艳武. 中国沪深股市收益率及波动性相关分析[J]. 金融研究，2003，(7):80-85.

[17] 陈学华，杨辉耀. APARCH 模型在证券投资风险分析中的应用[J]. 运筹与管理，2003，(3):92-97.

[18] 陈工孟，芮萌. 中国股票市场的股票收益与波动关系研究[J]. 系统工程理论与实践，2003，(10):12-21.

[19] 刘金全，崔畅. 中国沪深股市收益率和波动性的实证分析[J]. 经济研究(季刊)，2002，(1):885-898.

[20] 田华，曹家和. 中国股票市场报酬与波动的GARCH-M模型[J]. 系统工程理论与实践，2003，(8):81-86.

[21] 王春峰. 金融市场风险管理[M]. 天津：天津大学出版社，2001:126-148.

[22] 特伦斯·C·米尔斯. 金融时间序列的经济计量学模型[M]. 北京：经济科学出版社，2002:131-182.