全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

MDH理论与日历效应下的中国股市量价关系

DOI: 10.3969/j.issn.1000-5013.2007.04.029

Keywords: 分布混合假说理论, 日历效应, 广义自回归条件异方差模型, 股价波动性, 交易量, 中国股市

Full-Text   Cite this paper   Add to My Lib

Abstract:

基于分布混合假说(MDH)理论的数学推导,以我国深沪股市的大盘指数为研究对象,检验原始交易量、包含自相关性的交易量对广义自回归条件异方差模型(GARCH)效应的解释效果,并分析日历效应对交易量与股价波动性关系的特殊影响.结果表明,GARCH模型可以很好地拟合中国股市的股价波动持续性问题; 当引入原始交易量以后,股价波动性在一定程度上可以为原始交易量所解释,而包含自相关性的交易量对股市GARCH效应并无很好的解释力.经实证分析证实,股价的日历效应对于上海市场中交易量对股价波动性的解释有着推波助澜的作用.

References

[1]  ENGLE R. Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation [J]. Econometrica, 1982.987-1008.
[2]  CLARK P K. A subordinated stochastic process model with finite variance for speculative price [J]. Econometrica, 1973.135-156.doi:10.2307/1913889.
[3]  TAUCHEN G, PITTS M. The price variability-volume relationship on speculative markets [J]. Econometrica, 1983.485-505.
[4]  LAMOUREUX C, LASTRAPES W D. Heteroskedasticity in stock return data:Volume versus GARCH effects [J]. Journal of Finance, 1990.221-229.
[5]  RAJEN M, 俞乔. An empirical analysis of the equity markets in China [J]. Review of Financial Economics, 1999(1):41-60.
[6]  BOLLERSLEV T A. Generalized autoregressive conditional heteroskedasticity [J]. Journal of Econometrics, 1986.307-327.
[7]  HE H, WANG J. Differential information and dynamics behavior of stock trading volume and price volatility [J]. Review of Financial Studies, 1995.919-972.
[8]  HARRIS L. Cross-security tests of the mixture of distribution hypothesis [J]. Journal of Financial and Quantitative Analysis, 1986(1):109-126.
[9]  AADERSON T G. Return volatility and trading volume:An information flow interpretation of stochastic volatility [J]. Journal of Finance, 1996.169-204.
[10]  LEE C F, CHEN G M, RUI O. Stock returns and volatility on China’s stock markets [J]. Journal of Financial Research, 2001.523-534.
[11]  张宗新. 金融资产价格波动与风险控制 [M]. 上海:复旦大学出版社, 2005.55-58.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133