基于EGRACH模型的股指期货对股市非对称性波动影响的实证研究

本文基于EGRACH模型,利用高频数据,实证检验了沪深300股指期货对我国股市非对称波动的影响。实证研究表明,沪深300股指期货与现货市场之间存在互为格兰杰因果关系,在股指期货初期股指期货对股市的波动有放大作用,在远期降低了非对称性波动,具有稳定股市的功效。     

There's more to volatility than volume

It is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of transactions is held constant. In addition the distribution of price returns conditioned on volume or transaction frequency being held constant is similar to that in real time, making it clear that neither of these are the principal cause of heavy tails in price returns. We analyse recent results of Ane and Geman (2000 Ane, T and Geman, H. 2000. Order flow, transaction clock, and normality of asset returns. J. Finance, 55(5): 2259–2284. [Crossref], [Web of Science ®] , [Google Scholar]: J. Finance, 55, 2259–2284) and Gabaix et al. (2003 Gabaix, X, Gopikrishnan, P, Plerou, V and Stanley, H.E. 2003. A theory of power-law distributions in financial market fluctuations. Nature, 423: 267–270. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]: Nature, 423, 267–270), and discuss the reasons why their conclusions differ from ours. Based on a cross-sectional analysis we show that the long-memory of volatility is dominated by factors other than transaction frequency or total trading volume.     

Ordering univariate distributions by entropy and variance

This paper examines the role of variance and entropy in ordering distributions and random prospects. There is no universal relation between entropy and variance orderings of distributions. But we place their relationship in the context of a stronger ordering relation known as dispersion ordering. Further, some conditions are identified under which variance and entropy order similarly when continuous variables are transformed. We also analyze parametric changes which do not disturb the agreement between these rankings. The results are conveniently tabulated in terms of distribution parameters.     

GARCH族模型的预测能力比较:一种半参数方法

半参数GARCH模型无须设定条件分布的具体形式。本文首先将一种效率较高、易于实施的半参数方法——估计函数方法应用于10类常见的GARCH结构,并给出证据,显示该方法能显著提高GARCH族模型的波动率预测绩效。然后,应用估计函数方法,较为全面地比较各类GARCH结构的预测能力。为给出统计意义下的结果,并减少数据窥察问题,研究中分别使用OLS和SPA检验法进行绩效评价。结果发现,与其他GARCH类结构相比,EGARCH和APARCH模型能够较好地描述股市收益率的波动过程。     

机构投资者持股与股票收益波动性——基于机构重仓股的分阶段实证研究

以2003年第4季度至2011年第2季度机构投资者持股比例超过5％的上市公司为样本,根据证券投资基金总资产净值变动的状况把机构投资者发展历程分为平缓发展期、高速发展期和调整发展期,运用面板数据模型研究机构投资者持股对上市公司股票收益波动性的影响.研究发现,在平缓发展期,机构投资者持股比例与股票收益波动性无关,持股比例变动降低了股票收益波动性;在高速发展期和调整发展期,不管是机构投资者持股比例还是持股比例变动,均与上市公司股票收益波动性正相关.     

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