The Impact of Regulation Fair Disclosure on Information Asymmetry and Trading: An Intraday Analysis

This study examines the impact of Regulation Fair Disclosure (FD) on liquidity, information asymmetry, and institutional and retail investors trading behavior. Our main findings suggest three conclusions. First, Regulation FD has been effective in improving liquidity and in decreasing the level of information asymmetry. Second, retail trading activity increases dramatically after earnings announcements but there is a significant decline in institutional trading surrounding earnings announcements, particularly in the pre‐announcement period. Last, the decline in information asymmetry around earnings announcements is closely associated with a lower participation rate in the pre‐announcement period and more active trading of retail investors after earnings releases.     

Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

Initial Margin Requirements, Volatility, and the Individual Investor: Insights from Japan

Initial margin requirements represent: (1) a cost impediment to the wealth constrained investor and (2) a potential way of mitigating excessive volatility. However, prior empirical research finds that margins are not an effective tool in reducing volatility. We consider the possibility that margins primarily affect certain stocks and investors. Specifically, we test whether margins affect individuals who, as a group, we believe to be the investors most affected when margin requirements change. Our initial empirical tests, however, do not support this contention.     

Long memory in the volatility of China stock returns

In this paper, we empirically examine the volatility process of China's stock market returns using daily and weekly Shanghai and Shenzhen stock indices during January 1990 to August 2008. To investigate the property of the process, we used the FIGARCH (fractionally integrated GARCH) model including GARCH and IGARCH processes as special cases. Since the FIGARCH model allows fractional integration order, it can detect hyperbolically decaying volatility processes which cannot be explained by previous models with integer integration order. Our results show that the Shanghai and Shenzhen stock indices exhibit long-term dependencies. The long memory properties of the Shanghai and Shenzhen stock markets do not seem to be spuriously induced without exception.     

竞争对手随机进入具有随机寿命创新项目价值评估

在考虑了行业内不完全市场竞争条件下,竞争对手的随机进入及新技术随机出现对项目投资机会的价值影响,假设标的资产服从跳--扩散过程,获得了技术创新成果转化项目的投资机会的价值的模型.研究结果表明,若忽视行业中不完全市场竞争、竞争对手随机进入及新技术随机出现的影响,将会造成投资项目价值的不合理的估计.     

中国股市波动与成交量动态关系研究——基于分位数回归的角度

研究股市波动与成交量之间的动态关系对于了解股市的信息传导机制与微观结构有重要意义.本文基于广义混合分布假说理论,利用分位数回归方法对中国股市上证综指1994年1月至2007年12月的资料进行实证研究,结果发现:中国股市波动具有长期的持续性,负向消息对股市波动的影响大于正向消息;成交量与股市波动之间呈现显著的正向关系,即较大(小)的波动伴随着较大(小)的交易量,且这种关系随着波动增加而逐渐增强,同时具有不对称的特点.相对于传统实证方法,分位数回归对二者的动态关系提供了更完整的描述,能够弥补以往研究的不足.     

技术效率、资本深化与地区差异——基于随机前沿模型的中国地区收敛分析

本文提出了基于随机前沿生产函数的地区增长差异分析框架,将各地区劳均产出差距分解为劳均资本差异、经济规模差异和全要素生产率差异三个部分。利用改革时期的省级数据,本文发现尽管要素投入仍然是中国经济增长的主要源泉,但全要素生产率是造成地区差异的重要原因,在地区劳均产出差异中的贡献份额不断提高,将成为今后中国地区增长差异的主要决定力量。而且,1990年以来中国地区全要素生产率呈现出绝对发散趋势,严重的技术扩散壁垒加剧了体制转轨过程中的“马太效应”,短期内地区差距不会随经济发展而缩小,政府需要通过适当的政策对地区发展进行调节,尤其要促进地区间技术扩散,使各地区更好地分享技术创新和体制创新的成果。