我国证券投资基金重仓持股变动对股票价格波动性影响的实证研究

文章采用了2006年第一季度到2008年第四季度国内证券投资基金公布的季度数据,运用动态面板数据模型对我国证券投资基金重仓持股变动与股票价格波动性之间的关系进行了实证研究。结果表明,在牛市中证券投资基金重仓持股比例的变化与股价波动性成正向关系,加剧了股价的波动;在熊市中证券投资基金持股比例变化与股票价格波动性成反向关系,起到了稳定证券市场的作用。     

证券投资基金持股与管理者过度投资行为的相关性研究

基于沪深A股上市公司2008年-2010年的研究数据,分析了证券投资基金持股对企业过度投资的影响。研究发现,证券投资基金持股比例与管理者过度投资显著负相关,证券投资基金能有效抑制管理者的过度投资行为;进一步研究发现,证券投资基金持股比例越高,上市公司派发现金股利水平越高,并且证券投资基金持股在一定程度上能够抑制上市公司恶意派现的现象。     

机构投资者行为对股票价格波动性的影响 ——基于大盘股和小盘股的实证研究

机构投资者对股票价格的波动率是起着促进作用还是抑制作用,学术界一直存在着不同的观点。文章分析了机构投资者在大盘股和中小盘股中持股比例和交易强度对股票价格的波动率的影响。研究发现,在大盘股中机构投资者的交易强度与股价波动呈负相关关系,起到稳定股价的作用;在中小盘股中交易强度和股价波动呈正相关关系,短期内投机动机比较强。而大小盘股中机构投资者的持股比例均与股价波动均呈负相关关系,起到稳定股价的作用。     

证券投资基金持股比例与上市公司绩效关系的实证研究

本文对证券投资基金持股比例与上市公司绩效之间的关系进行了实证研究,指出我国证券投资基金持股比例与上市公司绩效呈现出一定的正相关性,并且随着公司股权的分散,基金对公司绩效的影响越来越显著。     

我国基金持股比例变动对股价波动影响研究

在上证180指数包含的180支样本股中选取2009年2季度至2014年2季度连续五年被基金重仓持有的112支股票作为研究样本,将一个季度作为研究期间,以股价季度波动率作为被解释变量,基金季度持股比例的变动率作为解释变量进行线性回归分析。结果表明:在研究期间内基金持股比例变动率与股价波动率呈显著的负相关关系。     

证券投资基金持股比例与上市公司绩效关系的实证研究

本文对证券投资基金持股比例与上市公司绩效之间的关系进行了实证研究,指出我国证券投资基金持股比例与上市公司绩效呈现出一定的正相关性,并且随着公司股权的分散,基金时公司绩效的影响越来越显著.     

证券投资基金持股比例与上市公司绩效的实证研究

本文对证券投资基金持股比例与上市公司绩效之间的关系进行了实证研究，指出我国证券投资基金持股比例与上市公司绩效呈现出一定的正相关性，并且随着公司股权的分散，基金对公司绩效的影响越来越显著。     

我国机构投资者参与公司治理实证分析

文章从我国机构投资者的角度出发,研究其参与上市公司治理的情况。机构投资者选择证券投资基金作为研究对象,公司治理效果选择公司业绩和上市公司董事治理排名来体现,对证券投资基金持有上市公司股票的比例与公司治理之间的关系进行分析。研究发现基金持股比例与公司业绩之间具有统计上的正相关关系、与董事会治理排名具有统计上的负相关关系。     

机构投资者持股与公司股权融资成本的实证研究

本文从机构投资者持股对股权融资成本影响的角度来研究机构投资者对公司治理的影响.实证结果表明,由于证券投资基金是独立的机构投资者并在我国机构投资者中占主导地位,机构投资者能够有效监督公司管理层,降低公司代理成本,两者持股比例与公司股权融资成本和BETA高度显著负相关.而社保基金和保险基金由于不是独立的机构投资者,无法发挥改善公司治理的作用,两者持股比例与股权融资成本和BETA系数关系不显著.     

基金持股对信息披露质量的改善作用研究——来自深圳证券交易所2004—2010年上市公司的经验证据

证券投资基金能否发挥监督优势、参与所持股公司的外部治理,一直是学术界关注的热点。因此,利用深圳证券交易所2004-2010年之间所公布的信息作为研究材料实证检验基金持股对信息披露质量的改善作用。研究结果表明,基金持股改善了所持股公司的信息披露质量,且随着基金持股比例的增加,所持股公司的信息披露质量随之提升。     

Information transmission between large shareholders and stock volatility

Does information transmission between large shareholders exacerbate stock volatility or reduce stock volatility? In this study, based on the common shareholding data in the Chinese stock market from 2007 to 2017, we establish the shareholder’s coshareholding network, and use the weighted network clustering coefficient to measure the information transmission speed. Moreover, we investigate the impact of information transmission speed on stock volatility. The empirical results show that a nonlinear U-shaped relationship exists between information transmission speed and stock volatility. The findings are robust to the inclusion of other determinants of stock volatility identified in the literature. Finally, we verify the existence of private information interaction in the coshareholding network.     

金融危机时期公允价值计量对股票收益率和市场波动性的相关性研究

文章研究我国A股非金融类上市公司在金融危机时期,公允价值计量的资产和损益对股票收益率和市场波动性的影响。文章选取2007年第4季度-2009年第2季度7个季度的面板数据,运用固定效应模型进行回归分析,结果表明:公允价值计量的资产对股票收益率有显著影响,公允价值计量的损益的会计信息没有反映在股价上,对股票收益率无显著影响;公允价值计量的资产和损益都没有加剧市场波动,反而降低了市场波动,即公允价值在我国没有起到金融危机助推器的作用。     

Sudden equity price declines and the flight-to-safety phenomenon: additional evidence using daily data

Using daily data we show sudden, extreme declines in the U.S. stock market for crash dates to lead to a capital preserving (as opposed to strategic or tactical) reallocation to government debt securities. In most cases we find flight-induced reallocation reverses direction within one day of a crash. However, for the 1987 world crash we find increased and persistent return volatility in both equity and bond returns lasting up to five days following this dramatic decline in world equity prices. Like previous research in this area, we find equity crashes alter long-run stock/bond return correlations and lead to increased stock and bond return volatility. Finally, we describe the somewhat unique stock and bond correlation adjustments triggered by the 9/11 attack and the impact this event had on the behavior of U.S. equity investors?? flight-to-safety reaction.     

互联网基金对股票市场的影响——基于大数据情绪指数的实证研究

投资者在进行投资决策时易受到自身情绪的影响，并且投资者行为是影响金融市场间波动溢出的直接原因。运用文本挖掘技术对新浪微博2014年4月至2016年7月的博文进行文本分析和随机森林主成分分析并构建微博大数据投资者情绪指数，根据投资者情绪指数研究互联网基金市场对股票市场的影响，结果表明互联网基金市场对股票市场具有波动溢出效应。     

Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model

This study employs a new GARCH copula quantile regression model to estimate the conditional value at risk for systemic risk spillover analysis. To be specific, thirteen copula quantile regression models are derived to capture the asymmetry and nonlinearity of the tail dependence between financial returns. Using Chinese stock market data over the period from January 2007 to October 2020, this paper investigates the risk spillovers from the banking, securities, and insurance sectors to the entire financial system. The empirical results indicate that (i) three financial sectors contribute significantly to the financial system, and the insurance sector displays the largest risk spillover effects on the financial system, followed by the banking sector and subsequently the securities sector; (ii) the time-varying risk spillovers are much larger during the global financial crisis than during the periods of the banking liquidity crisis, the stock market crash and the COVID-19 pandemic. Our results provide important implications for supervisory authorities and portfolio managers who want to maintain the stability of China’s financial system and optimize investment portfolios.     

机构投资者羊群行为动因分析——2009年数据实证

羊群行为作为机构投资者的一种普遍非理性行为,对我国的股票市场产生重大影响。羊群行为对短期股价波动会产生较大的影响,同时在一定程度上破坏股价的长期稳定。本文首先对羊群行为进行界定,然后旨在通过数据对证券投资基金的羊群行为进行实证,并分析其主要动因,最后针对其成因提出弱化机构投资者羊群行为的措施。     

Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach

In this study, we investigate the dependence structures between six Chinese stock markets and the international financial market including possible safe haven assets and global economic factors under different market conditions and investment horizons. The research is conducted by combining a quantile regression approach with a wavelet decomposition analysis. Although we find little or insignificant dependence under short investment horizons, we detect the strong asymmetric dependence of oil prices and the US dollar index on the six Chinese stock markets in the medium and long terms. Moreover, not only is crude oil not a safe haven, it may damage Chinese stock markets as it increases over the long term, even in bull markets. Meanwhile, appreciation of the US dollar (depreciation of RMB) damages (boosts) Chinese stock markets during bull (bear) market conditions under long investment horizons. Moreover, we find that VIX (volatility index)-related derivatives may serve as good risk management tools under any market condition, while gold is a safe haven asset only during crisis periods.     

Efficient predictability of stock return volatility: The role of stock market implied volatility

This study examines the predictability of stock market implied volatility on stock volatility in five developed economies (the US, Japan, Germany, France, and the UK) using monthly volatility data for the period 2000 to 2017. We utilize a simple linear autoregressive model to capture predictive relationships between stock market implied volatility and stock volatility. Our in-sample results show there exists very significant Granger causality from stock market implied volatility to stock volatility. The out-of-sample results also indicate that stock market implied volatility is significantly more powerful for stock volatility than the oil price volatility in five developed economies.     

Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach

In this study, we examine the connection between geopolitical risk (GPR) and stock market volatility in emerging economies. Our motivation for this study is premised on the need to assess both the predictability and the associated economic gains in relation to the subject in order to offer more useful insights to investors and practitioners. To the best of our knowledge, this is the first study that jointly considers these objectives. Consequently, we employ the GARCH-MIDAS framework which accommodates mixed data frequencies thereby circumventing information loss or any associated bias. We find that emerging stock market volatility responds more positively to geopolitical risks although the act-related GPR index offers better out-of-sample forecasts than the threat-related GPR. We also find that accounting for global economic factors in the predictability analysis is crucial for robust outcomes. Finally, we provide some utility gains of including GPR in the predictive model of stock market volatility while also highlighting some useful implications of our findings for investment and policy decisions.