并购商誉、商誉减值与股票错误定价

以近年来上市公司频发的并购重组为背景,选取2007—2019年我国沪深A股上市公司为研究样本,实证检验了并购商誉对股票错误定价的影响。研究发现,商誉加剧了并购方的股票错误定价,高商誉的公司股价被严重高估,计提商誉减值能够向投资者传递增量信息,缓解商誉导致的股票错误定价。进一步研究发现,会计稳健性和投资者情绪在并购商誉对股票错误定价的影响中发挥了部分中介作用。商誉对股票错误定价的影响在管理层持股高、分析师跟踪人数多的情况下更为显著,上市公司大股东及管理层存在利用并购商誉导致的股价高估实现高位减持的行为。研究结论有助于投资者对并购商誉正确定价,提高资本市场定价效率。     

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。     

以Two-beta模型为基础的中国股票市场换手率效应研究

基于2698家上市公司2000~2019年间的月度数据,对我国A股市场换手率效应的存在性及形成机制进行探讨。研究发现,我国股票市场存在显著的低换手率溢价现象,换手率与次月收益率呈显著负相关关系。平均而言,换手率最低组每月比换手率最高组的收益高出2.29%,并且该结论在控制了规模、流动性、特质波动率等8种定价因子之后依然稳健。此外,换手率效应无法用传统的FAMA因子定价模型解释,而从流动性溢价角度解释的比例也很低,平均仅为8.2%。进一步继承并拓展Twobeta模型进行研究,发现低换手率股票对应的企业拥有较高的现金流风险和较低的折现率风险,并且现金流风险拥有更高的风险价格,这造成了低换手率高收益现象,从而为换手率效应提供了全新的理论解释。     

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。     

我国股票市场报酬与波动的GARCH—M模型

一、绪论 根据资产定价理论,股票风险是股票价格的重要决定因素。现代财务学理论中,广泛地以波动代表风险,并可申资产报酬的标准差(或方差)度量?一般认为,投资者的投资决策是基于对股票报酬分布的认识,因此,股票报酬方差或标准差是影响投资行为的重要因素。同时,深刻了解股票市场波动(风险),分析引起波动的原因,并预测波动,政府可采取相     

审计行业专长与股价崩盘风险——基于信息不对称与异质信念视角的检验

使用2003—2012年A股非金融类上市公司数据,研究审计行业专长与股价崩盘风险之间的关系,发现审计行业专长有助于降低上市公司未来的股价崩盘风险,在信息不对称更严重以及投资者异质信念更大的公司,审计行业专长与股价崩盘风险之间的负相关关系更为显著。     

中国证券市场阶段划分的有序聚类分析

本文利用2002～2010年中国证券市场市场不确定性、股票错误定价和盈余管理数据,使用有序聚类分析方法对证券市场进行了两阶段划分。阶段划分结果表明2002～2006年为"平静时期",而2007～2010年为"动荡时期"。平静时期,股票错误定价主要由信息不对称下的企业盈余管理引起,因而宜用信息不对称理论进行解释;动荡时期,股票错误定价主要反映了投资者的非理性,宜用行为财务理论进行解释。     

机构投资者、信息披露质量与股价崩盘风险

采用2009—2014年A股上市公司的经验数据,以会计稳健性作为信息披露质量的替代变量,考察了机构投资者异质性、信息披露质量和股价崩盘风险之间的关系。研究发现,信息披露质量与股价崩盘风险显著负相关;将机构投资者划分为交易型机构投资者和稳定型机构投资者;进一步研究发现,与交易型机构投资者相比,信息披露质量与股价崩盘风险之间的负相关关系在稳定型机构投资者持股的上市公司更加显著。研究结论对于上市公司完善信息披露和防范股价崩盘风险具有一定的借鉴意义。     

互联网时代投资者行为对市场监管的启示 ——基于游戏驿站的案例分析

美国游戏驿站公司的股票在2021年1月和2月期间经历了剧烈的波动.梳理该股价波动事件的具体过程,对该公司的经营状况和财务报告进行分析,剖析股价快速大幅上涨以及之后迅速回落的原因.游戏驿站股价快速上涨的幅度脱离公司经营的基本面,互联网社交媒体和回音室效应使散户投资者联合起来针对做空的机构投资者进行掠夺式交易.该事件反映出美国资本市场和监管存在的问题.以此为鉴,在我国的资本市场建设过程中,应稳步推进卖空机制,防范系统性风险;提高股票定价的有效性;对于以社交媒体为代表的互联网平台,需识别其中潜在的股价操纵因素;通过投资者教育帮助投资者树立风险意识.     

负风险溢价对我国权证市场价格的影响

文章利用B—S期权定价公式对我国权证市场价格进行检验发现,大多数的权证存在着严重的价格泡沫,而少数认购权证的价格可能低于理论价格。文章认为对投资者的同质信念假设排除了股票的负的风险溢价,这就难以利用卖空约束解释期权和权证价格偏离完全市场的理论价格。股票市场的负的风险溢价来自于投资者的异质信念,将负风险溢价与卖空约束相结合,可以解释我国权证市场存在的一部分价格异象。     

Stock volatility and trading

Both, rational and behavioral models predict that stock and market volatility affect trading by investors. Tax-induced trading hypothesis predicts that investors increase realization of capital losses short term and capital gains only long term as volatility increases. Behavioral models predict that disposition biases of holding on to losers and disposing of winners intensifies with volatility. We document that market and stock volatility influence stock trading. Evidence on trading in response to rise in market volatility supports tax-loss harvesting hypothesis – abnormal trading of losers increases and winners decreases. However, evidence on trading patterns conditional on individual stock volatility is in support of both tax-loss-harvesting and behavioral models: trading in both losing stocks (tax-loss-harvesting hypothesis) and winning stocks (disposition effect hypothesis) increases with rise in stock volatility.     

Information transmission between small and large stocks in the National Stock Exchange in India: An empirical study

The study investigates return and volatility spillover effects between large and small stocks in the national stock exchange in India using daily index data on S&P CNX Nifty, CNX Nifty Junior and CNX Midcap. The VAR model together with the variance decomposition (VDC) and the impulse response function (IRF) analysis have been employed to uncover both casual and dynamic relationship between the large stocks and small stocks. The results show that there are very significant return spillovers from the market portfolio of large stocks to the portfolio of small stocks. To investigate the volatility spillover the study has used standard BEKK model and asymmetric BEKK model. Although, based on the standard BEKK model we have observed unidirectional volatility spillovers from the portfolio of large stocks to the portfolio of small stocks, the finding was less reliable. The more reliable finding, which is based on asymmetric BEKK model, is that there is bidirectional volatility spillover between the portfolio of large stocks and the portfolio of small stocks.     

中国股市的最大值效应

本文证实我国股市的投资者们长期存在对股票历史业绩的反应过度现象。我们发现历史上拥有最高收益率的股票在之后业绩都表现不佳。其主要原因是我国股市的投资者们在做投资选择时都遵循一条简单的规则:即在其他条件都相同的情况下,选择拥有最高的历史收益率的股票进行投资。集中投资使拥有最高的历史收益率的股票被过高评价,导致其后来的业绩表现要比那些拥有较低历史收益率的股票差。我们称之为"最大值效应"。通过使用Fama and Macbeth(1973)横断面回归分析方法,我们确认了"最大值效应"要比CAPM理论,Blitz and Pim van Vliet(2007)发现的"波动性效应"等更为有效地解释我国股市横断面股票收益率。     

Positive IVOL-MAX effect: A study on the Singapore Stock Market

This paper demonstrates a positive and significant IVOL effect in the Singapore Stock Market meaning that the highly volatile stocks are showing better returns in the subsequent month. More explicitly, there is a strong positive relationship between stock’s idiosyncratic volatility (IVOL) and its subsequent month’s return in the Singapore equity market. This positive IVOL effect is stronger only for small market-statistic firms. But for the Large capital firms, the positive IVOL effect is insignificant. In addition, this paper shows that the relationship between maximum daily return over a month (MAX) and the subsequent month’s return is positive and significant in this market. However, IVOL is the true effect of this market rather than MAX.     

Anticipating Long‐Term Stock Market Volatility

We investigate the relationship between long‐term US stock market risks and the macroeconomic environment using a two‐component GARCH‐MIDAS model. Our results show that macroeconomic variables are important determinants of the secular component of stock market volatility. Among the various macro variables in our dataset the term spread, housing starts, corporate profits and the unemployment rate have the highest predictive ability for long‐term stock market volatility. While the term spread and housing starts are leading variables with respect to stock market volatility, for industrial production and the unemployment rate expectations data from the Survey of Professional Forecasters regarding the future development are most informative. Copyright © 2014 John Wiley & Sons, Ltd.     

Intraday Volatility Spillover between the Shanghai and Hong Kong Stock Markets—Evidence from A+H Shares after the Launch of the Shanghai-Hong Kong Stock Connect

Using minute data of eligible A+H stocks under the Shanghai-Hong Kong Stock Connect (SHHKSC), we investigate the volatility spillover between the Shanghai and Hong Kong stock markets based on a generalized autoregressive conditional heteroskedasticity-X (GARCH-X) model with four exogenous variables, namely, volatilities of the corresponding stocks on the other market, volatilities of the indexes of both stock markets, and volatilities of the correlated stocks, which are selected using the dynamic conditional correlation model and bootstrap approach. Results show that after the launch of the SHHKSC, volatility spillovers are significant in both directions almost all the time, and the volatility spillover between the two stock markets tends to be larger when bidirectional capital flows under the SHHKSC increase or when important financial events occur. We also analyze the influences of the volatilities of correlated stocks and industries on the volatility spillover and volatilities of A+H stocks. The bidirectional volatility spillovers between Shanghai and Hong Kong stock markets do not change qualitatively after incorporating the volatilities of correlated stocks and industries in the GARCH-X model. Moreover, the average volatilities of the correlated stocks are shown to have significant influences on the volatilities of individual A+H stocks, and the influences increase when the local stock market shows a sharp rise or fall. Compared with the market indexes, the correlated stocks could be regarded as a more important and indispensable factor for individual A+H stocks’ volatilities modeling, which may carry more information than the industry.     

我国权证上市对标的股票的波动性影响研究

权证是基于标的股票产生的一种金融衍生产品,其与标的股票之间存在联动关系,因此,权证上市会对标的股票产生一定的影响。本文将通过EGARCH模型研究权证上市前后标的股票波动性的变化,据此探讨权证上市给标的股票波动性带来何种影响。     

Availability and settlement of individual stock futures and options expiration-day effects: evidence from high-frequency data

This study examines whether the expiration-day effects of stock options traded in Australian Stock Exchange on return, volatility, trading volume, and temporary price changes of individual stocks vary with the availability and the settlement method of individual stock futures contracts. Using transaction data of the stocks that have both options and futures contacts from 1993 to 1997, we find that options expiration has significant effects on return and volatility of the underlying stocks in absence of individual stock futures. After introduction of a cash-settled stock futures contract, the effects decrease notably. However, the switch of a futures contract from cash settlement to physical delivery promotes the expiration effects on return and volatility and boosts temporary price changes on expiration days. Finally, options expiration has little effect on trading volume. Trading activity tends to behave normally regardless whether stock futures contracts are available or not.     

Stock returns and volatility: Another look

Most empirical work examining the intertemporal mean-variance relationship in stock returns has tended to use relatively simple specifications of the mean and especially of the conditional variance. We augment the information set to include economic variables that other researchers have found to be important and use GARCH-M models to explore the relation between volatility and expected stock returns. We find that the additional variables have little impact on the conditional variance and that any intertemporal relationship between volatility and stock returns is weak or unstable. Our results signal the need for theoretical models of the intertemporal volatility-return relationship, and call for further studies of the determinants of the conditional variance of stock returns.     

Stock overreaction to extreme market events

The paper investigates the behavior of individual US stocks during the 21 trading days following the event of extreme movement in the market index on a day. We find that stocks tend to overreact after both positive and negative events, but in a more pronounced way in the latter case. This behavior is more intense when the market exhibits clustered extreme swings, indicating that the overreaction and market volatility are related. We also identify that the overreaction is driven by the performance of loser stocks that revert more strongly, even as they exhibit a lower market beta than winners.