没有信息,也有反应:中国A股市场股票名称变更事件的市场反应研究

本文以 1 999年到 2 0 0 1年发生股票名称变更的 1 48家上市公司为样本 ,研究股票名称变更对股价的短期影响。研究发现 ,不具有任何经济意义 ,也不向市场传递任何新信息的公司股票名称变更“事件”可以像具有经济意义 ,包含新信息的“事件”那样引起股票价格的显著波动 ,而且这一波动呈现出过度反应特征。这种股价波动可能与中国 A股市场投资者的投机行为有关。由于既具有“事件”特征 ,同时又不包含新的信息的“非事件”在证券市场上很少出现 ,我们的这一研究为探讨证券市场的有效性和研究投资者对信息的反应特征提供了新的线索和资料。     

我国A股上市公司高送转行为的市场表现及其具体成因研究

文章基于2010年至2015年的我国A股上市公司高送转股票样本数据,采用计量方法分析了A股市场上的高送转现象。在市场对高送转股的反应研究方面,发现高送转股票在分红预案公告日附近存在着超额收益。在高送转现象成因的研究方面,发现我国A股上市公司存在着进行高送转以降低股价,进而增加股票流动性的动机。此外,随着上市公司高送转的水平不同,信号传递假说和信号传递假说在解释其进行高送转的具体成因的有效程度也随之发生不同。     

基于Fama-French三因素模型的我国A股市场的实证分析

实证检验了Fama-French三因素模型描述我国A股市场期望超额收益率的解释能力。分别针对上证A股和深证A股做了四类模型的回归分析,为了能够从各类模型的对比中准确地捕捉到各因素影响投资组合期望超额收益率动态特征。结果显示,随着公司规模和账面市值比的变化,市场风险因素的系数变化不大,而规模风险因素的系数和账面市值比风险因素的系数呈现巨大差异,模型的拟合效果表明Fama-French三因素模型在我国A股市场表现出相当高的解释能力。     

投资者行为与股市波动

本文基于行为金融学对投资者行为的心理学研究成桌，构建了一个反映投资者预期形成过程的行为模型。模型考察了外部冲击对股价影响的长短期效应，较好的解释了实证研究发现的金融市场上普遍存在的一些异常现象，诸如收益率分布的厚尾现象，股价对信息反映不足或过度，市场对国有股减持的过度反应等等，并提出了规范股市减少异常波动发生的政策建议。     

资本市场开放能够提高股票价格稳定性吗?:基于沪港通的经验证据

基于2012年11月至2016年11月上海证券市场的月度面板数据,文章通过双重差分固定效应模型,分别从不同期间、不同市场开放程度入手,研究沪港通对股票价格稳定性的影响。研究发现,沪港通的实施有效降低了标的股票的整体波动性,波动性在短期的增加只是一种暂时性的现象,沪港通的实施通过扩大股票投资者基础、优化市场投资者结构从而对股价稳定性带来积极影响。随着市场开放程度的增加,沪港通也会对股票的极端波动产生影响,降低公司股价跳升风险,有利于缓解A股市场的投机氛围,但同时也增加了公司股价崩盘风险,带来市场不稳定因素。沪港通实施后公司股票的崩盘风险与中国证券市场薄弱的信息披露环境有关,那些信息披露环境差的公司股票的崩盘风险显著增加。     

A股市场过度反应的新证据——基于A股和H股估值变化的视角

传统的检验市场过度反应的方法是采用De Bondt和Thaler构造的赢家组合和输家组合,通过检验赢家组合和输家组合的超额收益率来判断市场是否存在过度反应。有别于传统的检验市场过度反应的方法,本文基于我国股票市场上A股和H股估值变化的特殊视角,实证分析了我国A股市场存在的过度反应现象。     

融资融券对我国上市券商股价波动的影响

融资融券交易是一种保证金杠杆交易模式,该制度的建立能够有效解决单边市场投机导致的暴涨暴跌问题,有助于降低股价的波动,维护市场稳定。但只有理性投资者才会通过融资融券交易的杠杆效应降低股价的波动性。若投资者是非理性的,融资融券的高杠杆性可能会带来助长投机,放大市场波动,加剧股价的波动。文章选取我国上市证券公司标的股为研究对象,进行实证分析,发现融资融券业务对我国上市券商股价波动率的影响。     

股权激励、股价波动与盈余管理——基于中国上市公司的经验证据

本文选取我国A股上市公司中,2006-2009年公告股权激励实施方案的113家公司为研究样本,检验实施股权激励前后股价的异常波动情况,解释和检验这种异常波动是否是由于高管盈余管理行为造成的,据此为监管层和投资者提出建议.     

中国A、B股市场收益波动风险的度量及比较

本文运用 GARCH方法对 1 996年 1 2月以来深圳和上海两地的 A、B股市场收益的波动风险进行了度量。经比较发现 :中国 B股市场收益的波动风险在绝大部分时间要高于 A股市场。在此基础上 ,本文对中国 A、B股市场风险差异的成因进行了分析 ,认为有效监管、降低市场风险对证券市场的发展有重要意义。     

我国股市波动非对称性和混合分布假定的经验分析

混合分布假定(MDH)用信息流的自相关结构解释收益波动的GARCH效应和持续性。本文先运用EGARCH—GED模型考察沪深A、B股市场的波动非对称性,发现A股市场波动显著非对称、B股市场“杠杆效应”不显著。然后,我们根据“杠杆效应”的显著与否,把同期交易量作为信息替代指标分别引入EGARCH—GED和GARCH—GED模型的条件方差方程,实证检验混合分布假定。最后,我们比较预期和未预期交易量对条件方差的解释力。研究表明：在B股和上证A股市场上,同期交易量对收益波动的GARCH效应和持续性有显著的解释力;同期交易量不能作为市场信息的完全替代指标;未预期交易量对收益波动有显著的解释力、比预期交易量的解释力强。     

Trump’s Effect on the Chinese Stock Market

U.S. President Donald J. Trump tweets frequently to communicate his thoughts to the public. We quantitatively evaluate the impact of Trump's China-related tweets on the Chinese stock market. We find that following Trump’s inauguration, his tweets with a positive sentiment significantly increase abnormal returns for the manufacturing industry in the Chinese stock market. Furthermore, an increase in the absolute value of his positive sentiment increases both the trading volume and volatility of the market. The positive effect is more pronounced for those subindustries with high exposure to international trade and stronger business relations with the United States than for other subindustries. The results are robust for various sensitivity tests.     

Long-Run Comovements in East Asian Stock Market Volatility

Two integrated stock markets are generally subjected to common shocks revealing that commonalities in fundamentals drive their underlying return processes. In such a case, volatility series should share a long-run component although their transitory components might temporary diverge. In this paper, we investigate stock market integration in East Asia by analyzing the co-persistent nature of their ex-post observed volatility. Using recent fractional cointegration techniques, we find that volatility of several markets converges in the long run to a common equilibrium. Our results reveal that a global integration process drives the most developed markets of the region, while no evidence of co-persistence appears for emerging markets.     

Transmission of Stock Prices and Volatility from the Influential Major Markets on the Emerging Market: A Case Study of the Korean Stock Market

Abstract

This study investigates how the 1997 crisis has changed the Korean market by focusing on price and volatility spillovers from the US, Chinese, and Japanese markets. Using the exponential general autoregressive conditional heteroskedastic (EGARCH) model, new information on stock prices originating in the US market was transmitted to the Korean market for all periods. The price spillover effect from the Japanese market to the Korean market became stronger from the crisis period. Asymmetry in the spillover effect on market volatility was more pronounced in the Korean market after the financial crisis.     

Volatility and Volume in Chinese Stock Markets

The fact that stock market returns in Europe and the USA are characterised by conditional heteroscedasticity is by now well documented in a large literature. We address the question of whether the same is true of the four Chinese stock markets (Shanghai and Shenzhen A and B) over the period from 25 November 1994 to 27 April 2001. Using daily index data, we make two departures from the standard GARCH(1,1) model. First, we use exponential GARCH (EGARCH) to allow for asymmetry in the volatility, which may be present as a result of leverage effects. Second, we respond to evidence of two-way causality between volume and return (and return volatility) by introducing a simultaneous equation model of the relationship. The results of estimating the model indicate that asymmetry does not seem to be present to a significant degree, possibly as a result of lack of information or concern among Chinese investors. We find that volume appears to play a significant part in determining index volatility, which may reflect information arrival effects or may alternatively result from the direct impact of trading on volatility. At the same time, we also find that both the level of returns and their conditional variance have an impact on trade volume, probably because positive (negative) returns tend to attract (deter) investors into the markets.     

后金融危机时期中国股市的国际地位——基于非线性视角的股市联动网络分析

后金融危机时期全球股市一体化程度不断提高,全面认识中国股市的国际地位对于揭示国际股市一体化联动中的传导机制,防范和应对国际金融风险冲击具有重要的理论意义和现实价值。文章应用非线性格兰杰因果检验方法和社会网络分析方法,对金砖国家和七国集团股市收益率和波动率的联动关系及其联动网络结构进行分析,揭示出中国在国际股市联动中的地位对传导关系的控制方式,定量分析出事件冲击下中国股市与国际股市之间的交互影响。研究发现：（1）国际股市收益率和波动率联动网络呈现出稳定的非线性联动关系网络结构,受其影响各国股市收益之间存在互惠性,而波动之间则存在传染性;（2）在收益率联动网络中,中国股市的作用和地位已与英国相当,远高于其他金砖国家,正逐渐由"从属地位"转向"中心地位";（3）在波动率联动网络中,中国股市是造成国际股市风险交叉影响的重要"桥梁"。综上而言,当前中国股市表现出"高风险低收益"的市场特征;（4）中国对国际股市的影响具有典型的"地缘特征",将网络中心国家股市的利好传递给地缘临近国家股市;（5）波动率联动网络中初始冲击强度较大的国家,往往是对中国股市持续大规模产生冲击的国家;（6）相比较国际股市调整波动冲击的时间而言,中国股市调整时间较短,这表明后金融危机时代中国致力于股市的一系列改革举措取得了显著成效。     

印花税政策调整对市场反应影响研究

文章使用中国A股市场的日数据检验了印花税税率的调整对市场流动性、市场的波动和股票异常收益率的影响.实证的结果表明,印花税税率的变化和市场流动性呈反向关系,但并不总是如此.与一般认知不同的是,无论印花税税率的增加还是减少都不会引起市场波动加剧.相应的,股票异常收益率对对印花税税率的变化也并不总是敏感的.基于上述实证结果,文章认为印花税并不是调控证券市场的有效政策工具.     

The effect of index futures trading on volatility: Three markets for Chinese stocks

This paper examines whether the introduction of Chinese stock index futures had an impact on the volatility of the underlying spot market. To this end, we estimate several Generalized Auto-regressive Conditional Heteroscedasticity (GARCH) models and compare our findings for mainland China with Chinese index futures traded in Singapore and Hong Kong. Our results indicate that Chinese index futures decrease spot market volatility in all three spot markets considered. In contrast, we do not obtain the same results for the companion index futures markets in Hong Kong and Singapore. China's stock market is relatively young and largely dominated by private retail investors. Nevertheless, our evidence is favorable to the stabilization hypothesis usually confirmed in mature markets.     

基于Copula-GARCH模型的原油市场和股票市场相关性研究

由于原油市场和股票市场之间的联动性日益增强,因此研究两个市场之间的关联特征,分析原油价格波动对股市的影响,有助于规避风险,保证经济持续平稳地增长.采用Copula-GARCH模型对WTI原油价格的收益率序列和NASDAQ股指的收益率序列进行实证分析.结果表明,GARCH(1,1)-t模型拟合两个序列的条件边缘分布效果最好,时变SJC Copula模型比常相关Copula模型能更好地刻画两个市场之间的相关关系.两个收益率序列之间存在正的相关关系,且相关关系具有时变性,相关结构具有一定的不对称性,上尾相关系数小于下尾相关系数,即两个市场同时出现价格极端下跌的可能性更大.这为中国金融市场风险管理,规避油价波动对股市的冲击提供一定的参考依据.     

Examining Stock Volatility in the Segmented Chinese Stock Markets: A SWARCH Approach

Abstract

This study adopts the SWARCH model to examine the volatile behavior and volatility linkages among the four major segmented Chinese stock indices. We find strong evidence of a regime shift in the volatility of the four markets, and the SWARCH model appears to outperform standard generalized autoregressive conditional heteroskedasticity (GARCH) family models. The evidence suggests that, compared with the A-share markets, B-share markets stay in a high-volatility state longer and are more volatile and shift more frequently between high- and low-volatility states. In addition, the relative magnitude of the high-volatility compared with that of the low-volatility state in the B-share markets is much greater than the case in the two A-share markets. B-share markets are found to be more sensitive to international shocks, while A-share markets seem immune to international spillovers of volatility. Finally, analyses of the volatility spillover effect among the four stock markets indicate that the A-share markets play a dominant role in volatility in Chinese stock markets.