股票日内流动性度量及其风险调整——基于上海股票市场高频数据的实证研究

流动性是股票市场的重要属性,但对流动性进行准确的定义和度量却是一件困难的事情。本文给出了股票流动性度量的三个指标,并对这些指标进行了风险调整。最后利用风险调整后的指标对上海股票市场的样本股票进行了截面相关分析,得出风险调整后的流动性指标逻辑关系更加紧密的结论。     

中国股票市场流动性的实证研究

本文根据我国A股市场股票的日交易数据计算出市场非流动性比率的时间序列,采用ARMA-GARCH族模型建立我国股票市场流动性AR(1-TARCH(1,1))模型。结果表明,我国股票市场流动性具有持久性,流动性成本可以预测收益。此外,我国股票市场流动性的波动具有非对称性。     

VaR模型中流动性风险的度量

虽然传统的VaR模型已经被广泛应用于度量价格风险和信用风险，但是对流动性风险度量的考虑不多。本文归纳总结了关于如何把流动性风险度量纳入VaR模型已有的研究成果，并结合中国股票市场的实际特点，建立了一个对流动性风险进行调整的VaR模型，用以度量中国股票的价格风险和流动性风险。本文还以沪深两市的A股为样本进行了实证分析，结果证明考虑了流动性风险后，流动性差的股票其风险价值(VaR)显著大于传统的VaR模型测算的风险价值。     

股票市场间的流动性动态关系研究

随着金融市场之间的相关性逐渐增强,流动性作为反映资产的变现速度和交易能力的证券市场首要属性,是需要多视角、多层次的研究。对我国内地股市和香港股市的证券流动性动态关系的实证研究发现,两个市场之间的流动性信息是相互传递,香港恒生指数非流动性指标对内地沪深300指数非流动性指标有引领和发现作用,对于反向的引领和发现作用,脉冲响应曲线表现出内地股票市场对香港股票市场非流动性指标也有影响。     

略论标准属性

本文从标准制定的依据上，参数指标上，技术要素上和应用范围上，论述了标准的本质属性具有科学性、先进性、度量考核性和适用性。标准的本质属性（也称自然属性），就是指标准的本身要素组成的文体结构内容所具有的性质。因此，标准的本质属性梗可从标准制定的依据上，参数指标上，技术要素上和应用范围上进行揭示，其本质属性具有：科学性、先进性、度量考核性和适用性。     

股票市场流动性溢价的实证研究

资产流动性的高低是否影响资产的价格一直是资本市场理论研究的热点问题，也是投资者决策的重要理论依据之一。本文根据股票市场流动性溢价原理，选取换手率与Amivest流动比率作为股票流动性的衡量指标，采用LR两阶段截面回归方法与似无关回归（SUR）估计法，对上海股票市场的股票流动性与预期收益率的关系进行了实证研究。结果表明，上海股票市场存在显著的流动性溢价，换手率低或Amivest流动比率低，流动性较差的资产具有较高的预期收益。研究同时发现，上海股票市场具有很强的规模效应和价值效应。     

股票市场流动性应用研究概述

流动性是证券市场的生命力。研究股票市场流动性对于加强市场流动性的评估、提升流动性风险定价能力,以及提升市场流动性具有重要意义。本文对流动性的概念进行归纳,分析流动性在公司金融、市场效率及资产定价中的应用研究,展望其在中国市场的未来发展。     

股票市场对居民储蓄的影响:一个实证分析

长期以来，股票市场与居民储蓄的关系问题，理论界一直存在着争论。本文的实证分析表明，我国股票市场发展的规模和流动性与居民储蓄具有相关性，能够在一定程度上影响储蓄量的变化；同时，股市的流动性对居民储蓄有着明显的分流作用，股市交易的活跃程度和股指的涨跌直接影响着投资者以及潜在投资者的储蓄行为。     

论增强流动性是当前我国股票市场建设的首要任务

文章从中国股票市场目前不正常的走势引入问题,从股票市场功能发挥的角度,以中外学者的研究为基础,结合中国股票市场的现状,得出股权分置、缺乏流动性是制约我国股票市场发挥应有功能的根本原因,并在研究的基础之上指出,增强流动性是我国当前股票市场建设的重要任务。     

中国股票市场流动性与预期收益实证研究

本文以国外流动性溢价理论和研究方法为基础,结合我国股票市场的实际情况,运用现代计量技术对流动性和预期收益之间的关系进行了实证研究,检验我国股票市场是否存在流动性溢价现象。实证结果表明:我国股票市场存在着显著的流动性溢价现象,并支持小公司效应和价值效应。     

证券市场流动性及其影响因素研究

流动性是证券市场运行质量的重要衡量指标。文章对证券市场流动性内涵进行归纳与总结,重新定义流动性内涵,认为证券流动性是证券资产与现金资产的相互转换能力,并对流动性与流通性的内涵进行了辨析;同时,文章还对影响证券市场流动性的因素加以总结,结果发现,证券交易特征、交易成本、市场竞争程度、交易机制与市场透明性等因素显著影响市场流动性水平。     

中国A股市场“小公司效应”的实证分析

本文以1995年1月至2003年12月期间在上海、深圳证券交易所交易的的全部A股股票为样本,分别以流通市值与总市值来衡量公司规模,对中国A股市场的“小公司效应”进行实证分析,研究表明:①作为规模度量的流通市值与总市值的选择对公司规模的排序没有显著影响。②最小规模公司股票组合获得显著的超额收益,且拥有最高的经风险调整后的收益(Sharpe比率),中国A股市场存在“小公司效应”。     

中小企业板市场流动性问题研究

流动性是资本市场或者说整个金融市场的重要特征。本文对其内在涵义、基本特征进行界定与刻画;进而辨析了几对容易混淆的相关范畴,阐释中小企业板市场流动性研究的理论意义;对其影响因素予以剖析,从中提炼出对策与建议。     

我国沪深证券市场流动性实证研究

流动性是一个市场的生命力所在。一个流动性好的市场才能很好的满足投资者的交易需求,减少投资者流动性风险是市场应该提供的功能之一。随着我国资本市场的逐步发展和成熟,投资者越来越注意到市场流动性的重要性。如何准确的界定流动性,如何用一系列的指标体系,来衡量一个市场的流动性,是理论界和市场投资者都很关注的问题。国内外对流动性的研究也很多,本文在借鉴前人研究成果的基础上,提出了自己对于流动性测量的一种观点,通过建立一个基于收益率和相对交易量基础之上的模型,来探讨关于市场流动性的问题。     

Risk spillover between the US and the remaining G7 stock markets using time-varying copulas with Markov switching: Evidence from over a century of data

This paper analyses the risk spillover effect between the US stock market and the remaining G7 stock markets by measuring the conditional Value-at-Risk (CoVaR) using time-varying copula models with Markov switching and data that covers more than 100 years. The main results suggest that the dependence structure varies with time and has distinct high and low dependence regimes. Our findings verify the existence of risk spillover between the US stock market and the remaining G7 stock markets. Furthermore, the results imply the following: 1) abnormal spikes of dynamic CoVaR were induced by well-known historical economic shocks; 2) The value of upside risk spillover is significantly larger than the downside risk spillover and 3) The magnitudes of risk spillover from the remaining G7 countries to the US are significantly larger than that from the US to these countries.     

Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis

This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators.     

Contestability of the urban land market: an event study of Hong Kong land auctions

The traditional theory of urban land markets assumes perfect contestability—the absolute freedom of market entry—that compels developers to bid up the land rent to equal the economic profit from land use. This assumption, however, is empirically untested due to the difficulties in measuring the ex ante economic profit of land acquisition. We overcome these difficulties by applying the event-study methodology to Hong Kong government land auctions. When a developer acquires a site at a price below its fair market value, the rationality of the stock market entails a positive abnormal return on the developer’s stock. Our analysis shows evidence of positive expected abnormal returns, indicating an imperfectly contestable land market. We further show that the expected abnormal return increases with the site value and the government land disposal level but decreases with the property market liquidity.     

中国股市日内流动性效应分析——基于高频数据的流动性度量、特征及其影响因素

本文归纳了流动性刻画维度和度量指标,选取不同规模和价位股票的高频数据作样本,吸收Amivest流动性比率计算原理,设定价格对交易量变动的敏感性为流动性度量指标,分析股票日内交易特征和流动性影响因素。结果发现：日内模式价格变动呈仰卧“F”形,交易量呈仰卧“E”形,而非传统的“L”或“U”型;日内交易模式、股票规模和股票价位均影响着股票流动性;日内模式异动时间内,股票流动性差;大规模股票流动性强;高价股流动性差。     

Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market

Given the growing need for managing financial risk and the recent global crisis, risk prediction is a crucial issue in banking and finance. In this paper, we show how recent advances in the statistical analysis of extreme events can provide solid methodological fundamentals for modeling extreme events. Our approach uses self-exciting marked point processes for estimating the tail of loss distributions. The main result is that the time between extreme events plays an important role in the statistical analysis of these events and could therefore be useful to forecast the size and intensity of future extreme events in financial markets. We illustrate this point by measuring the impact of the subprime and global financial crisis on the German stock market in extenso, and briefly as a benchmark in the US stock market. With the help of our fitted models, we backtest the Value at Risk at various quantiles to assess the likeliness of different extreme movements on the DAX, S&P 500 and Nasdaq stock market indices during the crisis. The results show that the proposed models provide accurate risk measures according to the Basel Committee and make better use of the available information.