节点文献
中国股票市场流动性风险溢价与资产定价研究
Research on Liquidity Risk Premium and Asset Pricing Based on Chinese Stock Market
【作者】 周芳;
【导师】 张维;
【作者基本信息】 天津大学 , 管理科学与工程, 2009, 博士
【摘要】 研究流动性风险溢价和资产定价是近年来金融研究领域中极具挑战性的工作之一。传统的资产定价理论在考虑风险时忽略了资产的不流动性所带来的风险,而越来越多的实证结果表明,流动性风险是一种系统性风险并影响资产价格。许多学者开始致力于将流动性风险引入传统的资产定价理论中,并且这方面的研究也已取得了很多有价值的成果。本文基于现有的资产定价理论,研究中国股票市场流动性风险溢价与资产定价问题。研究分8章撰写,内容主要涵盖以下四个方面:首先,对中国股票市场流动性风险溢价进行实证研究,采用OLS和GMM两种估计方法,通过检验CAPM模型、改进的Fama三因素模型和考虑流动性的两因素CAPM模型在中国股票市场的有效性,考察规模效应、价值效应和流动性风险溢价现象。其次,对导致市场异象的风险因素如流动性、公司规模和账面市值比之间的相关性进行研究,通过协整性检验、Granger因果性检验以及建立多元动态回归模型、向量自回归模型(VAR)和向量误差修正模型(VEC)揭示它们之间的因果性和相关性。以上研究为流动性风险定价和资产定价提供了理论依据和必要准备。然后,借助金融数学和金融工程的无套利思想在鞅测度下对市场风险和流动性风险进行定价,进而得到计算流动性风险溢价的表达式。最后,从风险构成的角度构建流动性风险调整的资本资产定价模型LACAPM。论文的主要创新体现在:(1)对中国股票市场的流动性风险溢价现象和规模效应以及价值效应进行了系统研究。研究表明CAPM模型不能解释这些市场异象,而改进的FAMA三因素模型基本可以解释价值效应,但不能解释规模效应,更不能解释流动性溢价现象,考虑流动性的两因素CAPM模型在解释市场异象上的有效性取决于流动性测度指标的选取,而综合考虑了流动性的两个度量指标换手率和非流动性指标的LACAPM不仅能够解释规模效应和价值效应,还可以较好地解释流动性风险溢价现象。(2)揭示了流动性与公司规模和账面市值比之间的相关性。Granger因果性检验表明,公司规模和帐面市值比之间、换手率和非流动性比率之间不存在Granger因果关系,即其中一个变量的滞后变量对另一个变量不产生影响。而在考虑了换手率和非流动性比率后公司规模对账面市值比存在着显著的Granger因果关系。换手率与公司规模波动之间则存在显著的双向Granger因果关系。虽然公司规模(SIZE)波动、换手率(TURN)和非流动性比率(ILLIQ)各自对账面市值比(BM)波动没有明显影响,但当滞后期足够长(12个月)时三者的联合对账面市值比(BM)波动产生显著影响。多元动态回归模型、VAR模型和VEC模型也表明,无论是对公司规模和账面市值比本身,还是对公司规模变动和账面市值比变动,换手率和非流动性比率都具有非常显著的解释能力。(3)在鞅测度下对市场风险和流动性风险进行定价,并给出了充分分散化证券组合的流动性风险的测度,解决了充分分散化证券组合(如基金)的流动性风险溢价的测算问题。(4)从风险构成的角度给出了单个证券的流动性风险的测度和流动性风险的市场价格,构建出两种形式的流动性风险调整的资本资产定价模型LACAPM(风险以相对量表示的LACAPM和风险以绝对量表示的LACAPM)。本文的研究拓展了现有的资产定价模型研究的思路,并为流动性风险测度和风险资产定价提供了一种新的方法。因此,本文的研究成果对于资产定价理论与方法的发展以及在投资决策和风险管理上的应用具有重要的理论意义和实际价值。
【Abstract】 Study on liquidity risk premium and asset pricing has been one of the mostchallenging work in finance field in recent years. Traditional asset pricing theoriesonly consider market risk and thus liquidity risk is ignored, but more and moreempirical researches show that liquidity risk is also a systemic risk and affects assetprices. Many researchers have tried to introduce liquidity risk to classic asset pricingtheories, and have achieved some interesting and valuable results.Based on the recent asset pricing theories, this paper investigates the liquidity riskpremium in Chinese stock market and the pricing of risky asset. The paper consistsof eight chapters involving the four main sections. Firstly, the paper empiricallystudies size effect and value effect and liquidity risk premium in Chinese stockmarket, through testing the validity of the CAPM, the improved Fama three-factormodel and the two-factor CAPM with liquidity by using two estimation methods ofOLS and GMM. Secondly, the paper analyzes the relationship between the riskfactors such as liquidity and firm size and book-to-market ratio that lead to the marketanomalies by using cointegration test and Granger causality test, and buildingdynamic multivariate regression models, VAR and VEC. The results are prepared forthe next pricing of liquidity risk and asset. Thirdly, the paper discusses the pricing ofmarket risk and liquidity risk under martingale measure by employing the no-arbitrageidea of financial calculus and finance engineering, and then constructs the pricingformula of liquidity risk premium. Finally, from the view of composition of risk, aliquidity risk-adjusted capital asset pricing model (LACAPM) is therefore established.The originalities of this paper are reflected in the following aspects:(1)The systematically analyses are conducted over market anomalies forChinese stock market including liquidity risk premium and size effect and value effect.Studies show that the CAPM can not explain market anomalies, and the improvedFama three-factor model can only explain value effect, but can not explain size effectand liquidity premium, and the validity of the two-factor CAPM with liquidity in explaining market anomalies depends on the liquidity measure. The two-factor CAPMbased on two liquidity measures of turnover and illiquidity ratio can not only explainsize effect and value effect, can also better explain the liquidity risk premium.(2)The correlation between the risk factors affecting market anomaliesincluding liquidity and firm size and book-to-market ratio are explored. Grangercausality test shows that there are no Granger causal relations between company sizeand book-to-market ratio, between turnover and illiquidity ratio, that is, the laggedvariable of one variable does not affect another variable. But firm size has strong Grangercausality on book-to-market ratio after turnover and illiquidity ratio are considered,and thereversal does not exist. The test proves that there exists bilateral Granger causalitybetween turnover and the volatility of firm size. Though turnover and illiquidity ratioand the volatility of firm size have no obvious effect on the volatility ofbook-to-market ratio respectively, all three variables together have a significantimpact on the volatility of book-to-market ratio when lag intervals are long enough(12months). The dynamic regression models, the VAR and the VEC also indicate that,either on firm size and book-to-market ratio their own, or on their volatilities, turnoverand illiquidity ratio have significant explanatory power.(3)The market prices of market risk and liquidity risk under martingale measureare provided, and the liquidity risk measure of the fully diversified portfolio is alsooffered, so the quantification of liquidity risk premium of the diversified portfolio(such as the diversified fund) is solved.(4)The liquidity risk measure of a single asset and the market price of liquidityrisk are proposed from the view of composition of risk, liquidity risk-adjusted capitalasset pricing model LACAPM with two types of the relative amount of risk and theabsolute volume of risk is constructed.The research extends the ideas of the recent research of asset pricing models andprovides liquidity risk measure and asset pricing with a new method. Therefore, theworks make some contributions to the development of asset pricing theories,methodsand applications in investment decision and risk management.
【Key words】 Liquidity; Risk Premium; VAR; Martingale Measure; Capital AssetPricing Model;