A new test on the conditional capital asset pricing model

Testing the validity of the conditional capital asset pricing model(CAPM) is a puzzle in the finance literatureLewellen and Nagel[14]find that the variation in betas and in the equity premium would have to be implausibly large to explain important asset-pricing anomaliesUnfortunately, they do not provide a rigorous test statisticBased on a simulation study, the method proposed in Lewellen and Nagel[14]tends to reject the null too frequently.We develop a new test procedure and derive its limiting distribution under the null hypothesis.Also, we provide a Bootstrap approach to the testing procedure to gain a good finite sample performanceBoth simulations and empirical studies show that our test is necessary for making correct inferences with the conditional CAPM.     

Capital Asset Pricing Model (CAPM) with drawdown measure

The notion of drawdown is central to active portfolio management. Conditional Drawdown-at-Risk (CDaR) is defined as the average of a specified percentage of the largest drawdowns over an investment horizon and includes maximum and average drawdowns as particular cases. The necessary optimality conditions for a portfolio optimization problem with CDaR yield the capital asset pricing model (CAPM) stated in both single and multiple sample-path settings. The drawdown beta in the CAPM has a simple interpretation and is evaluated for hedge fund indices from the HFRX database in the single sample-path setting. Drawdown alpha is introduced similarly to the alpha in the classical CAPM and is evaluated for the same hedge fund indices. Both drawdown beta and drawdown alpha are used to prioritize hedge fund strategies and to identify instruments for hedging against market drawdowns.     

Research on Flood Loss Distribution and Catastrophe Bond Pricing Based on Bayesian Inference

Taking flood catastrophe risk in China as the research background, aiming at the characteristics of flood loss ``low frequency and high loss', Bayesian inference method is used to fit the loss distribution, and Bayesian inference is used to obtain the loss frequency distribution and loss quota distribution of flood in China. On this basis, Monte Carlo simulation method is used to calculate the probability distribution of annual flood loss in China under different trigger conditions, and then CAPM is used to study the pricing of flood catastrophe bonds in China. It is concluded that under different trigger conditions, as the trigger value increases gradually, the corresponding trigger is triggered. Comparing the three types of bonds, it can be found that the price of bonds decreases with the decrease of principal guarantee ratio and the increase of principal loss ratio, that is, the investment risk is directly proportional to the return, which provides reference for issuing flood catastrophe bonds in China.     

对CAPM模型检验中独立同分布正态假设重要性的实证分析

金融市场的数据大多不是iid正态的,但是通常针对CAPM的Wald检验和F检验均是基于这一假设的。本文采用一种不需要iid正态假定的基于GMM方法的检验统计量,对同一原假设进行了检验,并且将结果与美国和澳大利亚股市的实证结果进行了比较。结果表明上海股市的确不满足iid正态,而且GMM统计量的检验结果和通常的检验存在差异并有可能影响到判别的结果。     

Leaders and followers in mutual funds: A dynamic Bayesian approach

This article proposes a dynamic Bayesian framework to analyze the leadership relationships between mutual funds. To this end, a two‐step procedure is proposed. First, a Bayesian rolling window based on the Capital Asset Pricing Model is used to estimate the evolution of mutual funds' market exposure over time. Then, a vector autoregressive (VAR) model is used to analyze the leader‐follower relationship between pair of mutual funds. Several leadership measures are studied. An application to Spanish mutual funds is carried out. In addition, the study examines the determining factors of mutual fund leadership.     

资本资产定价模型与上海股票市场的实证分析

借助SPSS10．0软件,以上海股票市场2000．06．30～2002．09．27期间(共109周)代码为600601～600640中的37支股票为样本,对资本资产定价模型(CAPM)在上海股票市场的应用进行实证研究,首先采用单指数模型估计了个股的B系数,然后利用BJS方法和FM模型分别进行时间序列回归和截面回归,并进行了假设检验,研究结果表明在上海股票市场上,股票的收益与其β系数存在着显著的正相关线性关系,但无风险收益率却是负的,这说明沪市具有明显的投机特征。为了消除单个股票的非系统性风险,进一步构造股票投资组合对CAPM模型进行修正检验,结果与BJS方法和FM模型得出的结论相同,但β系数能更好地衡量股票组合的风险。     

On the optimization of a CAPM portfolio using lower partial moments as measure of risk and using the possibility of safeguarding its loss

Using a portfolio built from bonds (investment without volatility) and shares (investment with volatility) corresponding to the CAPM we calculate the possible loss of this portfolio. The loss is measured by a so-called lower partial moment of the rate of return of the portfolio. Using this loss, we optimize the composition of the portfolio with respect to this loss. Also we investigate the optimization of the portfolio when the loss can be underwritten by an insurance. Concerning the premium of this insurance contract, we show that when the premium is defined inadequate, e.g. proportional to the investment or proportional to the amount of investment in shares, the optimal portfolio consists only of investment in shares. When the premium is defined more suitable, e.g. proportional to the loss, the optimal portfolio is built by an investment in bonds and shares.     

On the Spurious Correlation Between Sample Betas and Mean Returns

Abstract

Cornerstone asset pricing models, such as capital asset pricing model (CAPM) and arbitrage pricing theory (APT), yield theoretical predictions about the relationship between expected returns and exposure to systematic risk, as measured by beta(s). Numerous studies have investigated the empirical validity of these models. We show that even if no relationship holds between true expected returns and betas in the population, the existence of low-probability extreme outcomes induces a spurious correlation between the sample means and the sample betas. Moreover, the magnitude of this purely spurious correlation is similar to the empirically documented correlation, and the regression slopes and intercepts are very similar as well. This result does not necessarily constitute evidence against the theoretical asset pricing models, but it does shed new light on previous empirical results, and it points to an issue that should be carefully considered in the empirical testing of these models. The analysis points to the dangers of relying on simple least squares regression for drawing conclusions about the validity of equilibrium pricing models.     

Optimal portfolio choice and stochastic volatility

In this paper we examine the effect of stochastic volatility on optimal portfolio choice in both partial and general equilibrium settings. In a partial equilibrium setting we derive an analog of the classic Samuelson–Merton optimal portfolio result and define volatility‐adjusted risk aversion as the effective risk aversion of an individual investing in an asset with stochastic volatility. We extend prior research which shows that effective risk aversion is greater with stochastic volatility than without for investors without wealth effects by providing further comparative static results on changes in effective risk aversion due to changes in the distribution of volatility. We demonstrate that effective risk aversion is increasing in the constant absolute risk aversion and the variance of the volatility distribution for investors without wealth effects. We further show that for these investors a first‐order stochastic dominant shift in the volatility distribution does not necessarily increase effective risk aversion, whereas a second‐order stochastic dominant shift in the volatility does increase effective risk aversion. Finally, we examine the effect of stochastic volatility on equilibrium asset prices. We derive an explicit capital asset pricing relationship that illustrates how stochastic volatility alters equilibrium asset prices in a setting with multiple risky assets, where returns have a market factor and asset‐specific random components and multiple investor types. Copyright © 2011 John Wiley & Sons, Ltd.     

投资者情绪影响下资本资产定价的区制性研究——基于股票论坛发帖的情感分析

本文首先建立一个考虑投资者情绪的资本资产定价模型,研究发现,投资者情绪是资产定价的系统性因子且对其影响具有区制性(存在三个区制)。在此基础上通过仿真揭示投资者情绪对资产定价影响存在区制性的原因在于当投资者情绪增加时,最优组合超额收益受组合效应与情绪效应的综合影响。最后基于股票论坛发帖的情感分析构建投资者情绪指标,实证检验了本文的理论模型,并发现基于普通的线性回归模型得到的投资者情绪对股指超额收益影响,一方面会在投资者情绪处于第二区制内时将其对股指超额收益影响方向弄反,另一方面会在投资者情绪处于第三区制内时低估其增加导致的股指超额收益平均增加程度。