如何使用贝塔系数投资

贝塔系数(也记为β)起源于资本资产定价模型(CAPM 模型),它的含义就是指特定资产或资产组合的系统风险度量.所谓系统风险,是指资产受宏观经济、市场波动等整体性因素影响而发生的价格波动.换句话说,就是股票与大盘之间的连动性,系统风险比例越高,连动性越强.     

基于GARCH模型的贝塔系数均值回归分析

资本资产定价模型(CAPM)中的贝塔系数被认为是证券组合和单个证券风险大小的衡量指标,近年来理论界对于CAPM中的贝塔系数并非常数已达成共识。但贝塔系数不稳定,并不意味着CAPM模型完全失去作用。本文的研究表明,上海股票市场股票的贝塔系数虽然具有波动性,但是多数股票的贝塔系数遵循一个均值回归过程。     

中国沪市资本资产定价模型的实证检验——基于动态分组方法

本文利用1994年9月至2012年8月上海证券交易所678只股票月度历史数据,运用动态分组方法验证资本资产定价模型理论,结果表明:在研究样本取样时间段,传统资本资产定价模型中的平均超额收益率与贝塔系数之间的线性关系成立,但是模型的截距显著大于零,而斜率显著为负;将其平均分为四个亚时期,只有第一亚时期的拟合程度较好,且前三个亚时期模型的斜率均大于零,而第四亚时期的斜率变为负数,表明中国资本市场在2009年6月以后,经历了市场收益率为负数的状态,且这一时期的影响程度最终导致整个研究样本的斜率为负,这与席卷全球的金融危机抵达并影响中国股市的时间和程度吻合.     

资本资产定价模型对中国证券市场创业板的实证分析

中国创业板市场已运行两年,作为我国多层次资本市场体系的重要组成部分,其目的是为高成长性的中小企业提供融资渠道,同时,也使得证券市场资本市场配置多元化,以保障创业板稳健发展和分散风险的目的。通过计量经济回归分析,建立创业板资本资产定价模型(CAMP),估算其贝塔系数(β),以此考察创业板与主板市场的关系,分析中国创业板市场的投资价值及存在的问题,并提出完善创业板市场的对策。     

资本资产定价模型应用研究——对伊泰股份贝塔系数的测算

资本资产定价模型(CAPM)代表了金融领域最重要的进展和突破,是现代金融学最重要的理论基石之一.贝塔系数(也记为B)是资本资产定价模型最突出的发现,是证券或证券组合与市场相互关联的一个重要概念和参数,是衡量证券系统性风险的重要指标.它已经被广泛应用于投资理论和投资实践并发挥着重要的作用.本文以伊泰股份为研究对象,运用计量学的最小二乘回归计算出伊泰的贝塔系数.     

企业家的最优投资消费与定价

笔者考虑一个面临随机需求风险的企业家,如何通过消费平滑、风险管理及有成本地动态调整资本资产规模,实现消费效用最大化的公司金融问题.笔者运用动态随机控制方法,得到了非完备市场与非风险中性下企业资本的平均价值与边际价值的半闭式解及相应的最优经营策略;基于经典的资本资产定价(CAPM)理论,得到了企业家的期望收益率、企业的贝塔系数和风险溢价.数值结果表明,在非完备市场下企业家的风险态度对企业资本价值、贝塔系数、风险溢价、企业家的期望收益率及相应的最优经营策略等都具有显著影响.     

我国沪市上市公司影响系统性风险因素实证分析

采用2004年的沪市交易所的258个上市公司为样本，根据市场模型估计出这些上市公司的系统性风险系数（贝塔系数β），并通过因子分析模型和计量经济模型探索影响贝塔系数的因素。发现市场表现对我国证券市场的系统性风险影响较大，而各上市公司的财务情况，对系统性风险的影响却是徽乎其徽。     

资本资产定价理论与市场经济

资本资产定价模型(CAPM)是威廉·夏普于1964年在马克威茨的资产组合理论和托宾分离定理的基础上通过增加一些条件而建立起来的资本市场均衡定价模型。在CAPM的假设前提下,资本市场被带入一种所有的投资者持有相同风险资产市场组合的均衡状态,在这种状态下经济中所有的风险资产特别是企业资产都具有完全相同的所有权结构。从而将经济带入一种所有企业之间不存在利益冲突的"准公有制"状态,市场经济制度也将不复存在。如果我们认为这一结论是荒谬的,那问题一定出在CAPM的假设条件以及由此假设条件所推出的市场均衡,自然,建立在这种均衡状态下的资本资产定价模型的现实性也是成问题的。     

异质性财富偏好和资产定价

Bakshi和Chen(1996)在代表性投资者经济中提出了基于财富偏好的资产定价模型。本文研究了在异质性投资者经济中财富偏好对资产定价的影响。如果风险资产的价格服从几何布朗运动,那么资产市场具有两基金分离现象。本文首先证明了基于风险基金的资产定价模型,然后使用该模型证明了如果定价的基准是单个的投资者的最优消费和财富时,那么基于财富偏好的资产定价模型成立。但是,当定价的基准是总消费和总财富时,基于财富偏好的资产定价模型不能成立。也就是,不能在异质投资者经济中将Breeden(1979)的经典CCAPM模型推广到包含财富偏好的资产定价模型。     

异质性财富偏好和资产定价

Bakshi和Chen（1996）在代表性投资者经济中提出了基于财富偏好的资产定价模型。本文研究了在异质性投资者经济中财富偏好对资产定价的影响。如果风险资产的价格服从几何布朗运动，那么资产市场具有两基金分离现象。本文首先证明了基于风险基金的资产定价模型，然后使用该模型证明了如果定价的基准是单个的投资者的最优消费和财富时，那么基于财富偏好的资产定价模型成立。但是，当定价的基准是总消费和总财富时，基于财富偏好的资产定价模型不能成立。也就是，不能在异质投资者经济中将Breeden（1979）的经典CCAPM模型推广到包含财富偏好的资产定价模型。     

THE DISTRIBUTION OF BETAS IN PRESENCE OF NONTRADED ASSETS

This study considers a capital assets pricing model (CAPM) in an incomplete financial market wherein not all risky assets are traded and the risk from non‐traded assets is not orthogonal to that of the existing or traded assets. The model shows the extent of the divergence of the CAPM betas (true betas) from the traditional CAPM betas (perceived betas) in market equilibrium conditions in an incomplete market. Specifically, it implies that the more incomplete a financial market is, the wider is the discrepancy between the true and perceived betas, and the distribution of the perceived betas tends to centre more around 1 in an incomplete market than that of true betas. Empirical evidence in various settings support these results.     

Forecasting US recessions with various risk factors and dynamic probit models

This paper extends probit recession forecasting models by incorporating various recession risk factors and using the advanced dynamic probit modeling approaches. The proposed risk factors include financial market expectations of a gloomy economic outlook, credit or liquidity risks in the general economy, the risks of negative wealth effects resulting from the bursting of asset price bubbles, and signs of deteriorating macroeconomic fundamentals. The model specifications include three different dynamic probit models and the standard static model. The out-of-sample analysis suggests that the four probit models with the proposed risk factors can generate more accurate forecasts for the duration of recessions than the conventional static models with only yield spread and equity price index as the predictors. Among the four probit models, the dynamic and dynamic autoregressive probit models outperform the static and autoregressive models in terms of predicting the recession duration. With respect to forecasting the business cycle turning points, the static probit model is as good as the dynamic probit models by being able to flag an early warning signal of a recession.     

Nonparametric methods for estimating and testing for constant betas in asset pricing models

In this article, we study the performance of a smoothing spline method in estimating and testing for constant betas in two well-known asset pricing models, the usual market model and the three-factor model. The spline estimator is computed taking into account the conditional heteroscedasticity of the errors. Using the right model and estimation procedure for the variance term plays a crucial role in gaining efficiency in beta estimators. A simulation study shows the good performance of our method; in all the scenarios simulated, it outperforms the benchmark rolling estimator. The method enables users to obtain confidence intervals and to test for the significance and constancy of betas. Finally, the method is applied to US data, comprising 25 portfolios formed based on size and the ratio of book equity to market equity. The results show that the time-variability of the betas plays an important role, mainly when sensitivity to the HML factor is considered.     

Expected risk and excess returns predictability in emerging bond markets

This study examines the predictability of expected excess returns from eight emerging bond markets within an international asset pricing framework. Two sets of instruments are used, which include both world and local factors, to forecast emerging bond returns. Besides investigating the influence of the macroeconomic factors in specific countries on bond returns in those countries, this study also divides local factors into macroeconomic and financial factors. Unlike previous studies, we apply macroeconomic instruments that contain more information on excess returns as a proxy for local risk factors via principal component analysis methodology. The information variable approach enables the prediction of excess bond returns based on world and local factors and facilitating understanding of the degree of integration between emerging bond markets and developed bond markets. The results indicate that the bond market in emerging world is partially integrated to that in the developed world and the predictability of local factors that include both financial and macroeconomic information variables can forecast around 25–66% of the returns of emerging bonds. Incorporating the macroeconomic variables increases the explanatory power of the model. Both world and country-specific local instruments can forecast excess bond returns, but local instruments appear to be better predictors of such returns, particularly the local credit spread to US. Additionally, this study finds that investor risk aversion is significant among most of sample countries.     

Time-varying beta: a boundedly rational equilibrium approach

The conditional CAPM with time-varying betas has been widely used to explain the cross-section of asset returns. However, most of the literature on time-varying beta is motivated by econometric estimation using various latent risk factors rather than explicit modelling of the stochastic behaviour of betas through agents’ behaviour, such as momentum trading. Misspecification of beta risk and the lack of any theoretical guidance on how to specify risk factors based on the representative agent economy appear empirically challenging. In this paper, we set up a dynamic equilibrium model of a financial market with boundedly rational and heterogeneous agents within the mean-variance framework of repeated one-period optimisation and develop an explicit dynamic behaviour CAPM relation between the expected equilibrium returns and time-varying betas. By incorporating the two most commonly used types of investors, fundamentalists and chartists, into the model, we show that there is a systematic change in the market portfolio, risk-return relationships, and time varying betas when investors change their behaviour, such as the chartists acting as momentum traders. In particular, we demonstrate the stochastic nature of time-varying betas. We also show that the commonly used rolling window estimates of time-varying betas may not be consistent with the ex-ante betas implied by the equilibrium model. The results provide a number of insights into an understanding of time-varying beta.     

Beauty contest,bounded rationality,and sentiment pricing dynamics

We present a dynamic asset pricing model that incorporates investor sentiment, bounded rationality and higher-order expectations to study how these factors affect asset pricing equilibrium. In the model, we utilize a two-period trading market and investors make decisions based on the heterogeneous expectations principle and the “sparsity-based bounded rational” sentiment. We find that bounded rationality results in mispricing and reduces it in next period. Investor sentiment produces more significant effects than private signals, optimistic investor sentiment increases hedging demand, thus causing prices to soar. Higher-order investors are more rational and attentive to the strategies of other participants rather than private signals. This model also derives the dampening effect of higher-order expectations to price volatility and the heterogeneity expectation depicts inconsistent investor behavior in financial markets. In the model, investors' expectations about future price is distorted by their sentiment and bounded rationality, so they obtain a biased mean from the signal extraction.     

Option implied beta and option return

We study the information content of option-implied betas for future equity option returns, using data on the S&P 500 index options and all of the component stock options. We find a significantly strong relation between option-implied betas and option returns cross-sectional. The paper presents evidence that call (put) option returns increase (decrease) with the option-implied betas of the underlying stock. A trading strategy of buying high (low) implied beta call (put) option portfolio and selling low (high) implied beta call (put) option portfolio generates a statistically and economically significant return. Our results are robustly persistent even after controlling for various cross-sectional effects and are not explained by the risk factors in asset pricing.     

Structural Changes and the Scope of Inflation Targeting in Korea *

A small, open macroeconomic model that accounts for new financial accelerator effects (the effects of fluctuations in asset prices on bank credit and economic activity) is developed to evaluate various policy rules for inflation targeting. Given the conditions of asset markets and the fragility of the financial sector, monetary policy responses can potentially amplify the financial accelerator effect. Simulations are used to compare various forms of inflation targeting using a model that emphasizes long-term inflation expectations, output changes, and the asset price channels. The simulations suggest that a successful outcome can be obtained by adhering to simple forward-looking rules, rather than backward-looking policy rules. Furthermore, inflation targeting can contribute to price as well as output stability by helping to keep the financial accelerator from being activated. Inflation targeting in emerging economies can provide an environment conducive to long-term capital market development. [E51,F3,F4]     

Asset arbitrage and the price of oil

It is commonly understood that macroeconomic shocks influence commodity prices and that one channel for this is the link between interest rates, expected future asset returns and stock-holding. In this paper the link is extended to the petroleum market with the recognition that recorded stocks of oil comprise a small share of annual demand and that the parallel with storable commodities is the decision to produce the oil in the first place, as opposed to holding it in the ground as reserve. Oil reserves are then a key asset in producing countries, which is arbitraged against financial assets. Thus, when the yield on financial assets falls, retaining oil reserves becomes more attractive to producing countries, which then have less incentive to accommodate demand rises, and so the oil price rises. This perspective on oil pricing is modeled in a dynamic multi-region general equilibrium framework in which regional households manage portfolios of assets that include oil reserves. When the model is calibrated to match observed data over two decades, simulation results indicate that asset arbitrage made a large contribution to the high pre-GFC oil price.     

The nonlinear multidimensional relationship between stock returns and the macroeconomy

We use nonparametric dimension-reduction methods to extract from a set of 15 macroeconomic variables the risk factors that are priced in the stock market. The dominant factor moves with the business cycle but, because it is a nonlinear function of observed macroeconomic variables, it captures a rich set of interactions. Low-credit risk and low-inflationary expectations have a greater positive effect on stock returns when leading macroeconomic indicators are high relative to current economic activity, i.e. early in the business cycle as the economy emerges from recession. High-stock returns also arise in periods when the economy is booming relative to its leading indicators, but such periods tend to portend crashes.