On the Cross-Sectional Relation between Expected Returns, Betas, and Size

In this paper, I set up scenarios where the mean-variance capital asset pricing model is true and where it is false. Then I investigate whether the coefficients from regressions of population expected excess returns on population betas, and expected excess returns on betas and size, allow us to distinguish between the scenarios. I show that the coefficients from either ordinary least squares or generalized least squares regressions do not allow us to tell whether the model is true or false.     

Time-Varying Betas of German Stock Returns

The market model assumes stock returns to be a linear function of the market return. However, there is considerable evidence that the beta stability assumption commonly used when estimating the market model is invalid. In this paper we account for beta instability in German stock returns by allowing the coefficients to vary over time in estimation. For time-varying beta estimation we rely on the Flexible Least Squares approach, the Random Walk Model and Moving Window Least Squares. Due to our results time-varying estimation fits the data considerably better than time-invariant estimation and, hence, increases the efficiency of beta based risk measurement.Acknowledgements: The authors thank Stefan Mittnik, Christian Pigorsch, an anonymous referee and the editor for constructive comments.     

Expected Idiosyncratic Volatility Measures and Expected Returns

We find that idiosyncratic volatility forecasts using information available to traders at the time of the forecast are not related to expected returns. The positive relation documented in a number of other papers only exists when forward‐looking information is incorporated into the volatility estimate. That positive relation is driven by the realized idiosyncratic volatility component that cannot be forecasted by investors. Our findings are robust to several different empirical tests, volatility forecasting models and time periods.     

Earnings and Expected Returns

The aggregate dividend payout ratio forecasts excess returns on both stocks and corporate bonds in postwar U.S. data. High dividends forecast high returns. High earnings forecast low returns. The correlation of earnings with business conditions gives them predictive power for returns; they contain information about future returns that is not captured by other variables. Dividends and earnings contribute substantial explanatory power at short horizons. For forecasting long-horizon returns, however, only (scaled) stock prices matter. Forecasts of low long-horizon stock returns in the mid-1990s are caused not by earnings or dividends, but by high stock prices.     

Expected Option Returns

This paper examines expected option returns in the context of mainstream asset-pricing theory. Under mild assumptions, expected call returns exceed those of the underlying security and increase with the strike price. Likewise, expected put returns are below the risk-free rate and increase with the strike price. S&P index option returns consistently exhibit these characteristics. Under stronger assumptions, expected option returns vary linearly with option betas. However, zero-beta, at-the-money straddle positions produce average losses of approximately three percent per week. This suggests that some additional factor, such as systematic stochastic volatility, is priced in option returns.     

充分发挥信息对中国资本市场投资预期收益的作用

我国资本市场中是普遍存在着预期因素及其影响的。投资者所进行的资本市场投资预期是与信息密切相关的。信息的有无、信息的多少和对信息的利用程度直接影响投资者预期收益的多少,从而影响到他们资本市场投资的多少。提供和保证充分的信息是发挥资本市场投资预期积极作用的前提。     

Consumption Fluctuations and Expected Returns

This paper introduces a novel consumption-based variable, cyclical consumption, and examines its predictive properties for stock returns. Future expected stock returns are high (low) when aggregate consumption falls (rises) relative to its trend and marginal utility from current consumption is high (low). We show that the empirical evidence ties consumption decisions of agents to time variation in returns in a manner consistent with asset pricing models based on external habit formation. The predictive power of cyclical consumption is not confined to bad times and subsumes the predictability of many popular forecasting variables.     

线上销售与未来股票收益

本文通过分析相关上市公司在电商平台的线上销售数据,发现线上销售增长可以预测未来股票收益。根据线上销售增长率构建投资组合可以获得月均1.27%的超额收益,经三因子、五因子模型调整后收益率分别为1.40%和1.35%,并且该超额收益在较长时间内不会逆转。横截面回归结果显示,线上销售增长与未来股票收益显著正相关,并在控制其他市场异象因子后仍然显著。此外,本文还发现线上销售数据的预测能力主要集中在投资者关注有限、线上销售占比高以及套利成本高的公司,其投资价值来源于对公司未来基本面信息的预测能力。进一步研究表明,同时利用线上销售指标和营业收入指标进行投资可以获得更高的超额收益。在考虑业绩预告和业绩快报对线上销售指标预测能力的潜在影响后,结果依然稳健。     

Share Issuance and Cross-sectional Returns

Post‐1970, share issuance exhibits a strong cross‐sectional ability to predict stock returns. This predictive ability is more statistically significant than the individual predictive ability of size, book‐to‐market, or momentum. Our finding is related to research that finds that long‐run returns are associated with share repurchase announcements, seasoned equity offerings, and stock mergers, although our results remain strong even after exclusion of the data used in these studies. We estimate the issuance relation pre‐1970 and find no statistically significant predictive ability for most holding periods.     

Expected Returns and Habit Persistence

Using a consumption-based asset pricing model with infinite-horizonnonlinear habit formation, Campbell and Cochrane (1999) showthat low consumption in surplus of habit should forecast highexpected returns. This article argues that the finite-horizonlinear habit model also implies an inverse relation betweenexpected returns and surplus consumption. This article alsopresents empirical evidence, which indicates that expected returnson stocks and bonds vary with surplus consumption implied bythe habit models. The volatility of returns and the reward tovolatility are also related to surplus consumption. However,less than 30% of the predictable variation of expected returns,using standard lagged information variables, is attributed tosurplus consumption.     

Information Uncertainty and Expected Returns

This study examines the role of information uncertainty (IU) in predicting cross-sectional stock returns. We define IU in terms of “value ambiguity,” or the precision with which firm value can be estimated by knowledgeable investors at reasonable cost. Using several different proxies for IU, we show that (1) on average, high-IU firms earn lower future returns (the “mean” effect), and (2) price and earnings momentum effects are much stronger among high-IU firms (the “interaction” effect). These findings are consistent with analytical models in which high IU exacerbates investor overconfidence and limits rational arbitrage.This revised version was published online in August 2005 with a corrected cover date.     

Stock Returns,Expected Returns,and Real Activity

Measuring the total return variation explained by shocks to expected cash flows, time-varying expected returns, and shocks to expected returns is one way to judge the rationality of stock prices. Variables that proxy for expected returns and expected-return shocks capture 30% of the variance of annual NYSE value-weighted returns. Growth rates of production, used to proxy for shocks to expected cash flows, explain 43% of the return variance. Whether the combined explanatory power of the variables—about 58% of the variance of annual returns—is good or bad news about market efficiency is left for the reader to judge.     

上海股票市场时变的风险收益关系研究

在GARCH-M模型框架下,本文通过不同的模型研究了作为新兴市场的上海股票市场股票日超额收益率条件均值和条件波动性之间的关系。本文研究表明,在股票超额收益率条件均值和条件方差之间都存在一种正的关系。上海股票市场日超额收益率波动表现出非对象现象,且波动模式表现为持续时间长,幅度相对比较缓和的特征。研究结果还表明,无风险利率可以显著解释日超额收益率的条件方差变动。     

Order Flow and Expected Option Returns

I show that the inventory risk faced by market‐makers has a first‐order effect on option prices. I introduce a simple approach that decomposes the price impact of trades into inventory risk and asymmetric information components. While both components are large for option trades, the inventory risk component is larger. Using the full panel of daily option returns, I find that option order imbalances attributable to inventory risk have five times larger impact on option prices than previously thought. Finally, I find that past order imbalances have greater predictive power than any other commonly used predictor of option returns.     

对我国股票收益率与通货膨胀率关系的解释：1992-2007

股票收益率和通货膨胀率之间既可以正相关,也可以负相关。如果通货膨胀率的上升动力来自于供给冲击,那么两者负相关;如果来自于需求冲击则正相关。同一时期的正负相关关系取决于供给和需求冲击动力的相对重要性。对我国1992年5月至2007年8月实践的检验表明,整个样本期间内股票收益率和通货膨胀率相关性不明显。在1992年5月至1999年12月期间,供给冲击大于需求冲击的影响,导致股票收益率和通货膨胀率负相关,但2000年1月至2007年8月,同样是供给冲击大于需求冲击的影响,却导致两者正相关。其中的原因在于,2000年后国民经济中供需结构失衡,名义上的供给冲击转变成实际上的需求冲击,从而导致股票收益率和通货膨胀率正相关。政策当局在吸收过多流动性的同时,应加快经济结构调整,从根本上解决供需失衡问题。     

Portfolio Inefficiency and the Cross-section of Expected Returns

The Capital Asset Pricing Model implies that (i) the market portfolio is efficient and (ii) expected returns are linearly related to betas. Many do not view these implications as separate, since either implies the other, but we demonstrate that either can hold nearly perfectly while the other fails grossly. If the index portfolio is inefficient, then the coefficients and $R^2$ from an ordinary least squares regression of expected returns on betas can equal essentially any values and bear no relation to the index portfolio's mean-variance location. That location does determine the outcome of a mean-beta regression fitted by generalized least squares.     

Business Cycles and the Relation between Security Returns and Earnings

This paper examines business cycle variation in the earnings-returns relation. Earnings are more persistent when growth rates are high (i.e., in an expansion) than when growth rates are low (i.e., in a recession). Earnings are more persistent when production is high (i.e., in a credit crunch period) than when production is low (i.e., in a reliquification period). Relatedly, earnings response coefficients are larger in expansions (credit crunch periods) than in recessions (reliquification periods). Thus, earnings persistence and earnings response coefficients are positively associated with the rate of growth in economic activity and the level of economic activity.     

The Cross-Section of Volatility and Expected Returns

We examine the pricing of aggregate volatility risk in the cross‐section of stock returns. Consistent with theory, we find that stocks with high sensitivities to innovations in aggregate volatility have low average returns. Stocks with high idiosyncratic volatility relative to the Fama and French (1993, Journal of Financial Economics 25, 2349) model have abysmally low average returns. This phenomenon cannot be explained by exposure to aggregate volatility risk. Size, book‐to‐market, momentum, and liquidity effects cannot account for either the low average returns earned by stocks with high exposure to systematic volatility risk or for the low average returns of stocks with high idiosyncratic volatility.     

Tests of Asset Pricing with Time-Varying Expected Risk Premiums and Market Betas

Tests of asset-pricing models are developed that allow expected risk premiums and market betas to vary over time. These tests exploit the relation between expected excess returns and current market values. Using weekly data for 1963 through 1982 on ten common stock portfolios formed according to equity capitalization, a single-risk-premium model is not rejected if the expected premium is time varying and is not constrained to correspond to a market factor. Conditional mean-variance efficiency of a value-weighted stock index is rejected, and the rejection is insensitive to how much variability of expected risk premiums is assumed.     

Ex Ante Skewness and Expected Stock Returns

We use option prices to estimate ex ante higher moments of the underlying individual securities’ risk‐neutral returns distribution. We find that individual securities’ risk‐neutral volatility, skewness, and kurtosis are strongly related to future returns. Specifically, we find a negative (positive) relation between ex ante volatility (kurtosis) and subsequent returns in the cross‐section, and more ex ante negatively (positively) skewed returns yield subsequent higher (lower) returns. We analyze the extent to which these returns relations represent compensation for risk and find evidence that, even after controlling for differences in co‐moments, individual securities’ skewness matters.