On the Cross-sectional Relation between Expected Returns and Betas

There is an exact linear relation between expected returns and true “betas” when the market portfolio is on the ex ante mean-variance efficient frontier, but empirical research has found little relation between sample mean returns and estimated betas. A possible explanation is that market portfolio proxies are mean-variance inefficient. We categorize proxies that produce particular relations between expected returns and true betas. For the special case of a zero relation, a market portfolio proxy must lie inside the efficient frontier, but it may be close to the frontier.     

Tracking the Evolution of Idiosyncratic Risk and Cross-Sectional Expected Returns for US REITs

This paper adopts the methodology in Bali and Cakici (Journal of Financial & Quantitative Analysis, 43, 29–58, 2008) in tracking the evolution of the relation between equity REITs’ idiosyncratic risk and their cross-sectional expected returns between 1981 and 2010. In addition to the full sample period, we study this relation for (i) January 1981–December 1992, (ii) January 1993–September 2001, (iii) November 2001–August 2008 and (iv) November 2001–December 2010 and produce empirical results for (i) all sample REITs, (ii) REITs with a price greater than $10 or (iii) REITs with a price greater than $5. Each period represents different dynamics (including the Global Financial Crisis) in the life of the REIT industry and leads to a different hypothesis. Further, we present comparative results based on the Fama-French 3- and 4-factor models. Overall, we document a negative relation between idiosyncratic risk and cross-sectional expected returns and demonstrate that this negative relation changes over time. These findings amplify the “idiosyncratic volatility puzzle,” as reported in the recent finance literature. Interestingly, REITs with a price of $5-to-$10 do well in 2009 and 2010. Further, the momentum factor appears to be influential since the first-ever listing of a REIT in the S&P500 Index in early October 2001.     

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.     

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.     

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。     

Expected Returns,Time-varying Risk,and Risk Premia

A new empirical model for intertemporal capital asset pricing is presented that allows both time-varying risk premia and betas where the latter are identified from the dynamics of the conditional covariance of returns. The model is more successful in explaining the predictable variations in excess returns when the returns on the stock market and corporate bonds are included as risk factors than when the stock market is the single factor. Although changes in the covariance of returns induce variations in the betas, most of the predictable movements in returns are attributed to changes in the risk premia.     

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.     

Consumption, Aggregate Wealth, and Expected Stock Returns

This paper studies the role of fluctuations in the aggregate consumption–wealth ratio for predicting stock returns. Using U.S. quarterly stock market data, we find that these fluctuations in the consumption–wealth ratio are strong predictors of both real stock returns and excess returns over a Treasury bill rate. We also find that this variable is a better forecaster of future returns at short and intermediate horizons than is the dividend yield, the dividend payout ratio, and several other popular forecasting variables. Why should the consumption–wealth ratio forecast asset returns? We show that a wide class of optimal models of consumer behavior imply that the log consumption–aggregate wealth (human capital plus asset holdings) ratio summarizes expected returns on aggregate wealth, or the market portfolio. Although this ratio is not observable, we provide assumptions under which its important predictive components for future asset returns may be expressed in terms of observable variables, namely in terms of consumption, asset holdings and labor income. The framework implies that these variables are cointegrated, and that deviations from this shared trend summarize agents' expectations of future returns on the market portfolio.     

Expected Inflation, Interest Rates, and Stock Returns

This paper documents a long-lived asymmetrical relationship between interest rate changes and subsequent stock returns. Drops in interest rates are followed by twelve months of excess stock returns, while increases in interest rates have little effect. The results are robust to the choices of short-term interest rate and stock index. These findings cannot be explained by Geske and Roll's [10] reversed causality argument; nor do they appear to result from periods of unusual interest rates or stock returns. Since interest rate changes are generally used as proxies for changes in expected inflation, the results provide new insights into previous research on inflation and stock returns, and there are important implications for the literature on time-varying risk premia.     

Momentum, Business Cycle, and Time-varying Expected Returns

A growing number of researchers argue that time-series patterns in returns are due to investor irrationality and thus can be translated into abnormal profits. Continuation of short-term returns or momentum is one such pattern that has defied any rational explanation and is at odds with market efficiency. This paper shows that profits to momentum strategies can be explained by a set of lagged macroeconomic variables and payoffs to momentum strategies disappear once stock returns are adjusted for their predictability based on these macroeconomic variables. Our results provide a possible role for time-varying expected returns as an explanation for momentum payoffs.     

Dividend Dynamics,Learning, and Expected Stock Index Returns

We present a latent variable model of dividends that predicts, out‐of‐sample, 39.5% to 41.3% of the variation in annual dividend growth rates between 1975 and 2016. Further, when learning about dividend dynamics is incorporated into a long‐run risks model, the model predicts, out‐of‐sample, 25.3% to 27.1% of the variation in annual stock index returns over the same time horizon, with learning contributing approximately half of the predictability in returns. These findings support the view that investors' aversion to long‐run risks and their learning about these risks are important in determining stock index prices and expected returns.     

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。     

Market Frictions, Price Delay, and the Cross-Section of Expected Returns

We parsimoniously characterize the severity of market frictionsaffecting a stock using the delay with which its price respondsto information. The most delayed firms command a large returnpremium not explained by size, liquidity, or microstructureeffects. Moreover, delay captures part of the size effect, idiosyncraticrisk is priced only among the most delayed firms, and earningsdrift is monotonically increasing in delay. Frictions associatedwith investor recognition appear most responsible for the delayeffect. The very small segment of delayed firms, comprisingonly 0.02% of the market, generates substantial variation inaverage returns, highlighting the importance of frictions.     

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.