Time-Varying Expected Returns in International Bond Markets

This article examines the predictable variation in long-maturity government bond returns in six countries. A small set of global instruments can forecast 4 to 12 percent of monthly variation in excess bond returns. The predictable variation is statistically and economically significant. Moreover, expected excess bond returns are highly correlated across countries. A model with one global risk factor and constant conditional betas can explain international bond return predictability if the risk factor is proxied by the world excess bond return, but not if it is proxied by the world excess stock return.     

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.     

Conditioning Information and European Bond Fund Performance

In this paper we evaluate the performance of European bond funds using unconditional and conditional models. As conditioning information we use variables that we find to be useful in predicting bond returns in the European market. The results show that, in general, bond funds are not able to outperform passive strategies. These findings are robust to whatever model (unconditional versus conditional and single versus multi‐index) we use. The multi‐index model seems to add some explanatory power in relation to the single‐index model. Furthermore, when we incorporate the predetermined information variables, we can observe a slight tendency towards better performance. This evidence is consistent with previous studies on stock funds and comes in support of the argument that conditional models might allow for a better assessment of performance. However, our results suggest that the impact of additional risk factors seems to be greater than the impact of incorporating predetermined information variables.     

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.     

The Errors in the Variables Problem in the Cross-Section of Expected Stock Returns

Recent research has documented the failure of market beta to capture the cross-section of expected returns within the context of a two-pass estimation methodology. However, the two-pass methodology suffers from the errors-in-variables (EIV) problem that could attenuate the apparent significance of market beta. This article provides a new correction for the EIV problem that is robust to conditional heteroscedasticity. After the correction, I find more support for the role of market beta and less support for the role of firm size in explaining the cross-section of expected returns. While the EIV correction leads to a diminished role of firm size, the size variable remains a significant force in explaining the cross-section of expected returns.     

Are the Latent Variables in Time-Varying Expected Returns Compensation for Consumption Risk?

Multibeta asset pricing models are examined using proxies for economic state variables in a framework which exploits time-varying expected returns to estimate conditional betas. Examples include multiple consumption-beta models and models where asset returns proxy for the state variables. When the state variables are not specified, the tests indicate two or three time-varying expected risk premiums in the sample of quarterly asset returns. Conditional betas relative to consumption generate less striking evidence against the model than betas relative to asset returns, but both the consumption and the market variables fail to proxy for the state variables.     

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.     

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 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.     

Relations Between Stock Returns and Fundamental Variables: Evidence from a Segmented Market

This study examines relations between stock returns and potential explanatory factors in Korea, an important and segmented emerging market. Our results show that Korean stock returns in general and returns on stocks listed in Section 1 in particular are significantly positively related to book-to-market, sales-price, and debt-equity ratios, but not significantly related to market value of equity. Returns on stocks listed in Section 2 are, however, negatively related to market value of equity and not significantly related to the other three variables. Among the variables investigated by us, book-to-market ratio has the greatest explanatory power for stock returns and it indicates superior returns for value stocks. Our findings strengthen the international evidence of the role of book-to-market ratio in explaining stock returns by demonstrating its significance even in the segmented Korean market.     

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.     

Closed‐End Fund Discounts and Expected Investment Performance

This article provides empirical support for the theory that closed‐end fund discounts reflect expected investment performance. Evidence is presented to explain how equity closed‐end fund initial public offerings (IPOs) can sell at a premium when existing funds sell at a discount and why the initial IPO premiums decay after the IPO. Relative premium decay data are presented. Tests on (1) the relation between relative premium changes and investment performance following IPOs, (2) relative premium mean‐reversion following management changes, and (3) net redemptions following closed‐end fund open‐endings for funds trading at pre‐open‐ending announcement discounts individually support and collectively strongly support the theory.     

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.     

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.     

Corporate Bond Returns and Volatility

Recent literature emphasizes the relation of stock volatility to corporate bond yields. We demonstrate that during 1996–2005 corporate bond excess return volatility is directly related to contemporaneous corporate bond excess returns. In fact, the decompositions of aggregate bond volatility have a higher contemporaneous correlation with bond yields in comparison to idiosyncratic stock risk. Additionally, bond volatility and idiosyncratic risk are significant predictors of corporate three‐month and six‐month ahead bond excess returns. We also find that corporate bond volatility contains both slow moving and time‐varying components.