The Predictability of Equity REIT Returns: Time Variation and Economic Significance

This article presents evidence on predictability of excess returns for equity REITs relative to the aggregate stock market, small-capitalization stocks, and T-bills using best-fit models from prior time periods. We find that excess equity REIT returns are far less predictable out-of-sample than in-sample. This inability to forecast out-of-sample is particularly true in the 1990s. Nevertheless, in the absence of transaction costs, active-trading strategies based on out-of-sample predictions modestly outperform REIT buy-and-hold strategies. However, when transaction costs are introduced, profits from these active-trading strategies largely disappear.     

The Predictability of Short-Horizon Stock Returns

This examines the predictability of short-horizon stock returnsin the UK. We show that the subsequent return reversal of previousextreme performers is unlikely to be caused by either lead-lageffects or inventory imbalances, the most likely explanationbeing market overreaction. A market or trading based explanationis reinforced by the finding that these return reversals areasymmetric, being less significant after bad news. Further,we find that the lower transacting stocks exhibit the strongerreturn reversals, in direct contrast to both the existing USevidence and the implication that liquidity effects can explainthe return reversals. JEL Classification: G10, G11, G12     

Economic Significance of Predictable Variations in Stock Index Returns

Knowledge of the one-month interest rate is useful in forecasting the sign as well as the variance of the excess return on stocks. The services of a portfolio manager who makes use of the forecasting model to shift funds between bills and stocks would be worth an annual management fee of 2% of the value of the assets managed. During 1954:4 to 1986:12, the variance of monthly returns on the managed portfolio was about 60% of the variance of the returns on the value weighted index, whereas the average return was two basis points higher.     

International Evidence on the Predictability of Stock Returns

This article examines the predictability of stock returns using international stock market data from eighteen countries. The study finds that the ability of dividend yields to predict stock returns increases as the return horizon lengthens from one month to forty-eight months. These results add to earlier ones, based on U.S. data only, showing that predictability grows with the return horizon. The study also explores why the observed pattern of predictability arises and provides evidence supporting the reasons suggested by Fama and French.     

On the Predictability of Stock Returns: An Asset-Allocation Perspective

Sample evidence about the predictability of monthly stock returns is considered from the perspective of a risk-averse Bayesian investor who must allocate funds between stocks and cash. The investor uses the sample evidence to update prior beliefs about the parameters in a regression of stock returns on a set of predictive variables. The regression relation can seem weak when described by usual statistical measures, but the current values of the predictive variables can exert a substantial influence on the investor's portfolio decision, even when the investor's prior beliefs are weighted against predictability.     

A Note on the Predictability of UK Stock Returns

This note presents evidence on the predictability of UK stock returns using a database of companies in the FTSE-Allshare Index newly constructed towards the beginning of 1998. The tests used are autocorrelations at various lags and variance ratios for several aggregations of base observations. The evidence is consistent with that published for US stock returns, namely that daily stock returns contain a strong element of predictability.     

On the Predictability of Japanese Stock Returns Using Dividend Yield

The aim of this paper is to provide a critical and comprehensive reexamination of empirical evidence on the ability of the dividend yield to predict Japanese stock returns. Our empirical results suggest that in general, the predictability is weak. However, (1) if the bubble economy period (1986–1998), during which dividend yields were persistently lower than the historical average, is excluded from the sample, and (2) if positive autocorrelation in monthly aggregate returns is taken into account, there is some evidence that the log dividend yield is indeed useful in forecasting future stock returns. More specifically, the log dividend yield contributes to predicting monthly stock returns in the sample after 1990 and when lagged stock returns are included simultaneously.     

Distinguishing Between Rationales for Short‐Horizon Predictability of Stock Returns

In this paper, we shed light on short‐horizon return reversals. We show theoretically that a risk‐based rationale for reversals implies a relation between returns and past order flow, whereas a reversion in beliefs of biased agents does not do so. The empirical results indicate that returns are more strongly related to own‐return lags than to lagged order imbalances. Thus, the evidence suggests that monthly reversals are not completely captured by inventory effects and may be driven, in part, by belief reversion. We do find that returns are cross‐sectionally related to lagged imbalance innovations at horizons longer than a month.     

Asymmetries in Stock Returns: Statistical Tests and Economic Evaluation

We provide a model-free test for asymmetric correlations inwhich stocks move more often with the market when the marketgoes down than when it goes up, and also provide such testsfor asymmetric betas and covariances. When stocks are sortedby size, book-to-market, and momentum, we find strong evidenceof asymmetries for both size and momentum portfolios, but noevidence for book-to-market portfolios. Moreover, we evaluatethe economic significance of incorporating asymmetries intoinvestment decisions, and find that they can be of substantialeconomic importance for an investor with a disappointment aversion(DA) preference as described by Ang, Bekaert, and Liu (2005).     

南橘北枳:A股市场的经济关联与股票回报

本文系统检验并比较了中国A股市场中行业动量、区域动量、供应链动量以及科技关联动量等经济关联动量的显著性及预测周期。本文发现,中国股票市场中经济关联因子呈现出与美国股票市场不同的规律,在月度层面行业动量显著,而科技关联因子只在周度上具有显著的预测能力。进一步分析科技关联动量发现,中国股票市场中科技关联因子能预测目标公司未来1-3周的股票收益和未来基本面的变化,据此构建的多空策略能够产生周度0.16%的超额收益(年化8.67%);机制检验发现,科技关联因子预测期短的原因是由于中国股票市场中存在较多具有博彩倾向的散户投资者;有限注意和市场摩擦两个机制检验证明科技关联动量源自错误定价。进一步检验发现,科技关联动量在国有企业和创新政策颁布后更加显著。本文补充了现有A股市场的动量研究,有助于理解中国股票市场规律、提升资本市场有效性。     

The Predictability of Short-HorizonStock Returns

This examines the predictability of short-horizonstock returns in the UK. We show that the subsequentreturn reversal of previous extreme performers isunlikely to be caused by either lead-lag effects orinventory imbalances, the most likely explanationbeing market overreaction. A market or trading basedexplanation is reinforced by the finding that thesereturn reversals are asymmetric, being lesssignificant after bad news. Further, we find that thelower transacting stocks exhibit the stronger returnreversals, in direct contrast to both the existing USevidence and the implication that liquidity effectscan explain the return reversals.     

Stock Returns,Inflation, and Economic Activity: The Survey Evidence

The primary purpose of this paper is the use of survey expectations data to study the empirical relationships between stock returns, inflation, and economic activity. In the course of this analysis and as a secondary purpose, the paper discusses general considerations involving the use of expectations proxies and makes recommendations for econometric techniques. The main empirical findings are: (1) Hypothesized relationships between expected economic activity and expected inflation do not in practice appear to be important in explaining the negative relationship between expected inflation and stock returns. (2) Nevertheless, the survey data do lend some support to the hypothesis of a quantity theory relationship between expected inflation and expected economic activity, holding constant monetary growth. (3) The cross-forecaster dispersion of economic activity forecasts, a proxy for real uncertainty, appears to be a significant determinant of stock returns. Inclusion of this variable eliminates the negative impact of expected inflation.     

Assessing the Economic Significance of Return Predictability: A Research Note

The predictability of stock returns is often assessed using classical statistical significance from predictive regressions. Statistical inference, however, can belie the economic importance with which investors regard various predictors. This paper examines the influence that predictors have on an investor's optimal portfolio allocations. The results show that return predictability is sufficient to induce horizon effects in optimal allocations. After incorporating estimation risk, however, little evidence of predictability remains. We also assess the relative importance of three predictor variables. While dividend yield is the most important predictor, optimal allocations are also sensitive to the term spread and the relative bill rate.     

The Risk and Predictability of International Equity Returns

We investigate predictability in national equity market returns,and its relation to global economic risks. We show how to consistentlyestimate the fraction of the predictable variation that is capturedby an asset pricing model for the expected returns. We use amodel in which conditional betas of the national equity marketsdepend on local information variables, while global risk premiadepend on global variables. We examine single- and multiple-betamodels, using monthly data for 1970 to 1989. The models capturemuch of the predictability for many countries. Most of thisis related to time variation in the global risk premia.     

Stock Returns and Open-Market Stock Repurchase Announcements

Recent studies document stock price underreactions and overreactions. This evidence is extended by studying open-market stock repurchase announcements. Repurchase announcements were chosen for the study because of the uncertainty regarding the appropriate interpretation of the repurchase announcement. Cross-section regression models are used to test the relation between the reaction to the repurchase announcement and returns in subsequent periods. The results indicate that the market overreacts to repurchase announcements that are deemed to be “good news” by the market. Neither reversal nor drift is observed following repurchase announcements considered to be “bad news” by the market. The results are robust and are not driven by a few influential observations, beta shifts, or bid-ask bounce.     

Production-Based Asset Pricing and the Link Between Stock Returns and Economic Fluctuations

This paper describes a production-based asset pricing model. It is analogous to the standard consumption-based model, but it uses producers and production functions in the place of consumers and utility functions. The model ties stock returns to investment returns (marginal rates of transformation) which are inferred from investment data via a production function. The production-based model is used to examine forecasts of stock returns by business-cycle related variables and the association of stock returns with subsequent economic activity.     

Stock Market Returns and Economic Fundamentals in an Emerging Market: The Case of Korea

This paper investigates the feedback relationship between stock market returnsand economic fundamentals in an emerging market. Starting from an intertemporalconsumption-based CAPM (CCAPM), we obtain a restricted VAR model for stockreturns and macroeconomic variables. We then apply this model to Korea and findstatistically significant departures from the restrictions implied by CCAPM.Consequently, an unrestricted VAR model is used to analyze the variations of expectedand unexpected returns in the Korean stock market. It is shown that the expectedmarket returns vary with a set of macroeconomic variables, and that thepredictable component is substantial. Reflecting richer dynamics in the data,relative to the usual single equation modeling in the literature, the estimatedVAR model shows considerable predictive ability for both real economic activityand real returns. Using the model for a variance decomposition of unexpectedreturns, we find that, although we cannot directly observe the market's revisionof expected future dividend growth, we can estimate a large part of therevision with the news in the expected industry output growth from our VAR model.Finally, we also find that economic fundamentals can explain only a smallportion of the variation in unexpected returns in the Korean stock market.     

On Stock Market Returns and Returns on Investment

This article presents general conditions under which it is possible to obtain asset pricing relations from the intertemporal optimal investment decision of the firm. Under the assumption of linear homogeneous production and adjustment cost functions (the Hayashi (1982) conditions), it is possible to establish, state by state, the equality between the return on investment and the market return of the financial claims issued by the firm. This result proves to be, in essence, robust to the consideration of very general constraints on investment and the inclusion of taxes.     

Excess Cash and Stock Returns

I document a positive relationship between corporate excess cash holdings and future stock returns. The difference in returns of portfolios of high and low excess cash firms amounts to 5% annually or 6% after standard three-factor risk adjustment. Firms with more excess cash have higher market betas and earn lower returns during market downturns. High excess cash companies invest considerably more in the future than do their low cash peers, but do not experience stronger future profitability. On the whole, this evidence is consistent with the notion that excess cash holdings proxy for risky growth options.     

Asymmetric Information and the Predictability of Real Estate Returns

This article examines the relation between systematic price changes and the heterogeneity of investors information sets in real estate asset markets. The empirical implications rely on a theoretical economy in which information asymmetry alters the dynamic relation between returns and trading volume. We employ a filter-rule methodology to determine predictability in returns and augment the return-based conditioning set with trading volume. The additional conditioning information is necessary since the model is underspecified when predictability is based on returns alone. Our results provide new insight into the coexistence of informational and noninformational exchange in the speculative markets for real estate assets. Specifically, we find that the predictability of real estate returns is generally more indicative of portfolio rebalancing effects than an adverse-selection problem. These results are unique in addressing the time-variation in information asymmetry.