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.     

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.     

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.     

Financially Constrained Stock Returns

We study the effect of financial constraints on risk and expected returns by extending the investment-based asset pricing framework to incorporate retained earnings, debt, costly equity, and collateral constraints on debt capacity. Quantitative results show that more financially constrained firms are riskier and earn higher expected stock returns than less financially constrained firms. Intuitively, by preventing firms from financing all desired investments, collateral constraints restrict the flexibility of firms in smoothing dividend streams in the face of aggregate shocks. The inflexibility mechanism also gives rise to a convex relation between market leverage and expected stock returns.     

Heteroskedasticity in Stock Returns

We use predictions of aggregate stock return variances from daily data to estimate time-varying monthly variances for size-ranked portfolios. We propose and estimate a single factor model of heteroskedasticity for portfolio returns. This model implies time-varying betas. Implications of heteroskedasticity and time-varying betas for tests of the capital asset pricing model (CAPM) are then documented. Accounting for heteroskedasticity increases the evidence that risk-adjusted returns are related to firm size. We also estimate a constant correlation model. Portfolio volatilities predicted by this model are similar to those predicted by more complex multivariate generalized-autoregressive-conditional-heteroskedasticity (GARCH) procedures.     

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.     

Forecasting the Correlation Structure of German Stock Returns: A Test of Firm-Specific Factor Models

This paper evaluates the performance of various factor models with firm-specific variables in forecasting correlation matrices at the German stock market. We investigate forecasts of correlations for a comprehensive sample and a sample of blue chips and analyse the impact of stock market crashes on the forecasting accuracy. Our empirical results show that the multi-factor models do not generally produce better forecasts than 'naive' models. Specifically, the traditional industry mean model significantly outperforms all other techniques in most of the time periods.     

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.     

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.     

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.     

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.     

Testing the CAPM with Time-Varying Risks and Returns

This paper draws on Engle's autoregressive conditionally heteroskedastic modeling strategy to formulate a conditional CAPM with time-varying risk and expected returns. The model is estimated by generalized method of moments. A CAPM that allows mean excess returns to shift in January survives generalized method of moments specification tests for a number of omitted variables. However, a residual dividend yield component is found to remain in the excess returns of smaller firms. We find significant monthly and quarterly components in the risk premia and beta estimates.     

How to Discount Cashflows with Time-Varying Expected Returns

While many studies document that the market risk premium is predictable and that betas are not constant, the dividend discount model ignores time‐varying risk premiums and betas. We develop a model to consistently value cashflows with changing risk‐free rates, predictable risk premiums, and conditional betas in the context of a conditional CAPM. Practical valuation is accomplished with an analytic term structure of discount rates, with different discount rates applied to expected cashflows at different horizons. Using constant discount rates can produce large misvaluations, which, in portfolio data, are mostly driven at short horizons by market risk premiums and at long horizons by time variation in risk‐free rates and factor loadings.     

Information Uncertainty and Stock Returns

There is substantial evidence of short‐term stock price continuation, which the prior literature often attributes to investor behavioral biases such as underreaction to new information. This paper investigates the role of information uncertainty in price continuation anomalies and cross‐sectional variations in stock returns. If short‐term price continuation is due to investor behavioral biases, we should observe greater price drift when there is greater information uncertainty. As a result, greater information uncertainty should produce relatively higher expected returns following good news and relatively lower expected returns following bad news. My evidence supports this hypothesis.     

Real Stock Returns and Inflation

This paper develops the relation between the real rate of return on the stock market and changes in the price level using a multiperiod economy with production. The observed relation between real ex post stock returns and inflation is shown to be consistent with equilibrium in an economy with rational investors. The relation between expected real returns and expected inflation is shown to depend on the form of the economy's production function and on the form of investor preferences. When the production function exhibits stochastic constant returns to scale, the model explains the negative relation between expected real returns and expected inflation which has frequently been observed in empirical studies.     

Sports Sentiment and Stock Returns

This paper investigates the stock market reaction to sudden changes in investor mood. Motivated by psychological evidence of a strong link between soccer outcomes and mood, we use international soccer results as our primary mood variable. We find a significant market decline after soccer losses. For example, a loss in the World Cup elimination stage leads to a next‐day abnormal stock return of ?49 basis points. This loss effect is stronger in small stocks and in more important games, and is robust to methodological changes. We also document a loss effect after international cricket, rugby, and basketball games.     

Investment Plans and Stock Returns

When the discount rate falls, investment should rise. Thus with time-varying discount rates and instantly changing investment, investment should positively covary with current stock returns and negatively covary with future stock returns. Aggregate nonresidential U.S. investment contradicts both these implications, probably because of investment lags. Investment plans, however, satisfy both implications. These investment plans, from a U.S. government survey of firms, are highly informative measures of expected investment and explain more than three-quarters of the variation in real annual aggregate investment growth. Plans have substantial forecasting power for excess stock returns, showing that time-varying risk premia affect investment.     

Diagnostic Expectations and Stock Returns

We revisit La Porta's finding that returns on stocks with the most optimistic analyst long‐term earnings growth forecasts are lower than those on stocks with the most pessimistic forecasts. We document the joint dynamics of fundamentals, expectations, and returns of these portfolios, and explain the facts using a model of belief formation based on the representativeness heuristic. Analysts forecast fundamentals from observed earnings growth, but overreact to news by exaggerating the probability of states that have become more likely. We find support for the model's predictions. A quantitative estimation of the model accounts for the key patterns in the data.     

Stock Market Returns and Consumption

This paper employs Swedish data on households' stock holdings to investigate how consumption responds to changes in stock market returns. We instrument the actual capital gains and dividend payments with past portfolio weights. Unrealized capital gains lead to a marginal propensity to consume of 23% for the bottom 50% of the wealth distribution and about 3% for the top 30% of the wealth distribution. Household consumption is significantly more responsive to dividend payouts across all parts of the wealth distribution. Our findings are consistent with households treating capital gains and dividends as separate sources of income.     

The Cross-Section of Expected Stock Returns

Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market β, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in β that is unrelated to size, the relation between market β and average return is flat, even when β is the only explanatory variable.