Cross-Sectional Dispersion and Expected Returns


Book Description

This study investigates whether the cross-sectional dispersion of stock returns, which reflects the aggregate level of idiosyncratic risk in the market, represents a priced state variable. We find that stocks with high sensitivities to dispersion offer low expected returns. Furthermore, a zero-cost spread portfolio that is long (short) in stocks with low (high) dispersion betas produces a statistically and economically significant return, after accounting for its exposure to other systematic risk factors. Dispersion is associated with a significantly negative risk premium in the cross-section (-1.32% per annum) which is distinct from premia commanded by a set of alternative systematic factors. These results are robust to a wide set of stock characteristics, market conditions, and industry groupings.




Aggregation of Information About the Cross Section of Stock Returns


Book Description

We propose a new approach for estimating expected returns on individual stocks from a large number of firm characteristics. We treat expected returns as latent variables and apply the partial least squares (PLS) estimator that filters them out from the characteristics under an assumption that the characteristics are linked to expected returns through one or few common latent factors. The estimates of expected returns constructed by our approach from twenty six firm characteristics generate a wide cross-sectional dispersion of realized returns and outperform estimates obtained by alternative techniques. Our results also provide evidence of commonality in asset pricing anomalies.




Dispersion of Beliefs, Ambiguity, and the Cross-Section of Stock Returns


Book Description

We examine whether ambiguity is priced in the cross-section of expected stock returns. Using the cross-sectional dispersion in real-time forecasts of real GDP growth as a measure for ambiguity, we find that high ambiguity beta stocks earn lower future returns relative to low ambiguity beta stocks. This negative predictive relation between the ambiguity beta and future returns is consistent with theory, which predicts the marginal utility of consumption to rise when ambiguity is high. We further show that the ambiguity premium remains significant after controlling for exposures to expected real GDP growth, VIX, and financial market dislocations index.




Statistics of Random Processes II


Book Description

"Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW




Investor Overreaction, Cross-Sectional Dispersion of Firm Valuations, and Expected Stock Returns


Book Description

This paper develops the theoretical predictions that when investor overreaction to market-wide information is larger, firm valuations in the cross-section become more dispersed, and stocks on average earn lower expected returns. Consistent with the model prediction, I find that my measure of firm valuation dispersion measure is a negative predictor of subsequent aggregate returns. The dispersion-return relation is most pronounced among firms that have highly subjective valuations and significant limits of arbitrage.




The Cross-Sectional Dispersion of Stock Returns, Alpha and the Information Ratio


Book Description

Both the cross-sectional dispersion of U.S. stock returns and the VIX provide forecasts of alpha dispersion across high- and low-performing portfolios of stocks that are statistically and economically significant. These findings suggest that absolute return investors can use cross-sectional dispersion and time-series volatility as signals to improve the tactical timing of their alpha-focused strategies. Because active risk increases by a greater amount than alpha, however, high return dispersion/high VIX periods are followed by slightly lower information ratio dispersion. Therefore, relative return investors who keep score in an information ratio framework are unlikely to find return dispersion useful as a signal regarding when to increase or decrease the activeness of their portfolio strategies.




The Second Moment Matters! Cross-Sectional Dispersion of Firm Valuations and Expected Stock Returns


Book Description

Behavioral theories predict that firm valuation dispersion in the cross section (ldquo;dispersionrdquo;) measures aggregate overpricing caused by investor overconfidence and should be negatively related to expected aggregate returns. This paper develops and tests these hypotheses. Consistent with the model predictions, I find that measures of dispersion are positively related to aggregate valuations, trading volume, idiosyncratic volatility, past market returns, and current and future investor sentiment indexes. Dispersion is a strong negative predictor of subsequent shortand long-term market excess returns. Market beta is positively related to stock returns when the beginning-of-period dispersion is low and this relationship reverses when initial dispersion is high. A simple forecast model based on dispersion significantly outperforms a naive model based on historical equity premium in out-of-sample tests and the predictability is stronger in economic downturns.




Earnings Dispersion and Aggregate Stock Returns


Book Description

While aggregate earnings should affect aggregate stock returns, standard portfolio theory predicts that the cross-sectional dispersion in firm-level earnings per se would not affect aggregate stock returns. Nonetheless, this paper documents that cross-sectional earnings dispersion is positively related with contemporaneous stock returns and negatively related with lagged stock returns. A possible interpretation of our findings is that an increase in uncertainty causes expected returns to rise, which in turn causes prices to fall. Since prices anticipate future earnings, the uncertainty is manifested in earnings dispersion in the following year (resulting in a negative relation between earnings dispersion and lagged returns). In addition, because the higher earnings dispersion is associated with higher expected returns, the contemporaneous relation between dispersion and stock return is positive. Our findings are robust to including macroeconomic indicators that prior research show is correlated with stock returns.




Cross-Sectional Determinants of Expected Returns


Book Description

We analyze the relation between equity returns, risk, and a rich set of security characteristics that includes institutional ownership, Samp;P 500 index membership, analyst following, and dispersion in analyst forecasts, in addition to previously examined variables such as the book-to-market ratio, firm size, the bid-ask spread, and lagged returns. Our primary objective is to determine whether these characteristics have marginal explanatory power relative to the Connor and Korajczyk (1988) risk factors. We also compare the different approaches that have been used to test asset pricing models against specific alternatives. We find that inferences are extremely sensitive to the sorting criteria used for portfolio formation, so that results based on regressions using portfolio returns should be interpreted with caution. Fama-MacBeth type regressions for individual securities suggest some new findings: risk-adjusted stock returns show a puzzling negative (and strongly significant) relation to the bid-ask spread, a negative relation with both size and share turnover, and a positive relation with both Samp;P 500 membership and analyst following. However, previously noted book-to-market and size effects are eliminated once account is taken of the above characteristics.




Expectations and the Structure of Share Prices


Book Description

John G. Cragg and Burton G. Malkiel collected detailed forecasts of professional investors concerning the growth of 175 companies and use this information to examine the impact of such forecasts on the market evaluations of the companies and to test and extend traditional models of how stock market values are determined.