Evidence on the Characteristics of Cross Sectional Variation in Stock Returns

Firm sizes and book-to-market ratios are both highly correlated with the average returns of common stocks. Fama and French (1993) argue that the association between these characteristics and returns arise because the characteristics are proxies for nondiversifiable factor risk. In contrast, the evidence in this article indicates that the return premia on small capitalization and high book-to-market stocks does not arise because of the comovements of these stocks with pervasive factors. It is the characteristics rather than the covariance structure of returns that appear to explain the cross-sectional variation in stock returns.     

Risk,Mispricing, and Value Investing

We evaluate the stock return performance of a modified version of the book-to-market strategy and its implications for market efficiency. If the previously documented superior stock return of the book-to-market strategy represents mispricing, its performance should be improved by excluding fairly valued firms with extreme book-to-market ratios. To attain this, we classify stocks as value or glamour on book-to-market ratios and accounting accruals jointly. This joint classification is likely to exclude stocks with extreme book-to-market ratios due to mismeasured accounting book values reflecting limitations underlying the accounting system. Using both 12-month buy-and-hold returns and earnings announcement returns, our results show that this joint classification generates substantially higher portfolio returns in the post-portfolio-formation year than the book-to-market classification alone with no evidence of increased risk. In addition, this superior stock return performance is more pronounced among firms held primarily by small (unsophisticated) investors and followed less closely by market participants (stock price <$10). Finally, and most importantly, financial analysts are overly optimistic (pessimistic) about earnings of glamour (value) stock, and for a subset of firms identified as overvalued by our strategy, the earnings announcement raw return, as well as abnormal return, is negative. These last results are particularly important because it is hard to envision a model consistent with rational investors holding risky stocks with predictable negative raw returns for a long period of time rather than holding fT-bills and with financial analysts systematically overestimating the earnings of these stocks while underestimating earnings of stocks that outperform the stock market.     

Cashflow risk,systematic earnings revisions,and the cross-section of stock returns

The returns of stocks are partially driven by changes in their expected cashflow. Using revisions in analyst earnings forecasts, we construct an analyst earnings beta that measures the covariance between the cashflow innovations of an asset and those of the market. A higher analyst earnings beta implies greater sensitivity to marketwide revisions in expected cashflow, and therefore higher systematic risk. Our analyst earnings beta captures exposure to macroeconomic fluctuations and has a positive risk premium that provides a partial explanation for the value premium, size premium, and long-term return reversals. From 1984 to 2005, 55.1% of the return variation across book-to-market, size, and long-term return reversal portfolios is captured by their analyst earnings betas.     

Predicting stock returns

This paper studies whether incorporating business cycle predictors benefits a real time optimizing investor who must allocate funds across 3,123 NYSE-AMEX stocks and cash. Realized returns are positive when adjusted by the Fama-French and momentum factors as well as by the size, book-to-market, and past return characteristics. The investor optimally holds small-cap, growth, and momentum stocks and loads less (more) heavily on momentum (small-cap) stocks during recessions. Returns on individual stocks are predictable out-of-sample due to alpha variation, whereas the equity premium predictability, the major focus of previous work, is questionable.     

Return dispersion and expected returns

This paper proposes a two-factor asset-pricing model that incorporates market return and return dispersion. Consistent with this model, we find that stocks with higher sensitivities to return dispersion have higher average returns, and that return dispersion carries a significant positive price of risk. In particular, the return dispersion factor dominates the book-to-market factor in explaining cross-sectional expected returns. The return dispersion model outperforms the CAPM, MVM, IVM, and FF-3M when using a set of 5×5 test portfolios constructed from NYSE and AMEX stock returns from August 1963 to December 2005. Return dispersion continues to play an important role in explaining the cross-sectional variation of expected returns, even when market volatility, idiosyncratic volatility, size, book-to-market factors, and a momentum factor are included. This study sheds some light on the ability of return dispersion to explain expected returns beyond the standard asset-pricing factors. Our finding suggests that return dispersion captures two dimensions of systematic risk: the business cycle and fundamental economic restructuring.     

Liquidity risk,leverage and long-run IPO returns

We examine the risk-return characteristics of a rolling portfolio investment strategy where more than 6000 Nasdaq initial public offering (IPO) stocks are bought and held for up to 5 years. The average long-run portfolio return is low, but IPO stocks appear as “longshots”, as 5-year buy-and-hold returns of 1000% or more are somewhat more frequent than for non-issuing Nasdaq firms matched on size and book-to-market ratio. The typical IPO firm is of average Nasdaq market capitalization but has relatively low book-to-market ratio. We also show that IPO firms exhibit relatively high stock turnover and low leverage, which may lower systematic risk exposures. To examine this possibility, we launch an easily constructed “low-minus-high” (LMH) stock turnover portfolio as a liquidity risk factor. The LMH factor produces significant betas for broad-based stock portfolios, as well as for our IPO portfolio and a comparison portfolio of seasoned equity offerings. The factor-model estimation also includes standard characteristic-based risk factors, and we explore mimicking portfolios for leverage-related macroeconomic risks. Because they track macroeconomic aggregates, these mimicking portfolios are relatively immune to market sentiment effects. Overall, we cannot reject the hypothesis that the realized return on the IPO portfolio is commensurable with the portfolio's risk exposures, as defined here.     

Momentum and Autocorrelation in Stock Returns

This article studies momentum in stock returns, focusing onthe role of industry, size, and book-to-market (B/M) factors.Size and B/M portfolios exhibit momentum as strong as that inindividual stocks and industries. The size and B/M portfoliosare well diversified, so momentum cannot be attributed to firm-or industry-specific returns. Further, industry, size, and B/Mportfolios are negatively autocorrelated and cross-seriallycorrelated over intermediate horizons. The evidence suggeststhat stocks covary "too strongly" with each other. I argue thatexcess covariance, not underreaction, explains momentum in theportfolios.     

On the explanatory power of firm-specific variables in cross-sections of expected returns

This paper pertains to the controversy surrounding the explanatory power of certain firm-specific variables such as size and the book-to-market ratio in cross-sections of average stock returns. To investigate whether these firm-specific variables capture the sensitivity of returns to unobserved systematic risk, two sets of principal component factors are used. The first set is constructed from individual stock returns and the second set is from size- and book-to-market-sorted portfolio returns. The evidence from the first set of factors shows that size and the book-to-market ratio have little to do with factor betas. The evidence from the second set of factors shows that the forces underlying size and the book-to-market ratio are indeed systematic risks, although they explain very little return variation at the firm level, and that the betas of size- and book-to-market-sorted portfolio returns with respect to the corresponding systematic factors do explain the size and book-to-market effects.     

Institutional investors,intangible information,and the book-to-market effect

This paper establishes a robust link between the trading behavior of institutions and the book-to-market effect. Building on work by Daniel and Titman (2006), who argue that the book-to-market effect is driven by the reversal of intangible returns, I find that institutions tend to buy (sell) shares in response to positive (negative) intangible information and that the reversal of the intangible return is most pronounced among stocks for which a large proportion of active institutions trade in the direction of intangible information. Furthermore, the book-to-market effect is large and significant in stocks with intense past institutional trading but nonexistent in stocks with moderate institutional trading. This influence of institutional trading on the book-to-market effect is distinct from that of firm size. These results are consistent with the view that the tendency of institutions to trade in the direction of intangible information exacerbates price overreaction, thereby contributing to the value premium.     

Firm life expectancy and the heterogeneity of the book-to-market effect

I argue that the reason the book-to-market effect is stronger in small stocks is because smaller stocks generally have shorter life expectancy and therefore shorter equity duration. I build a model in which the book-to-market effect is stronger in stocks with shorter life expectancy. Empirically, I use delisting probability as my proxy for life expectancy. The data support my model's central prediction and its additional implications for stock return and variance. My results provide a rational explanation for the heterogeneity of the book-to-market effect, evidence previously taken as support for behavioral explanations.     

Jump risk,stock returns,and slope of implied volatility smile

In the presence of jump risk, expected stock return is a function of the average jump size, which can be proxied by the slope of option implied volatility smile. This implies a negative predictive relation between the slope of implied volatility smile and stock return. For more than four thousand stocks ranked by slope during 1996–2005, the difference between the risk-adjusted average returns of the lowest and highest quintile portfolios is 1.9% per month. Although both the systematic and idiosyncratic components of slope are priced, the idiosyncratic component dominates the systematic component in explaining the return predictability of slope. The findings are robust after controlling for stock characteristics such as size, book-to-market, leverage, volatility, skewness, and volume. Furthermore, the results cannot be explained by alternative measures of steepness of implied volatility smile in previous studies.     

Sensitivity to investor sentiment and stock performance of open market share repurchases

This paper finds that stocks of repurchasers with high sensitivity to investor sentiment are more likely to be mispriced. Thus, such repurchases are followed by superior post-buyback stock performance. This abnormal return associated with sensitivity to sentiment cannot be explained by other undervaluation factors: book-to-market or prior return effects. My results are robust with factor model analysis and controls for contamination effects. I conclude that this sentiment-driven undervaluation may result from the difficulty to value and/or limits to arbitrage rather than investor overreaction.     

Do zero-cost portfolios have the ability to predict economic growth? Evidence from Hong Kong, South Korea and Taiwan

In this paper we investigate the relationship between growth in future Gross Domestic Product (GDP) and Industrial Production (IDP) and the performance of SMB (small stocks minus big stocks) and HML (High book-to-market stocks minus low book-to-market stocks) portfolios for equities listed in Hong Kong, South Korea and Taiwan.We find evidence to suggest that: (a) the excess market return is positively related to future GDP or IDP growth in South Korea and Taiwan; (b) contrary to most European markets, Australia, Japan and the US, future economic growth is in general significantly negatively related to SMB in Hong Kong and South Korea; and, (c) a negative relationship between future economic growth and HML for Hong Kong. Our results cast doubt if SMB and HML portfolios are positive risk factors in the Fama and French (Fama, E. F., and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3-56) three-factor asset pricing model for Hong Kong, South Korea and Taiwan.     

Pricing deviation,misvaluation comovement,and macroeconomic conditions

We measure an individual stock’s misvaluation based on the deviation of its price from predicted intrinsic value. Both under- and overvalued stocks identified by this misvaluation measure exhibit greater valuation uncertainty and arbitrage difficulty, and the misvaluation measure strongly predicts stock returns incremental to size, book-to-market ratio, past returns, and various return anomalies. Based on the misvaluation measure, we form a misvaluation factor and find that stock return covariances with this factor possess significant and robust return predictive power. We further show that the misvaluation factor predicts future economic conditions, providing additional insight into the real effect of systematic misvaluation in the stock market.     

Return Predictability of Turkish Stocks: An Empirical Investigation

Employing the portfolio method and cross-sectional regressions, this paper provides a comprehensive analysis of stock return predictability in Turkey from January 1997 to July 2011. In the risk-related predictors, we found predictive power for beta, total volatility, and idiosyncratic volatility. The "cheapness" variable, book-to-market ratio, is the most important return predictor for the stocks traded on the Istanbul Stock Exchange (now part of the Borsa Istanbul). Grouping the stocks as small and large according to the median value of the market capitalization of the stocks adds important insights to the analysis. Our results show the set of large stocks on the Istanbul Stock Exchange to be the least predictable set of stocks.     

New Evidence on Risk Factors, Characteristics and the Cross-Sectional Variation of Japanese Stock Returns

This paper examines whether the cross-sectional variations in stock returns are better described by systematic risk factors or by firm characteristics such as book-to-market ratios and market capitalization. It provides new evidence from the Japanese stock market based on the recent sample period from 2002 to 2007, which is not addressed in the existing literature. Also, the new results are derived from the generalized method of moments applied to daily returns. The evidence suggests that both the firm size and book-to-market ratio are significantly related to average return premiums. There is mixed evidence, which tends to lend stronger support to the characteristic model rather than the Fama-French three-factor model as more reflective of the return dynamics in the Japanese stock market.     

The conditional relation between dispersion and return

The main goal of this paper is to examine the conditional pricing effect of return dispersion on the cross section of returns. We observe a systematic conditional relation between dispersion and return even after controlling for market, size and book-to-market factors. However, we find that return dispersion risk is asymmetrically priced with a significantly positive premium observed during periods of large market gains only. The findings are found to be robust to alternative conditional specifications of market returns, suggesting asymmetric pricing effect of the return dispersion factor. We provide alternative explanations for the systematic risk captured by the return dispersion factor and discuss implications for portfolio management and corporate decisions.     

An Analysis of Contrarian Investment Strategies in the UK

The performance of contrarian, or value strategies – those that invest in stocks that have low market value relative to a measure of their fundamentals – continues to attract attention from researchers and practitioners alike. While there is much extant evidence on the profitability of value strategies, however, most of this evidence pertains to the US. In this paper, we provide a detailed characterisation of value strategies using data on UK stocks for the period 1975 to 1998. We first undertake simple one-way and two-way classifications of stocks in which value is defined using both past performance and expected future performance. Using sales growth as a proxy for past performance and book-to-market, earnings yield and cash flow yield as measures of expected future performance, we find that that stocks that have both poor past performance and low expected future performance have significantly higher returns than those that have either good past performance or good expected future performance. Allowing for size effects in returns reduces the value premium but it nevertheless remains significant. We go on to explore whether the profitability of value strategies in the UK can be explained using the three factor model of Fama and French (1996). Broadly consistent with the results for the US, we find that using the one-way classification the excess returns to almost all value strategies can be explained by their loading on the market, book-to-market and size factors. However, in contrast with the US, using the two-way classification there are excess returns to value strategies based on book-to-market and sales growth, even after controlling for their loading on the market, book-to-market and size factors.     

Disagreement and return predictability of stock portfolios

This paper provides evidence that portfolio disagreement measured bottom-up from individual-stock analyst forecast dispersions has a number of asset pricing implications. For the market portfolio, market disagreement mean-reverts and is negatively related to ex post expected market return. Contemporaneously, an increase in market disagreement manifests as a drop in discount rate. For book-to-market sorted portfolios, the value premium is stronger among high disagreement stocks. The underperformance by high disagreement stocks is stronger among growth stocks. Growth stocks are more sensitive to variations in disagreement relative to value stocks. These findings are consistent with asset pricing theory incorporating belief dispersion.     

Are extreme returns priced in the stock market? European evidence

This paper revisits some recently found evidence in the literature on the cross-section of stock returns for a carefully constructed dataset of euro area stocks. First, we confirm recent results for US data and find evidence of a negative cross-sectional relation between extreme positive returns and average returns after controlling for characteristics such as momentum, book-to-market, size, liquidity and short term return reversal. We argue that this is the case because these stocks have lottery-like characteristics, which is attractive to certain investors. Also, these stocks tend to be very volatile so that arbitrageurs are discouraged from correcting potential mispricing. As a consequence, these stocks are often overpriced and hence face lower expected returns. Second, when we control for extreme returns, the recently found negative relationship between idiosyncratic risk and future returns is less robust. In our models, after adding maximum returns, the relationship is insignificant and sometimes even positive. We also find that idiosyncratic skewness and coskewness play an important role for asset pricing, as predicted by several theoretical models.