Expectations and the Cross-Section of Stock Returns

Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. I test for the existence of systematic errors using survey data on forecasts by stock market analysts. I show that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme.     

Asset Growth and the Cross-Section of Stock Returns

We test for firm-level asset investment effects in returns by examining the cross-sectional relation between firm asset growth and subsequent stock returns. Asset growth rates are strong predictors of future abnormal returns. Asset growth retains its forecasting ability even on large capitalization stocks. When we compare asset growth rates with the previously documented determinants of the cross-section of returns (i.e., book-to-market ratios, firm capitalization, lagged returns, accruals, and other growth measures), we find that a firm's annual asset growth rate emerges as an economically and statistically significant predictor of the cross-section of U.S. stock returns.     

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.     

Investor Sentiment and the Cross-Section of Stock Returns

We study how investor sentiment affects the cross‐section of stock returns. We predict that a wave of investor sentiment has larger effects on securities whose valuations are highly subjective and difficult to arbitrage. Consistent with this prediction, we find that when beginning‐of‐period proxies for sentiment are low, subsequent returns are relatively high for small stocks, young stocks, high volatility stocks, unprofitable stocks, non‐dividend‐paying stocks, extreme growth stocks, and distressed stocks. When sentiment is high, on the other hand, these categories of stock earn relatively low subsequent returns.     

Monetary Policy and the Cross-Section of Expected Stock Returns

Ample evidence shows that size and book-to-market equity explain significant cross-sectional variation in stock returns, whereas beta explains little or none of the variation. Recent studies also demonstrate that proxies for monetary stringency increase the explained variation in stock returns. We reexamine a three-factor model that includes beta, size, and book-to-market equity, while allowing monetary conditions to influence the relations between these risk factors and average stock returns. We find that ex-ante proxies for monetary stringency significantly influence the relations between stock returns and all three risk factors. Additionally, all three variables are found to contribute significantly to explaining cross-sectional returns in a three-factor model that includes the monetary sector.     

The Cross-Section of Stock Returns on The Shanghai Stock Exchange

This study explores the cross-sectional stock return behavior on the A-share market of the Shanghai Stock Exchange (SSE), which is segmented from world's other equity markets. We estimate the effects of beta, firm size, book-to-market equity ratio and a variable unique to the Chinese stock markets, the proportion of firm's floating (tradable) equity over total equity on SSE stocks over the period 1993–2002. We find that smaller firms and value stocks perform better. Systematic risk is negatively significant in down markets. The proportion of floating equity has no direct effect on stock returns. JEL Classification: G14, G15     

Predicting Stock Market Returns with Aggregate Discretionary Accruals

We find that the positive relation between aggregate accruals and one‐year‐ahead market returns documented in Hirshleifer, Hou, and Teoh [2009] is driven by discretionary accruals but not normal accruals. The return forecasting power of aggregate discretionary accruals is robust to choices of sample periods, return measurements, estimation methods, business condition and risk premium proxies, and accrual models used to isolate discretionary accruals. Our extensive analysis shows that aggregate discretionary accruals, in sharp contrast to aggregate normal accruals, contain little information about overall business conditions or aggregate cash flows and display little co‐movement with ICAPM‐motivated risk premium proxies. Our findings imply that aggregate discretionary accruals likely reflect aggregate fluctuations in earnings management, thereby favoring the behavioral explanation that managers time aggregate equity markets to report earnings.     

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.     

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.     

The Role of Expectations in Explaining the Cross-Section of Stock Returns

We find highly significant results when the cross-section of market-adjusted stock returns is regressed against changes in analyst expectations this year about: (1) this year's earnings, (2) next year's earnings, (3) long-term earnings growth, and (4) noise (measured as the standard deviation of analyst forecasts). Surprisingly, changes in expectations about this year's earnings are not significant in a multiple regression with the other independent variables. Changes in expectations about next year's earnings are highly significant but with an impact that is much smaller than that of changes in expectations about the long-term growth in earnings. Changes in noise are also statistically significant and are negatively related to market-adjusted returns, an indication that the signal to noise ratio, rather than merely the signal, is what drives price adjustments to new information.     

The Cross-Section of Realized Stock Returns: The Pre-COMPUSTAT Evidence

Using a database that is free of survivorship bias, this article finds that book-to-market equity, earnings yield, and cash flow yield have significant explanatory power with respect to the cross-section of realized stock returns during the period from July 1940 through June 1963. There is a strong January seasonal in the explanatory power of these variables, even though small stocks are, by construction, excluded from the sample.     

Cash Flow, Consumption Risk, and the Cross-section of Stock Returns

I link an asset's risk premium to two characteristics of its underlying cash flow: covariance and duration. Using empirically novel estimates of both cash flow characteristics based exclusively on accounting earnings and aggregate consumption data, I examine their dynamic interaction in a two-factor cash flow model and find that they are able to explain up to 82% of the cross-sectional variation in the average returns on size, book-to-market, and long-term reversal-sorted portfolios for the period 1964 to 2002. This finding highlights the importance of fundamental cash flow characteristics in determining the risk exposure of an asset.     

The Role of Beta and Size in the Cross-Section of European Stock Returns

This paper examines the ability of beta and size to explain cross-sectional variation in average returns in 12 European countries. We find that average stock returns are positively related to beta and negatively related to firm size. The beta premium is in part due to the fact that high beta countries outperform low beta countries. Within countries high beta stocks outperform low beta stocks only in January, not in other months. We reject the hypothesis that differences in average returns on size- and beta-sorted portfolios can be explained by market risk and exposure to the excess return of small over large stocks (SMB). Consistent with recent US evidence, we find that after controlling for size, there is no association between average returns and exposure to SMB.     

Online Search Frequency,Retail Investor Overreaction,and the Cross-Section of Stock Returns: Evidence from the Chinese Stock Market

I find a strong negative relation between online search frequency and future returns on the Chinese stock market. I suggest that this effect captures retail investor overreaction to unexpected signals, because online search frequency reflects the efforts made by investors to obtain firm-specific knowledge. The effect is particularly strong in stocks with high information uncertainty (high analyst dispersion, big past earnings surprises, low analyst coverage, and large trading volume), whose intrinsic values are difficult or costly for investors to estimate. Online search frequency as a direct indicator of retail investors’ reaction to signals also sheds light on the idiosyncratic volatility (IVOL) puzzle. I find that this puzzle is more pronounced in high-search-frequency subsamples and disappears in low-search-frequency subsamples. Further evidence shows that high search frequency strengthens the negative IVOL effect in stocks with positive signals but weakens this effect in stocks with negative signals. I suggest that the IVOL puzzle in the Chinese market can be partially explained as a reversal following overreaction to positive signals by retail investors.     

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.     

Macro Liquidity Risk,Money Growth,and the Cross-Section of Stock Returns: The Case of Korea

According to the homogeneity of money holding purpose, we decompose the broad money M2 into an underlying and a non-underlying part and propose innovations in future non-underlying M2 growth as a proxy for macro liquidity. In both the cross-sectional regression tests and the GMM tests, we find that risk related to innovations in future non-underlying M2 growth is strongly significantly priced in Korea, after controlling for the well-known risk factors and other macroeconomic variables. Meanwhile, risk related to innovations in future aggregate or underlying M2 growth is insignificantly priced. These results indicate that non-underlying M2 growth more directly affects macro liquidity than does aggregate or underlying M2 growth.     

Can Investors Profit from the Prophets? Security Analyst Recommendations and Stock Returns

We document that purchasing (selling short) stocks with the most (least) favorable consensus recommendations, in conjunction with daily portfolio rebalancing and a timely response to recommendation changes, yield annual abnormal gross returns greater than four percent. Less frequent portfolio rebalancing or a delay in reacting to recommendation changes diminishes these returns; however, they remain significant for the least favorably rated stocks. We also show that high trading levels are required to capture the excess returns generated by the strategies analyzed, entailing substantial transactions costs and leading to abnormal net returns for these strategies that are not reliably greater than zero.     

C-CAPM Refinements and the Cross-Section of Returns

This paper studies if the consumption-based asset pricing model can explain the cross-section of expected returns. The CRRA model and several refinements (habit persistence and idiosyncratic shocks) all imply that the conditional expected return is linearly increasing in the asset’s conditional covariance with consumption growth. Results from quarterly data on the 25 Fama-French portfolios suggest that the model has serious problems: there are large and systematic pricing errors. In addition, the estimated time-varying effective risk aversion coefficients appear implausible and are unrelated with most candidates for habit persistence and idiosyncratic risk.     

The Cross-Section of Expected Stock Returns: New Evidence from an Emerging Market

Over 300 factors have been found to explain the cross-section of expected stock returns. Empirical studies also show that findings from multifactor asset-pricing models have not been consistent in an emerging market. Using DuPont analysis and a residual income valuation model for 284 nonfinancial companies on Ho Chi Minh Stock Exchange during the period 2008–2014, findings suggest that the return on equity and its change are informative for stock returns in Vietnam. In addition, the level of capital turnover, financial cost ratio (FCR), and changes in capital and in the FCR contain incremental explanatory power for stock returns.