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.     

Robust portfolio choice with stochastic interest rates

We determine the optimal investment strategy for an ambiguity-averse investor in a setting with stochastic interest rates. The investor has access to stocks, bonds, and a bank account and he is ambiguous about the expected rate of return of both bonds and stocks. The investor can have different levels of ambiguity aversion about the two types of risky assets. We find that it is more important to take model uncertainty about the stock dynamics than model uncertainty about the bond dynamics into account. Furthermore, the investor’s ambiguity increases his hedging demand. Consequently, the bond/stock ratio increases with his ambiguity and implies less extreme positions in the bank account. Altogether, our model yields portfolio allocations which are more in line with what is implementable in practice. Finally, we demonstrate that neglecting model uncertainty implies significant losses for the investor.     

The term structures of equity and interest rates

This paper proposes a dynamic risk-based model capable of jointly explaining the term structure of interest rates, returns on the aggregate market, and the risk and return characteristics of value and growth stocks. Both the term structure of interest rates and returns on value and growth stocks convey information about how the representative investor values cash flows of different maturities. We model how the representative investor perceives risks of these cash flows by specifying a parsimonious stochastic discount factor for the economy. Shocks to dividend growth, the real interest rate, and expected inflation are priced, but shocks to the price of risk are not. Given reasonable assumptions for dividends and inflation, we show that the model can simultaneously account for the behavior of aggregate stock returns, an upward-sloping yield curve, the failure of the expectations hypothesis, and the poor performance of the capital asset pricing model.     

The cross-section of stock returns in an early stock market

Using a new dataset which contains monthly data on 1015 stocks traded on the London Stock Exchange between 1825 and 1870, we investigate the cross section of stock returns in this early capital market. Unique features of this market allow us to evaluate the veracity of several popular explanations of asset pricing behavior. Using portfolio analysis and Fama–MacBeth regressions, we find that stock characteristics such as beta, illiquidity, dividend yield, and past-year return performance are all positively correlated with stock returns. However, market capitalization and past-three-year return performance have no significant correlation with stock returns.     

COSKEWNESS,DIVIDEND YIELD AND CAPITAL ASSET PRICING

The coskewness and dividend yield effects on capital asset prices have been established in two separate literatures. Neither literature controls for the variable in the other, nor for other potentially confounding factors such as size of the firm and the January effect on returns. Using stock return data for 1969–1978, this study provides evidence of coskewness, size, yield and January effects on stock returns. Coskewness appears to be a surrogate variable for dividend yield. When yield is controlled for, the coskewness effect cannot be detected. Hence, the significance of coskewness seems to result from the presence of the uncontrolled factor, dividend yield.     

Time-varying risk The case of the American computer industry

A bivariate GARCH-in-mean model for individual stock returns and the market portfolio is designed to model volatility and to test the conditional Capital Asset Pricing Model versus the conditional Residual Risk Model. We find that a univariate model of volatility for individual stock returns is misspecified. A joint modelling of the market return and the individual stock return shows that a major force driving the conditional variances of individual stocks is the history contained in the market return variance. We find that a conditional residual risk model, where the variance of the individual stock return is used to explain expected returns, is preferred to a conditional CAPM. We propose a partial ordering of securities according to their market risk using first and second order dominance criteria.     

Ex-Dividend Returns and the Tax Reform Act of 1986

As previously recognized, the Tax Reform Act of 1986 reduced observed ex-day returns to stocks that do not attract dividend capture trading. However, by decreasing the top corporate tax rate, and decreasing the corporate dividend income deduction, the Act also reduced the return to dividend capture by U.S. corporations. The ex-day returns for stocks that had previously attracted corporate dividend capture should therefore increase. This prediction is consistent with evidence that ex-day returns increased after the Act was implemented, among low-transaction cost, high-dividend yield stocks and among low-risk, high-dividend yield stocks.     

Taxes,dividend yields and returns in the UK equity market

The higher rate of taxation on dividend income relative to capital gains has been offered as an explanation for the positive relation between stock returns and dividend yields among US firms. In the UK the relative tax rates are the reverse of those in the US. Thus, UK data provides an independent test of the tax-based approach to explaining the relation between stock returns and dividend yields. We find that high yielding stocks earn positive risk adjusted returns, whereas low yielding stocks earn negative risk adjusted returns. We also detect evidence of non-linearity in the performance of zero-dividend stocks. Controlling for firm size, seasonality and market risk we find a significant positive relation between dividend yields and returns. We conclude that the evidence is inconsistent with a tax-based explanation.     

A simple examination of the empirical relationship between dividend yields and deviations from the CAPM

Several papers have been published in recent years dealing with both the theoretical and the empirical impact of dividend yields on security returns. Dividends have been postulated as affecting stock returns because of tax effects, agency costs and the Wealth Transfer Hypothesis. In this paper we perform a purely empirical examination of whether and to what extent deviations from the zero beta form of the CAPM are explained by divident yields. The paper demonstrates that dividend yield has a large and statistically significant impact on return above and beyond that explained by the zero beta form of the CAPM. This is consistent with the findings of Litzenberger and Ramaswamy. In addition our results are consistent with the findings of small firm effects.     

Social media effect,investor recognition and the cross-section of stock returns

Investor recognition affects cross-sectional stock returns. In informationally incomplete markets, investors have limited recognition of all securities, and their holding of stocks with low recognition requires compensation for being imperfectly diversified. Using the number of posts on the Chinese social media platform Guba to measure investor recognition of stocks, this paper provides a direct test of Merton's investor recognition hypothesis. We find a significant social media premium in the Chinese stock market. We further find that including a social media factor based on this premium significantly improves the explanatory power of Fama-French factor models of cross-sectional stock returns, and these results are robust when we control for the mass media effect and liquidity effect. Finally, we find that investment strategies based on the social media factor earn sizable risk-adjusted returns, which signifies the importance of the social media premium in portfolio management.     

Expected returns and expected dividend growth

We investigate a consumption-based present-value relation that is a function of future dividend growth and find that changing forecasts of dividend growth are an important feature of the post-war U.S. stock market, despite the failure of the dividend–price ratio to uncover such variation. In addition, dividend forecasts are found to covary with changing forecasts of excess stock returns over business cycle frequencies. This covariation is important because positively correlated fluctuations in expected dividend growth and expected returns have offsetting effects on the log dividend–price ratio. The market risk premium and expected dividend growth thus vary considerably more than is apparent using the log divided–price ratio alone as a predictive variable.     

The dividend–price ratio does predict dividend growth: International evidence

Unpredictable dividend growth by the dividend–price ratio is considered a ‘stylized fact’ in post war US data. Using long-term annual data from the US and three European countries, we revisit this stylized fact, and we also report results on return predictability. We make two main contributions. First, we document that for the US, results for long-horizon predictability are crucially dependent on whether returns and dividend growth are measured in nominal or real terms, and this difference is due to long-term inflation being strongly negatively predictable by the dividend–price ratio. The impact of inflation is to reinforce real return predictability and to reduce – or change direction of – real dividend growth predictability. This provides an explanation for the strong predictability of long-horizon real returns in the ‘right’ direction, and the strong predictability of long-horizon real dividend growth in the ‘wrong’ direction, that we see in US post war data. Second, we find that predictability patterns in three European stock markets are in many ways different from what characterize the US stock market. In particular, in Sweden and Denmark dividend growth is strongly predictable by the dividend–price ratio in the ‘right’ direction while returns are not predictable. The results for the UK are mixed. Our results are robust to a number of changes in the modeling framework. We discuss the results for dividend growth predictability in terms of the ‘dividend smoothing hypothesis’.     

The return impact of realized and expected idiosyncratic volatility

We show that the negative relation between realized idiosyncratic volatility, measured over the prior month, and returns is robust in non-January months. Controlling for realized idiosyncratic volatility, we show that the relation between returns and expected idiosyncratic volatility is positive and robust. Realized and expected idiosyncratic volatility are separate and important effects describing the cross-section of returns. We find the negative return on a zero-investment portfolio that is long high realized idiosyncratic volatility stocks and short low realized idiosyncratic volatility stocks is dependent on aggregate investor sentiment. In cross-sectional tests, we find the negative relation is weaker for stocks with a large analyst following and stronger for stocks with high dispersion of analyst forecasts. The positive relation between expected idiosyncratic volatility and returns is not due to mispricing.     

Differences in Perstistence in Aggregated and Disaggregated UK Stock Returns: A Reconciliation

Studies of the persistence in the returns series of UK stocks, using inter alia variance ratios, have documented clear differences between the relatively low levels of persistence in individual security returns and the relatively high levels of persistence in the returns of portfolios composed of these same securities. In this paper, I reconcile this contrast by showing that portfolio return variance ratios should not be expected to reflect (own) persistence levels in the component security returns, but instead should reflect a 'cross-persistence' between the securities. I calculate synthetic portfolio variance ratios from measures of security return 'cross-persistence' and find that they replicate closely the observed portfolio return variance ratios, which provides empirical support for the theoretical results.     

The modified dividend–price ratio

We show that log-dividends (d) and log-prices (p) are cointegrated, but, instead of de facto assuming the stationarity of the classical log dividend–price ratio, we allow the data to reveal the cointegration vector between d and p. We define the modified dividend–price ratio (mdp), as the long run trend deviation between d and p. Using S&P 500 data for the period 1926 to 2012, we show that mdp provides substantially improved forecasting results over the classical dp ratio. Out of sample, while the dp ratio cannot outperform the “simplistic forecast” benchmark for any useful horizon, an investor who employs the mdp ratio will do significantly better in forecasting 3-, 5- and 7-year returns with an R_OS² of 7%, 26% and 31% respectively. In some sense mdp can be considered as a de-noising of the classical ratio as it addresses the major weakness in dp, its presumed inability in revealing business cycle variation in expected returns. Unlike dp, mdp exhibits positive correlation with the risk free return component, and can discern if a low dividend state coincides with a low yield state.     

Is dividend smoothing universal?: New insights from a comparative study of dividend policies in Hong Kong and the U.S.

In this paper, we develop new insights about the dynamics of corporate dividend policy by performing the natural experiment of comparing corporate dividend policies in Hong Kong and the U.S., two economies where the tax regime and equity ownership structure are significantly different. Our empirical results can be summarized as follows. First, a test of the Lintner model reveals that the extent of dividend smoothing by firms in Hong Kong is significantly less than those in the U.S. Second, the signaling effects of dividend changes on stock returns are stronger in the U.S. compared to those in Hong Kong. Third, our logit analysis of the determinants of dividend changes indicates that, while the lagged dividend yield significantly affects dividend changes in both countries in the same fashion, prior year stock returns have opposite effects on dividend changes in the two countries. Finally, the extent of dividend smoothing is not systematically related to blockholder equity ownership in either country. Overall, our results suggest that, compared to U.S. firms, Hong Kong firms pursue a more flexible dividend policy commensurate with earnings, and that the differences between the dividend policies of firms in the two countries are consistent with the signaling implications of the differences in the tax regime across the two countries.     

Stock Returns, Dividend Yields, and Taxes

Using an improved measure of a common stock's annualized dividend yield, we document that risk-adjusted NYSE stock returns increase in dividend yield during the period from 1963 to 1994. This relation between return and yield is robust to various specifications of multifactor asset pricing models that incorporate the Fama–French factors. The magnitude of the yield effect is too large to be explained by a "tax penalty" on dividend income and is not explained by previously documented anomalies. Interestingly, the effect is primarily driven by smaller market capitalization stocks and zero-yield stocks.     

Connecting two markets: An equilibrium framework for shorts,longs, and stock loans

We analyze a reduced-form framework for understanding the equity loan market's impact on share prices. We show that hard-to-borrow stocks will have distinct return patterns, responding more to shocks in the supply of shares available, and to changes in the heterogeneity of investor beliefs, than other stocks. We conduct two empirical tests in which we find strong support for these equilibrium predictions. In our first test, we take advantage of a tax-driven exogenous shock to share loan supply and find that when supply is reduced around dividend record dates, prices of hard-to-borrow stocks increase 1.1% while prices of easy-to-borrow stocks are unaffected. In our second test, we find that hard-to-borrow stocks have 4.8% lower three-month returns than other stocks, with negative returns concentrated in stocks with high heterogeneity in investor beliefs. Thus, we extend the Diether, Malloy, and Scherbina (2002) result that stocks with a greater dispersion of investor beliefs have lower returns.     

Accounting Ratios and the Cross‐section of Expected Stock Returns

Under clean‐surplus accounting, the log return on a stock can be decomposed into a linear function of the contemporaneous log return on equity, the contemporaneous log dividend–price ratio (if the stock pays a dividend), and both the contemporaneous and lagged values of the log book‐to‐market equity ratio. This paper studies the implications of this decomposition for the cross‐section of conditional expected stock returns. The empirical analysis reveals that the log accounting ratios capture cross‐sectional variation in both the conditional mean and conditional variance of log stock returns, which is consistent with the decomposition. It also brings fresh insights to the relation between firm size (market equity) and conditional expected stock returns. The evidence indicates that the conditional median return increases with firm size, while the conditional return skewness decreases with firm size. Empirically, the skewness effect outweighs the median effect, leading to the well‐documented inverse relation between size and average returns. The results of out‐of‐sample tests suggest that investors could use the information provided by the observed values of the log accounting ratios to formulate more effective portfolio strategies.     

Stock returns,dividend yield,and book-to-market ratio

A dividend yield model has been widely used in previous research that relates stock market valuations to cash flow fundamentals. Given controversies about using dividends as a proxy for cash flows, a loglinear book-to-market model has recently been proposed. However, these models rely on the assumption that dividend yield and book-to-market ratio are both stationary, and empirical evidence for this is, at best, mixed. We develop a new model, the loglinear cointegration model, that explains future profitability and excess stock returns in terms of a linear combination of log book-to-market ratio and log dividend yield. The loglinear cointegration model performs better than the log dividend yield model and the log book-to-market model in terms of cross-equation restriction tests and forecasting performance comparisons. The superior performance of the loglinear cointegration model suggests that the linear combination may be a better indicator of intrinsic fundamentals than the dividend yield or the book-to-market ratio separately.