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.     

Determinants of asymmetric return comovements of gold and other financial assets

Using conditional time-varying copula models, we characterize the dependence structure of return comovements of gold and other financial assets (stocks, bonds, real estate and oil) during economic expansion and contraction regimes. We also investigate which key macroeconomic and non-macroeconomic variables significantly impact the asset return comovements using a two stage Markov Switching Stochastic Volatility (MSSV) framework. Our results show that the non-macro variables have significant influence on the return comovements. We find that gold is an inappropriate hedge against interest rate changes for real-estate and oil-based portfolios, while for bond portfolios, gold offers a good hedge against inflation uncertainty. We also provide evidence that the “flight to safety” phenomenon is due to the implied volatility of the stock market, rather than the observed stock market uncertainty. Finally, we forecast the asset return comovements and examine their economic significance. We show that a dynamic MSSV model which includes the macroeconomic and non-macroeconomic variables yields superior forecast of future asset return comovements when compared with a multivariate conditional covariance model.     

Importance of skewness in decision making: Evidence from the Indian stock exchange

In this paper our goal is to examine the importance of skewness in decision making, in particular on investor utility. We use time-series daily data on sectoral stock returns on the Indian stock exchange. We test for sectoral stock return predictability using commonly used financial ratios, namely, the price-to-book, dividend yield and price-earnings. We find strong evidence of predictability. Using this evidence of predictability, we forecast sectoral stock returns for each of the sectors in our sample, allowing us to devise trading strategies that account for skewness of returns. We discover evidence that accounting for skewness leads not only to higher utility compared to a model that ignores skewness, but utility is sector-dependent.     

Equity premium estimates from economic fundamentals under structural breaks

This article compares three estimates of the conditional equity premium using dividend and earnings growth rates to measure the expected rate of capital gain. The premia are estimated using a theory-informed Bayesian model that admits structural breaks. The equity premium fell from 8.16% in 1951 to 1.15% in 1985. Approximately half of this decline was reversion of a high conditional premium to the long run mean and the remainder resulted from a decline in the expected stock return. The decline in the expected stock return was largely driven by the Fed Accord (1951) and the Fed's ‘monetarist policy experiment’ (1979–1982).     

Is the Market Portfolio a Dynamic Factor? Evidence from Individual Stock Returns

This paper uses a factor model to test whether the market portfolio is a dynamic factor in the sense that individual stock returns contain a premium linked to the conditional risk of the market portfolio. The market conditional risk is based on a decomposition of the market variance into a time-varying trend component and a transitory component. The evidence shows that the conditional market premium is rising when the permanent trend rises relative to the conditional variance. The evidence for individual stock returns supports the notion that the market portfolio is a dynamic factor. Individual stock return autocorrelations are fully explained by the time variation in the market premium. The risk premia attributed to static factors are statistically insignificant.     

Excess stock returns and news: evidence from European markets

This paper aims at decomposing the forecast error variance of excess returns in five major European stock markets into the variance of news about future excess returns, dividends and real interest rates. Special emphasis is given on the issue of stationarity and structural breaks in the unconditional mean of dividend yields and their implications for variance decompositions. Empirical results indicate that in some markets the dividend yield is subject to structural breaks in the mean. Evidence from Monte Carlo simulations suggests that this kind of structural breaks cause small-sample bias in variance decompositions of a magnitude comparable to bias introduced by unit roots. Our results constitute a warning about return decompositions that, in particular, use variables in the forecasting equations that may be nonstationary or contain a structural break.     

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.     

Predictable events and excess returns: The case of dividend announcements

This paper hypothesizes that the risk per unit of time and the required rate of return are higher than normal during an event period whose timing can be predicted. Consistent with this hypothesis this paper presents empirical evidence indicating that the unconditional mean rate of return, the variance of stock returns and their systematic risk are higher than ‘usual’ during dividend announcement periods. However, the documented increases in the systematic risk are not large enough to fully explain the ‘excess returns’. This finding is puzzling and hard to reconcile with existing theory.     

The Predictive Ability of Dividend and Earnings Yields for Long-Term Stock Returns

We use empirical models to examine the predictive ability of dividend and earnings yields for long‐term stock returns. Results show that dividend and earnings yields share a similar predictive power for future stock returns and growth. We find that the predictive power of dividend yields increases with the return horizon, but that yields forecast future returns and growth over a much longer horizon. Finally, dividend and earnings yields exhibit high autocorrelation and strong contemporaneous relations.     

Asset Pricing with Countercyclical Household Consumption Risk

We show that shocks to household consumption growth are negatively skewed, persistent, countercyclical, and drive asset prices. We construct a parsimonious model where heterogeneous households have recursive preferences. A single state variable drives the conditional cross‐sectional moments of household consumption growth. The estimated model fits well the unconditional cross‐sectional moments of household consumption growth and the moments of the risk‐free rate, equity premium, price‐dividend ratio, and aggregate dividend and consumption growth. The model‐implied risk‐free rate and price‐dividend ratio are procyclical, while the market return has countercyclical mean and variance. Finally, household consumption risk explains the cross section of excess returns.     

There is a risk-return trade-off after all

This paper studies the intertemporal relation between the conditional mean and the conditional variance of the aggregate stock market return. We introduce a new estimator that forecasts monthly variance with past daily squared returns, the mixed data sampling (or MIDAS) approach. Using MIDAS, we find a significantly positive relation between risk and return in the stock market. This finding is robust in subsamples, to asymmetric specifications of the variance process and to controlling for variables associated with the business cycle. We compare the MIDAS results with tests of the intertemporal capital asset pricing model based on alternative conditional variance specifications and explain the conflicting results in the literature. Finally, we offer new insights about the dynamics of conditional variance.     

Forecasting stock-return variance: toward an understanding of stochastic implied volatilities

We examine the behavior of measured variances from the optionsmarket and the underlying stock market. Under the joint hypothesesthat markets are informationally efficient and that option pricesare explained by a particular asset pricing model, forecastsfrom time-series models of the stock return process should nothave predictive content given the market forecast as embodiedin option prices. Both in-sample and out-of-sample tests suggestthat this hypothesis can be rejected. Using simulations, weshow that biases inherent in the procedure we use to imply variancescannot explain this result. Thus, we provide evidence inconsistentwith the orthogonality restrictions of option pricing modelsthat assume that variance risk is unpriced. These results alsohave implications for optimum variance forecast rules.     

Models for stock returns

Historically, the normal variance model has been used to describe stock return distributions. This model is based on taking the conditional stock return distribution to be normal with its variance itself being a random variable. The form of the actual stock return distribution will depend on the distribution for the variance. In practice, the distributions chosen for the variance appear to be very limited. In this note, we derive a comprehensive collection of formulas for the actual stock return distribution, covering some sixteen flexible families. The corresponding estimation procedures are derived by the method of moments and the method of maximum likelihood. We feel that this work could serve as a useful reference and lead to improved modelling with respect to stock market returns.     

Modeling Conditional Skewness in Stock Returns

Abstract

In this paper, we propose a new GARCH-in-Mean (GARCH-M) model allowing for conditional skewness. The model is based on the so-called z distribution capable of modeling skewness and kurtosis of the size typically encountered in stock return series. The need to allow for skewness can also be readily tested. The model is consistent with the volatility feedback effect in that conditional skewness is dependent on conditional variance. Compared to previously presented GARCH models allowing for conditional skewness, the model is analytically tractable, parsimonious and facilitates straightforward interpretation.Our empirical results indicate the presence of conditional skewness in the monthly postwar US stock returns. Small positive news is also found to have a smaller impact on conditional variance than no news at all. Moreover, the symmetric GARCH-M model not allowing for conditional skewness is found to systematically overpredict conditional variance and average excess returns.     

The Equity Premium

We estimate the equity premium using dividend and earnings growth rates to measure the expected rate of capital gain. Our estimates for 1951 to 2000, 2.55 percent and 4.32 percent, are much lower than the equity premium produced by the average stock return, 7.43 percent. Our evidence suggests that the high average return for 1951 to 2000 is due to a decline in discount rates that produces a large unexpected capital gain. Our main conclusion is that the average stock return of the last half-century is a lot higher than expected.     

Regime-switching volatility of six East Asian emerging markets

This paper investigates regime-switching behaviour in the return-generating processes of six East Asian emerging stock markets over the period from 1970 to 2004 and examines the specific characteristics of each regime by utilizing Markov-switching variance models. The results show very strong evidence of more than one regime in each of these stock markets. In addition, the conditional probabilities of each regime derived from the model provide mixed evidence regarding the impact of financial liberalization on return volatility.     

Time‐Varying Risk–Return Trade‐off in the Stock Market

We uncover a strong comovement of the stock market risk–return trade‐off with the consumption–wealth ratio (CAY). The finding reflects time‐varying investment opportunities rather than countercyclical aggregate relative risk aversion. Specifically, the partial risk–return trade‐off is positive and constant when we control for CAY as a proxy for investment opportunities. Moreover, conditional market variance scaled by CAY is negatively priced in the cross‐section of stock returns. Our results are consistent with a limited stock market participation model, in which shareholders require an illiquidity premium that increases with CAY, in addition to the risk premium that is proportional to conditional market variance.     

Conditional accounting conservatism and future negative surprises: An empirical investigation

We investigate whether conditional accounting conservatism has informational benefits to shareholders. We find some evidence that higher current conditional conservatism is associated with lower probability of future bad news, proxied by missing analyst forecasts, earnings decreases, and dividend decreases. Second, we find weak evidence that the stock market reacts stronger (weaker) to good (bad) earnings news of more conditionally conservative firms. Thus, we provide additional evidence that conditional conservatism affects stock prices.     

The outperformance of family firms: the role of variance in earnings per share and analyst forecast dispersion on the Swiss market

Recent studies provide empirical evidence that family firms are outperforming their non-family counterparts in terms of stock market performance. For the Swiss stock market we find that family firms indeed outperform their non-family counterparts after controlling for firm size and beta. In addition, our data shows that family firms display more stable earnings per share in contrast to their non-family counterparts. Furthermore we find that the variance of earnings per share positively affects analyst forecast dispersion. According to anomaly literature, lower analyst forecast dispersion has been found to induce higher excess return, which our data supports for the Swiss stock market. By linking variance of earnings per share, analyst forecast dispersion and stock performance we provide an insightful explanation for the excess stock market returns of family firms. In addition, our text extends the theory of dispersion effect with an additional empirical element, the variance of earnings per share.