Do Decomposed Financial Ratios Predict Stock Returns and Fundamentals Better?

We investigate the prediction of excess returns and fundamentals by financial ratios, which include dividend‐price ratios, earnings‐price ratios, and book‐to‐market ratios, by decomposing financial ratios into a cyclical component and a stochastic trend component. We find both components predict excess returns and fundamentals. Cyclical components predict increases in future stock returns, while stochastic trend components predict declines in future stock returns in long horizons. This helps explain previous findings that financial ratios in the absence of decomposition find weak predictive power in short horizons and some predictive power in long horizons. We also find both components predict fundamentals.     

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.     

Shiller's CAPE: Market Efficiency and Risk

Robert Shiller shows that Cyclically Adjusted Price to Earnings Ratio (CAPE) is strongly associated with future long‐term stock returns. This is often interpreted as evidence of market inefficiency. We present two findings contrary to such an interpretation. First, if markets are efficient, stock returns should be higher than the risk‐free rate. We find that even when CAPE is in its ninth decile, future 10‐year stock returns, on average, are higher than future returns on 10‐year U.S. Treasurys. Thus, the results are largely consistent with market efficiency. Second, consistent with a risk–return tradeoff, we find that CAPE is negatively associated with future stock market volatility.     

Currency devaluation and stock market response: An empirical analysis

We study local stock market reaction to currency devaluation by a country's central bank. Devaluations appear to be anticipated by the local stock markets, and there are significant negative abnormal returns even one year prior to the announcement of the devaluation. A negative trend in stock returns persists for up to one quarter following the first announcement, and then becomes positive thereafter, suggesting a reversal. We explore whether changes in macroeconomic variables prior to currency devaluations are related to abnormal stock returns. We find that stock returns are significantly lower if the devaluation is larger and if the country is a developing nation. Furthermore, stock markets decline more around devaluations if reserves are lower, if the real exchange rate has depreciated over the prior years, if the capital account has declined, if the current account deficit has gone up, or if the country credit rating has deteriorated.     

Stock Returns and Operating Performance of Securities Issuers

We examine long‐run stock returns and operating performance around firms’ offerings of common stock, convertible debt, and straight debt from 1985 to 1990. We find that pre‐issue abnormal returns are positive and significant for stock issuers, but not for convertible and straight debt issuers. The post‐issue mean returns show that common stock and convertible debt issuers experience underperformance during the post‐issue periods, but straight debt issuers do not. Consistent with these results, common stock issuers experience the best pre‐issue operating performance among all three types of issuers, and operating performance declines during the post‐issue periods for common stock and convertible debt issuers. Using a new approach in linear model estimations to correct heteroskedasticity and to adjust for finite sample, we find a positive relation between post‐issue operating performance and issue‐period stock price reactions. The results suggest that future operating performance is anticipated at the issue and that securities issues provide information on issuers’ future performance.     

The pricing of firms with expected losses/profits: The role of January

We examine the role of January in the relation between expected losses/profits and future stock returns. We predict and find that the relation between expected losses/profits and future returns reverses from the usual positive relation in non‐January months to a negative one in January. The reverse January relation is consistent across sample years, is observed in the United States and international markets, and is incremental to other variables associated with January returns. At least part of the reverse January relation is explained by tax‐loss selling. Further analysis shows that the reverse January relation results in a temporary price drift away from fundamental value. In other words, we find that abnormal positive (negative) future returns do not always indicate past under(over)valuation. Overall, our results illustrate the importance of controlling for the effect of January when examining how investors price expected losses/profits.     

Discretionary accruals: signalling or earnings management in Australia?

We investigate the signalling effect of discretionary accruals (DAC). Although we find that discretionary accruals are insignificantly related to contemporaneous stock returns, we uncover that income‐increasing discretionary accruals of GAAP‐complying growth firms are significantly and positively related to contemporaneous stock returns. Furthermore, we find that this positive effect is stronger among firms with better corporate governance mechanisms, such as Board of Directors Independence, Audit Committee Independence and Large Shareholders’ Ownership. In addition to contemporaneous stock returns, we also find similar results with the future increase in dividends. Our findings are consistent with the argument that corporate governance can enhance the signalling effect of reported earnings of GAAP‐complying growth firms.     

On the Stability of the Cross‐Section of Expected Stock Returns in the Cross‐Section: Understanding the Curious Role of Share Turnover

In this paper, we shed further light on cross‐sectional predictors of stock return performance. Specifically, we explore whether the cross‐section of expected stock returns is robust within stock groups sorted by past monthly return. We find that the book/market and momentum effects are remarkably robust to sorting on past returns. However, share turnover is negatively related to future returns for stocks with abnormally low stock price performance in the recent past, but postively related to returns for well‐performing stocks. This casts doubt on the use of turnover as a liquidity proxy, but is consistent with turnover being a proxy for momentum trading which pushes prices in the direction of past price movements. Our results are robust to both NYSE/AMEX and Nasdaq stocks, and also robust to stratifying the sample by time period.     

A STATE‐SPACE MODEL OF SHORT‐ AND LONG‐HORIZON STOCK RETURNS

In this article we propose a new parsimonious state‐space model in which state variables characterize the stochastic movements of stock returns. Using the equally weighted and decile monthly stock returns, we show that (a) a parsimonious state‐space model characterizes the variation in expected returns at any horizon; (b) the extracted expected returns explain a substantial proportion of the variance in realized returns, and the magnitude of this proportion increases significantly with the horizon of returns; (c) the model successfully captures the empirical fact that returns of smaller firms have both stronger positive autocorrelations of short‐horizon returns and stronger negative autocorrelations of long‐horizon returns; and (d) the forecasts of asset returns obtained with the state‐space model subsume the information in other potential predictor variables such as dividend yields. JEL classification: G10, G12.     

Reversal and momentum patterns in weekly stock returns: European evidence

We analyze short‐term reversal and medium‐term momentum patterns in weekly stock returns in Europe. Focusing on raw and stock‐specific returns, our empirical results show for both return specifications (a) a negative relation between weekly past returns and future returns in the short run and (b) a positive relation in the medium run. However, returns from reversal and momentum strategies based on stock‐specific returns are less volatile. In further analyses, we find short‐term reversal and medium‐term momentum patterns to be connected to stock characteristics. Looking at the potential causes of these effects, our results do not support the idea that short‐term reversal in weekly stock returns is due to an over‐ or underreaction to firm‐specific news nor that it is mainly driven by illiquidity. Medium‐term momentum in weekly stock returns, on the other hand, can be connected to behavioral biases. Our concluding tests confirm that our findings are robust among industries, in subperiods, for the January effect and in varying market states. Finally, while medium‐term momentum strategies remain profitable after accounting for transaction costs, short‐term reversal strategies can be mainly explained by transaction costs due to their high turnover.     

Information content of credit ratings in pricing of future earnings

This paper examines whether credit ratings convey information about the firm’s future earnings to the capital markets. Using the future earnings response coefficient methodology, we find that the current stock returns of rated firms reflect more future earnings than do the stock returns of non-rated firms. We also find that the market reflect more future earnings in current returns for higher-rated firms. In addition, we present evidence that returns impound future earnings to a greater extent after a ratings initiation or upgrade. We empirically eliminate the possibility that our findings are driven by earnings smoothing, market liquidity or omitted default risk factors associated with ratings. Our results are robust to controlling for potential omitted variables, endogeneity bias, loss versus profit firms, and serial correlation of error terms. Overall, the evidence suggests that credit ratings help disseminate private information to reduce information uncertainty about the firm’s future profitability among market participants.     

Do stock bulletin board systems (BBS) contain useful information? A viewpoint of interaction between BBS quality and predicting ability

This study explores whether information on internet stock bulletin board systems (BBS) is valuable for stock return prediction, taking advantage of data derived from the biggest stock BBS in China. Using a text classification algorithm, we find the online messages significantly predict stock return with negligible R‐squared. However, we find that accuracy of individual BBS posts is below 50 percent and there is no distinction at prediction accuracy between high‐ and low‐quality stock BBS. Due to the autocorrelation of stock returns, we argue that BBS predicts stock returns because of its reflection on the simultaneous stock return rather than revelation on valuable information.     

Tax Expense Momentum

We investigate the joint hypothesis that (1) tax expense contains information about core profitability that is incremental to reported earnings and (2) that information is reflected in stock prices with a delay. We find that seasonally differenced quarterly tax expense, our proxy for tax expense surprise, is related positively to future returns. This anomaly is separate from previously documented pricing anomalies based on financial and tax variables. Additional investigation reveals that tax expense surprise is related positively to changes in future quarterly earnings and tax expense, and both those future changes are related positively to future returns. While the returns to investing in predictable future earnings changes has been documented before, these results suggest that predicting changes in future tax expense also generates incremental future returns.     

On the predictability of Chinese stock returns

We examine stock return predictability in China. We take 18 firm-specific variables that have been documented to predict cross-sectional stock returns in the U.S. and examine their relation with stock returns in China for the sample period from 1995 to 2007. We find relatively weak predictability for Chinese stocks. Only five firm-specific variables predict returns in the Chinese market. Tests on U.S. stock returns find that more predictors can explain cross-sectional stock return variation. We test two explanations for the cause of weak returns predictability in China. First, perhaps return predictors in China are less heterogeneously distributed than they are in the U.S. Second, stock prices are less informative in China than they are in the U.S. We find support for both explanations.     

Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies

We examine the influence of US, UK and German macroeconomic and financial variables on the stock returns of two relatively small, open European economies, Ireland and Denmark. Within a nonlinear framework, we allow for time variation via regime switching using a smooth transition regression (STR) model. We find that US (global) and UK and German (regional) stock returns are significant determinants of returns in both markets. Further, global information represented by oil and US asset price movements drive changes between states in each market. Significantly, the role of country‐specific domestic variables is typically confined to a single state while global and regional variables pervade all states.     

The Usefulness of Book-to-Market and ROE Expectations for Explaining UK Stock Returns

Abstract:  The fundamental valuation perspective on stock returns suggests that book-to-market will be positively related to returns if market value of equity equals future expected cash flows discounted at the expected return and book value proxies for future cash flows. Building on this perspective, we develop a log linear model which includes expectations of future BM and ROE in addition to current BM as explanatory variables for future stock returns. We show that these three variables explain a significant part of UK cross-sectional stock returns and that they remain highly statistically significant after including additional risk proxy variables. This supports relevance of fundamental valuation based firm characteristics for explaining stock returns and indicates their potential usefulness for predicting future stock returns.     

What Moves Investment Growth?

We use accounting identities to decompose unexpected changes in investment growth into surprises to current cash‐flow growth and stock returns, and revisions of expectations about future cash‐flow growth and future discount rates. Using a vector autoregressive model we find that current cash‐flow surprises account for the largest element of the variance decomposition. Investment growth and current cash‐flow surprises are negatively correlated with news about future cash‐flow growth, which can be expected from persistent productivity shocks and decreasing returns to scale. We find little evidence of a discount rate channel for investment since return terms are small and have unintuitive signs.     

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.     

High Idiosyncratic Volatility and Low Returns: A Prospect Theory Explanation

The well‐documented negative relationship between idiosyncratic volatility and stock returns is puzzling if investors are risk‐averse. However, under prospect theory, while investors are risk‐averse in the domain of gains, they exhibit risk‐seeking behavior in the domain of losses. Consistent with risk‐seeking investors’ preference for high‐volatility stocks in the loss domain, we find that the negative relationship between idiosyncratic volatility and stock returns is concentrated in stocks with unrealized capital losses, but is nonexistent in stocks with unrealized capital gains. This finding is robust to control for short‐term return reversals and maximum daily return, among other variables.     

Causal and Dynamic Relationships among Stock Returns,Return Volatility and Trading Volume: Evidence from Emerging markets in South-East Asia

This paper examines the causal and dynamic relationships among stock returns, return volatility and trading volume for five emerging markets in South-East Asia—Indonesia, Malaysia, Philippines, Singapore and Thailand. We find strong evidence of asymmetry in the relationship between the stock returns and trading volume; returns are important in predicting their future dynamics as well as those of the trading volume, but trading volume has a very limited impact on the future dynamics of stock returns. However, the trading volume of some markets seems to contain information that is useful in predicting future dynamics of return volatility.