Signaling safety

Contrary to signaling models’ central predictions, changes in the level of cash flows do not empirically follow changes in dividends. We use the Campbell (1991) decomposition to construct cash-flow and discount-rate news from returns and find the following: (1) both dividend changes and repurchase announcements signal changes in cash-flow volatility (in opposite directions); (2) larger cash-flow volatility changes come with larger announcement returns; and (3) neither discount-rate news, nor the level of cash-flow news, nor total stock return volatility change following dividend changes. We conclude cash-flow news—and not discount-rate news—drive payout policy, and payout policy conveys information about future cash-flow volatility.     

The cross-section of equity returns and assets’ fundamental cash-flow risk

The decomposition of consumption beta into a component driven by assets’ cash-flow news and one related to assets’ discount-rate news reveals that macroeconomic risks embodied in cash flows largely account for the cross-sectional dynamics of average stock returns. Empirically, we find that differences in expected excess returns between low book-to-market and high book-to-market portfolios are associated with differences in their cash-flow betas, and thus reflect macroeconomic, especially consumption-related risks. This result holds true for a broad set of consumption-based asset pricing models. In addition, the results indicate that the risk premium on equity markets is primarily driven by the exposure of assets’ cash-flow components to the cyclical variability of durable consumption goods.     

Explaining Returns with Cash-Flow Proxies

Stock returns are correlated with contemporaneous earnings growth,dividend growth, future real activity, and other cash-flow proxies.The correlation between cash-flow proxies and stock returnsmay arise from association of cash-flow proxies with one-periodexpected returns, cash-flow news, and/or expected-return news.We use Campbell’s (1991) return decomposition to measurethe relative importance of these three effects in regressionsof returns on cash-flow proxies. In some of the popular specifications,variables that are motivated as proxies for cash-flow news alsotrack a nontrivial proportion of one-period expected returnsand expected-return news. As a result, the R² from a regressionof returns on cash-flow proxies may overstate or understatethe importance of cash-flow news as a source of return variance.     

What Drives Firm‐Level Stock Returns?

I use a vector autoregressive model (VAR) to decompose an individual firm's stock return into two components: changes in cash-flow expectations (i.e., cash-flow news) and changes in discount rates (i.e., expected-return news). The VAR yields three main results. First, firm-level stock returns are mainly driven by cash-flow news. For a typical stock, the variance of cash-flow news is more than twice that of expected-return news. Second, shocks to expected returns and cash flows are positively correlated for a typical small stock. Third, expected-return-news series are highly correlated across firms, while cash-flow news can largely be diversified away in aggregate portfolios.     

Earnings forecasts and idiosyncratic volatilities

We test the theoretical relation between idiosyncratic return volatilities and the volatilities of cash-flow news based on the expected returns on equity (ROE) for CRSP stocks over the period 1977–2008. Consistent with economic intuition, we find that using analyst forecasts of earnings is superior to using realized earnings to proxy for market expectations about future cash flow news. Our findings are consistent with a market where stock return volatilities are positively and asymmetrically related to changes in the volatilities of expectations for a fundamental driver of cash flow news (ROE). Our findings are robust after correcting for forecast biases, various fundamental variables, newly-listed and mature firms, and periods with and without earnings announcements.     

Stock returns,aggregate earnings surprises,and behavioral finance

We study the stock market's reaction to aggregate earnings news. Prior research shows that, for individual firms, stock prices react positively to earnings news but require several quarters to fully reflect the information in earnings. We find a substantially different pattern in aggregate data. First, returns are unrelated to past earnings, suggesting that prices neither underreact nor overreact to aggregate earnings news. Second, aggregate returns correlate negatively with concurrent earnings; over the last 30 years, for example, stock prices increased 5.7% in quarters with negative earnings growth and only 2.1% otherwise. This finding suggests that earnings and discount rates move together over time and provides new evidence that discount-rate shocks explain a significant fraction of aggregate stock returns.     

Aggregate insider trading: Contrarian beliefs or superior information?

We decompose realized market returns into expected return, unexpected cash-flow news and unexpected discount rate news to test the relation between aggregate market returns and aggregate insider trading. We find that (1) the predictive ability of aggregate insider trading is much stronger than what was reported in earlier studies, (2) aggregate insider trading is strongly related to unexpected cash-flow news, (3) market expectations do not cause insider trading contrary to what others have documented, and (4) aggregate insider trading in firms with high information uncertainty is more likely to be associated with contrarian investment strategy. These results strongly suggest that the predictive ability of aggregate insider trading is because of insider’s ability to predict future cash-flow news rather than from adopting a contrarian investment strategy. These results hold even after we control for non-informative trades and information uncertainty.     

Explaining the default risk anomaly by the two-beta model

This study attempts to explain the anomaly that firms with high-default risk earn low average realized returns. We measure default risk according to Ohlson's (1980) O-score and Campbell, Hilscher, and Szilagyi's (2008) failure probability and further implement Duffie, Saita, and Wang's (2007) doubly-stochastic intensity model to estimate default probabilities that incorporate the dynamics of the changes in covariates. We then employ Campbell and Vuolteenaho's (2004) two-beta model to estimate firms' cash-flow and discount-rate betas according to the default risk. The default risk anomaly persists when using Duffie el al.'s (2007) method. We show that cash-flow and discount-rate betas, respectively, earn a high and low premium and find that high-default firms tend to have relatively high discount-rate and low cash-flow betas. Hence, high-default firms deliver low expected returns. Importantly, 25.5% of the default risk anomaly can be explained by the two-beta model and that, on average, also accounts for 49.2% of the cross-sectional variation across the portfolios formed on default risk. This result implies that investors believe that high-default firms are unlikely to generate significantly extra cash flows when market-wide profitable opportunities improve.     

Short sales,institutional investors and the cross-section of stock returns

Short-sale constraints are most likely to bind among stocks with low institutional ownership. Because of institutional constraints, most professional investors simply never sell short and hence cannot trade against overpricing of stocks they do not own. Furthermore, stock loan supply tends to be sparse and short selling more expensive when institutional ownership is low. Using institutional ownership as a proxy, I find that short-sale constraints help explain cross-sectional stock return anomalies. Specifically, holding size fixed, the under-performance of stocks with high market-to-book, analyst forecast dispersion, turnover, or volatility is most pronounced among stocks with low institutional ownership. Ownership by passive investors with large stock lending programs partly mitigates this under-performance, indicating some impact of stock loan supply. Prices of stocks with low institutional ownership also underreact to bad cash-flow news and overreact to good cash-flow news, consistent with the idea that short-sale constraints hold negative opinions off the market for these stocks.     

Modeling the Conditional Covariance Between Stock and Bond Returns: A Multivariate GARCH Approach

To analyze the intertemporal interaction between the stock andbond market returns, we assume that the conditional covariancematrix follows a multivariate GARCH process. We allow for asymmetriceffects in conditional variances and covariances. Using dailydata, we find strong evidence of conditional heteroskedasticityin the covariance between stock and bond market returns. Theresults indicate that not only variances, but also covariancesrespond asymmetrically to return shocks. Bad news in the stockand bond market is typically followed by a higher conditionalcovariance than good news. Cross asymmetries, that is, asymmetriesfollowed from shocks of opposite signs, appear to be importantas well. Covariances between stock and bond returns tend tobe relatively low after bad news in the stock market and goodnews in the bond market. A financial application of our modelshows that optimal portfolio shares can be substantially affectedby asymmetries in covariances. Moreover, our results show sizablegains due to asymmetric volatility timing.     

The decomposition of US and Euro area stock and bond returns and their sensitivity to economic state variables

This paper decomposes US and Euro area excess stock and bond return innovations into news factors using the Campbell–Schiller methodology. The results indicate that stock return volatility is mostly due to volatility of future excess return news. Inflation news plays a minor role although it is significantly correlated with excess return innovations. For the bond market too, it is future return news—not inflation news—that moves bond returns most. For finite investment horizons, however, asset market movements give a differential importance to the various news components. Results are comparable for the US and the Euro area, but differ in terms of magnitudes. In addition, sensitivities (‘betas’) to a set of state variables are estimated, yielding high interest rate betas and low money growth betas. Generally, inflation, unemployment and leading indicator betas are significant. Asset market exposures to oil and exchange rate changes are more significant for the Euro area than in the US.     

Stock Market Returns and Economic Fundamentals in an Emerging Market: The Case of Korea

This paper investigates the feedback relationship between stock market returnsand economic fundamentals in an emerging market. Starting from an intertemporalconsumption-based CAPM (CCAPM), we obtain a restricted VAR model for stockreturns and macroeconomic variables. We then apply this model to Korea and findstatistically significant departures from the restrictions implied by CCAPM.Consequently, an unrestricted VAR model is used to analyze the variations of expectedand unexpected returns in the Korean stock market. It is shown that the expectedmarket returns vary with a set of macroeconomic variables, and that thepredictable component is substantial. Reflecting richer dynamics in the data,relative to the usual single equation modeling in the literature, the estimatedVAR model shows considerable predictive ability for both real economic activityand real returns. Using the model for a variance decomposition of unexpectedreturns, we find that, although we cannot directly observe the market's revisionof expected future dividend growth, we can estimate a large part of therevision with the news in the expected industry output growth from our VAR model.Finally, we also find that economic fundamentals can explain only a smallportion of the variation in unexpected returns in the Korean stock market.     

Do Accruals Drive Firm‐Level Stock Returns? A Variance Decomposition Analysis

This paper extends the variance decomposition framework of Campbell [1991], Campbell and Ammer [1993], and Vuolteenaho [2002] to address the relative value relevance of accrual news, cash flow news, and expected-return news in driving firm-level equity returns. The extension is based on the Feltham-Ohlson [1995, 1996] clean surplus relations. Using three models, this study shows that all three factors, accruals, cash flows, and expected future discount rates are value relevant. Moreover, accrual news is found to significantly dominate expected-return news in driving firm-level stock returns. Operating income news is also found to significantly dominate both expected-return news and free cash flow news in driving firm-level stock returns. Furthermore, after splitting net income into cash flow and accrual earnings components in the Vuolteenaho model, accrual earnings news and cash flow earnings news are found to equally drive firm-level stock returns and to dominate expected-return news. Further disaggregation of the data yields some evidence that accrual earnings news is a more important factor than cash flow earnings news in driving current stock returns. Overall, the three models indicate that changes in expected future accruals are a primary driver, if not the primary driver, of current stock returns.     

Turn-of-the-month and intramonth effects in government bond markets: Is there a role for macroeconomic news?

This paper focuses on the turn-of-the-month (TOM) and intramonth anomalies in government bond returns. In particular, we examine whether the TOM and intramonth effects exist in government bond markets, and moreover, whether these anomalies are related to the release of macroeconomic news as suggested in recent stock market studies. Using data on the 2-year and 10-year US Treasury Notes and German government bonds, we document a modest TOM effect in government bond returns. This effect does not disappear after controlling for the release of macroeconomic announcements, thereby suggesting that the origin of the TOM effect is not necessarily the same across asset classes.     

Macro news and stock returns in the Euro area: A VAR-GARCH-in-mean analysis

This paper analyses the effects of newspaper coverage of macro news on stock returns in eight countries belonging to the euro area (Belgium, France, Germany, Greece, Ireland, Italy, Portugal and Spain) using daily data for the period 1994–2013. The econometric analysis is based on the estimation of a VAR-GARCH-in-mean model. The results can be summarised as follows. Positive (negative) news have significant positive (negative) effects on stock returns in all cases. Their volatility has a significant impact on both stock returns and volatility; specifically, an increase in news volatility is always associated with a decrease in stock returns. Markets are particularly responsive to negative news, and the reaction is bigger in the PIIGS countries, and during the recent crisis period.     

Relations Between Stock Returns and Fundamental Variables: Evidence from a Segmented Market

This study examines relations between stock returns and potential explanatory factors in Korea, an important and segmented emerging market. Our results show that Korean stock returns in general and returns on stocks listed in Section 1 in particular are significantly positively related to book-to-market, sales-price, and debt-equity ratios, but not significantly related to market value of equity. Returns on stocks listed in Section 2 are, however, negatively related to market value of equity and not significantly related to the other three variables. Among the variables investigated by us, book-to-market ratio has the greatest explanatory power for stock returns and it indicates superior returns for value stocks. Our findings strengthen the international evidence of the role of book-to-market ratio in explaining stock returns by demonstrating its significance even in the segmented Korean market.     

Stock returns and macro risks: Evidence from Finland

Deviations from the CAPM have generally been observed for the stock markets. One of many alternative approaches is using macro variables as systematic risks. We tested with a number of macro risks for the explanation of Finnish industry returns for a period from 1993:03 until 2008:07. The evidence suggests macro risks explain larger cross-sectional variations in average industry returns than the market factor alone and same is reported with the Hansen and Jagannathan (1997) specification measure. The changes in expected returns with a positive shock in the exchange rate risk and unanticipated inflation remain economically persistent for the post euro period, arguably a sign for the regulatory impact of the coordinated policies from European central bank (ECB). The robustness checks show the prevalence of macro risks, and market risk cannot be ignored altogether.     

STOCK MARKET REACTION TO GOOD AND BAD INFLATION NEWS

This article shows that differentiating between good and bad inflation news is important to understanding how inflation affects stock market returns. Summing positive and negative inflation shocks as in previous studies tends to wash out or mute the effects of inflation news on stock returns. More specifically, we find that, depending on the economic state, positive and negative inflation shocks can produce a variety of stock market reactions. We conclude that the effect of inflation on stock returns is conditional on whether investors perceive inflation shocks as good or bad news in different economic states.     

Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets

This paper examines empirical contemporaneous and causal relationships between trading volume, stock returns and return volatility in China's four stock exchanges and across these markets. We find that trading volume does not Granger-cause stock market returns on each of the markets. As for the cross-market causal relationship in China's stock markets, there is evidence of a feedback relationship in returns between Shanghai A and Shenzhen B stocks, and between Shanghai B and Shenzhen B stocks. Shanghai B return helps predict the return of Shenzhen A stocks. Shanghai A volume Granger-causes return of Shenzhen B. Shenzhen B volume helps predict the return of Shanghai B stocks. This paper also investigates the causal relationship among these three variables between China's stock markets and the US stock market and between China and Hong Kong. We find that US return helps predict returns of Shanghai A and Shanghai B stocks. US and Hong Kong volumes do not Granger-cause either return or volatility in China's stock markets. In short, information contained in returns, volatility, and volume from financial markets in the US and Hong Kong has very weak predictive power for Chinese financial market variables.     

Exchange rates,interventions, and the predictability of stock returns in Japan

Using monthly Japanese data for the period 1991–2005, we examined the link between exchange rate movements and stock returns. We found that exchange rate movements per se do not help to explain stock returns. There is, however, evidence of in-sample predictability if one accounts for the interventions of the Japanese monetary authorities in the foreign exchange market. This evidence does not indicate a violation of market efficiency insofar as investors cannot use information on interventions to systematically improve the performance of simple trading rules based on out-of-sample forecasts of stock returns.