A liquidity-augmented capital asset pricing model

Using a new measure of liquidity, this paper documents a significant liquidity premium robust to the CAPM and the Fama–French three-factor model and shows that liquidity is an important source of priced risk. A two-factor (market and liquidity) model well explains the cross-section of stock returns, describing the liquidity premium, subsuming documented anomalies associated with size, long-term contrarian investment, and fundamental (cashflow, earnings, and dividend) to price ratios. In particular, the two-factor model accounts for the book-to-market effect, which the Fama–French three-factor model fails to explain.     

Are good-news firms riskier than bad-news firms?

This paper examines the relative risk of good-news firms, i.e., those with high standardized unexpected earnings (SUE), and bad-news (low SUE) firms using a stochastic discount factor approach. We find that a stochastic discount factor constructed from a set of basis assets helps explain post-earnings-announcement drift (PEAD). The risk exposures on the pricing kernel increase monotonically from the lowest to highest SUE sorted portfolios. Specifically, good-news firms always have higher risk exposures than bad-news firms in both 10 SUE sorted portfolios and 25 size and SUE sorted portfolios. However, the estimated expected risk premium is too small to explain the observed magnitude of returns on the PEAD strategy. Our risk adjustment can explain only about one-fourth of the total magnitude of the average realized return to the PEAD strategy. As a result, the average risk-adjusted returns of earnings momentum strategies are mostly positive and significant. Overall, our results support the view that at least some portion of the returns to the earnings momentum strategies examined represent compensation for bearing increased risk.     

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.      

Extreme downside risk and expected stock returns

We propose a measure for extreme downside risk (EDR) to investigate whether bearing such a risk is rewarded by higher expected stock returns. By constructing an EDR proxy with the left tail index in the classical generalized extreme value distribution, we document a significantly positive EDR premium in cross-section of stock returns even after controlling for market, size, value, momentum, and liquidity effects. The EDR premium is more prominent among glamor stocks and when high market returns are expected. High-EDR stocks are generally characterized by high idiosyncratic risk, large downside beta, lower coskewness and cokurtosis, and high bankruptcy risk. The EDR premium persists after these characteristics are controlled for. Although Value at Risk (VaR) plays a significant role in explaining the EDR premium, it cannot completely subsume the EDR effect.     

The disparity between long-term and short-term forecasted earnings growth

We find the disparity between long-term and short-term analyst forecasted earnings growth is a robust predictor of future returns and long-term analyst forecast errors. After adjusting for industry characteristics, stocks whose long-term earnings growth forecasts are far above or far below their implied short-term forecasts for earnings growth have negative and positive subsequent risk-adjusted returns along with downward and upward revisions in long-term forecasted earnings growth, respectively. Additional results indicate that investor inattention toward firm-level changes in long-term earnings growth is responsible for these risk-adjusted returns.     

Analyst characteristics, timing of forecast revisions, and analyst forecasting ability

We first examine whether analysts with certain characteristics that prior research has identified are related to superior forecasting ability systematically time their forecast revisions later in the fiscal quarter. We then examine whether this superior ability persists after controlling for the timing advantage by using relative forecast error, a measure that largely eliminates the timing advantage of recent forecasts. Using a sample of quarterly earnings forecast revisions over the 20-year period from 1990 to 2009, we find that analysts with more firm-specific and general experience and more accurate prior-period forecasts, analysts employed by larger brokerage firms, and analysts who follow fewer industries and companies tend to revise forecasts later in the quarter. We also find that analyst characteristics that are positively correlated with revision timing are negatively related to relative forecast errors. These results are consistent with analyst characteristics being useful proxies for analyst forecasting ability and analysts with greater ability revising forecasts later in the quarter.     

The informativeness of analyst forecast revisions and the valuation of R&D-intensive firms

Prior studies (e.g., [McNichols and O’Brien, 1997] and [Diether et al., 2002]) find that analysts are less willing to disclose unfavorable earnings forecasts than to disclose favorable forecasts, and this tendency induces an optimistic bias in disclosed forecasts that increases with the degree of earnings uncertainty. Building on these findings, we predict that, in the context of R&D-intensive industries, there should be differential informativeness and asymmetric valuation roles for upward versus downward analyst forecast revisions. Consistent with our predictions, we find the following evidence: (i) analyst forecast revisions contain a downward bias, causing upward revisions to under-represent, whereas downward revisions to over-represent, changes in true earnings expectations, with the extent of over/under-representation greater for firms with higher R&D expenditures; (ii) upward revisions are associated with more rapid reductions in earnings uncertainties (proxied by forecast dispersions) than downward revisions, mainly for high R&D firms; and (iii) upward revisions are more effective in mitigating the return differentials between high and low R&D firms (as documented in Chan et al., 2001).     

The cross section of cashflow volatility and expected stock returns

I show that historical cashflow volatility is negatively related to future returns cross-sectionally. The negative association is large; economically meaningful; long-lasting up to five years; robust to known return-informative effects of size, value, price and earnings momentums and illiquidity; and extends to both systematic and idiosyncratic cashflow volatilities. Using the standard deviations of cashflow to sales and of cashflow to book equity as proxies for cashflow volatility, the least volatile decile portfolio outperforms the most volatile decile portfolio by 13% a year relative to the Fama–French four factors. The cashflow volatility effect is closely related to the idiosyncratic return volatility effect documented in Ang et al. [Ang, A., Hodrick, R.J., Xing, Y. and Zhang, X. “The cross-section of volatility and expected returns.” Journal of Finance, 51 (2006), 259–299.]. However, in portfolios simultaneously sorted on both cashflow and return volatilities, and in cross sectional regressions of returns at the firm level, these two effects neither drive out nor dominate each other. While the pricing of idiosyncratic cashflow volatility represents an anomaly against the traditional asset pricing theories, the pricing of historical cashflow uncertainty sheds light on potential fundamental risks embodied in the Fama–French HML and SMB factors.     

Analyst Forecasts and the Cross Section of European Stock Returns

We examine revisions to earnings forecasts by equity analysts and their role in predicting stock returns. We provide evidence that European stocks with net upward revised forecasts earn higher future returns than otherwise similar stocks. This effect is not concentrated in small stocks, stocks with low analyst coverage, or stocks with low book‐to‐market ratios. We find differences in the return continuation patterns of stocks with upward versus downward revisions, namely, bad news travels quickly, but good news travels slowly. This result is consistent with investors' attaching greater significance to poor earnings forecasts, but adopting a wait‐and‐see approach to good news.     

Analyst versus model-based earnings forecasts: implied cost of capital applications

We find that a composite implied cost of capital (ICC) estimate – based on the earnings forecasts generated by cross-sectional models – is highly correlated with future realised returns in both portfolio- and regression-based tests. By contrast, we find very little evidence for an association with future realised returns for an ICC estimate based on analyst earnings forecasts. We also document the time-varying nature of expected returns and risk premia, and provide up-to-date estimates of an implied Australian market risk premium.     

Effect of Analysts' Optimism on Estimates of the Expected Rate of Return Implied by Earnings Forecasts

Recent literature has used analysts' earnings forecasts, which are known to be optimistic, to estimate implied expected rates of return, yielding upwardly biased estimates. We estimate that the bias, computed as the difference between the estimates of the implied expected rate of return based on analysts' earnings forecasts and estimates based on current earnings realizations, is 2.84%. The importance of this bias is illustrated by the fact that several extant studies estimate an equity premium in the vicinity of 3%, which would be eliminated by the removal of the bias. We illustrate the point that cross‐sample differences in the bias may lead to the erroneous conclusion that cost of capital differs across these samples by showing that analysts' optimism, and hence, bias in the implied estimates of the expected rate of return, differs with firm size and with analysts' recommendation. As an important aside, we show that the bias in a value‐weighted estimate of the implied equity premium is 1.60% and that the unbiased value‐weighted estimate of this premium is 4.43%.     

Disagreement and asset prices

How do differences of opinion affect asset prices? Do investors earn a risk premium when disagreement arises in the market? Despite their fundamental importance, these questions are among the most controversial issues in finance. In this paper, we use a novel data set that allows us to directly measure the level of disagreement among Wall Street mortgage dealers about prepayment speeds. We examine how disagreement evolves over time and study its effects on expected returns, return volatility, and trading volume in the mortgage-backed security market. We find that increased disagreement is associated with higher expected returns, higher return volatility, and larger trading volume. These results imply that there is a positive risk premium for disagreement in asset prices. We also show that volatility in and of itself does not lead to higher trading volume. Instead, only when disagreement arises in the market is higher uncertainty associated with more trading. Finally, we are able to distinguish empirically between two competing hypotheses regarding how information in markets gets incorporated into asset prices. We find that sophisticated investors appear to update their beliefs through a rational expectations mechanism when disagreement arises.     

Analyst Earnings Forecast Revisions and the Pricing of Accruals

We investigate the relation between two market anomalies to provide insights into analysts role as information intermediaries. Prior research finds that accruals and analyst earnings forecast revisions predict future returns. We find that the accrual and forecast revision strategies generate hedge returns of 15.5% and 5.5% when implemented independently. Strikingly, a combined strategy that uses forecast revisions to refine the accrual strategy generates a hedge return of 28.5%. Firms with consistent accrual and forecast revision signals have less persistent accruals and earnings. We also find that accruals can be used to refine the forecast revision strategy—high accruals are associated with overoptimism in analyst forecasts. Our findings indicate that although forecast revisions reflect information about accrual and earnings persistence beyond that reflected in the level of current year accruals, investors do not fully incorporate this information into their valuation assessments.     

Market uncertainty and the importance of media coverage at earnings announcements

We investigate whether increased investor demand for financial information arising from higher market uncertainty leads to greater media coverage of earnings announcements. We also investigate whether greater coverage during times of higher uncertainty further destabilizes financial markets because of greater attention-based trading or, alternatively, improves trading and pricing by lowering investor acquisition and interpretation costs. When uncertainty is higher, we find evidence of greater media coverage of earnings announcements and that the greater coverage leads to improvements in investor informedness, information asymmetry, and intraperiod price timeliness, and greater trade by both retail and institutional investors. In contrast to the media serving an expanded role in improving capital markets during more uncertain times, we fail to find that changes in firm-initiated disclosures lead to similar improvements and find that less frequent analyst forecast revisions exacerbate problems in capital markets during earnings announcements.     

Analysts’ estimates of the cost of equity capital

We explore a large sample of analysts' estimates of the cost of equity capital (CoE) to evaluate their usefulness as expected return proxies (ERP). We find that the CoE estimates are significantly related to a firm's beta, size, book-to-market ratio, leverage, and idiosyncratic volatility but not other risk proxies. Even after controlling for the popular return predictors, the CoE estimates incrementally predict future stock returns. This predictive ability is better explained as the CoE estimates containing ERP information rather than reflecting stock mispricing. When evaluated against traditional ERPs, including the implied costs of capital, the CoE estimates are found to be the least noisy. Finally, we document CoE responses around earnings announcements, demonstrating their usefulness to study discount-rate reactions of market participants. We conclude that analysts' CoE estimates are meaningful ERPs that can be fruitfully employed in a variety of asset pricing contexts.     

On the test of the correction mechanism for mis-pricing between assets using a statistical yield spread model

This paper investigates the existence of a correction mechanism for mis-pricing between Japanese stock and bond. By this correction mechanism we mean that when deviations occur from the equilibrium levels of the expected return differentials between stock and bond — the risk premium differentials, the market will tend to correct the mis-pricing and bring the expected return differentials back to the equilibrium levels. We assume that the yield spread between the predicted earnings price ratio of stock and the yield to maturity of bond reflects the risk premium between stock and bond, and estimate the equilibrium risk premium differentials and mis-prices between stock and bond by modelling their behaviors with a statistical yield spread model (SYS). Empirical results strongly indicate the existence of the mis-pricing correction mechanism, suggesting the inefficiency of securities markets.     

The effect of repeat restructuring charges on analysts’ forecast revisions and accuracy

The primary objective of this study is to examine the effect of prior restructuring charges on analyst forecast revisions and accuracy. We find evidence that analysts respond differently to first-time restructuring firms than to repeat restructuring firms. Analysts revise their forecasts of both one-year-ahead earnings and five-year long-term growth in earnings more negatively for first-time restructuring firms than for firms with prior charges. When we examine forecast errors in the year subsequent to the restructuring, we find that current charges complicate analysts’ earnings forecast task. We further find that the decline in analyst forecast accuracy is mitigated by prior charges within past two years.     

The intertemporal relation between expected returns and risk

This paper explores the time-series relation between expected returns and risk for a large cross section of industry and size/book-to-market portfolios. I use a bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model to estimate a portfolio's conditional covariance with the market and then test whether the conditional covariance predicts time–variation in the portfolio's expected return. Restricting the slope to be the same across assets, the risk-return coefficient is highly significant with a risk–aversion coefficient (slope) between one and five. The results are robust to different portfolio formations, alternative GARCH specifications, additional state variables, and small sample biases. When conditional covariances are replaced by conditional betas, the risk premium on beta is estimated to be in the range of 3% to 5% per annum and is statistically significant.     

The earnings announcement premium around the globe

U.S. stocks have been shown to earn higher returns during earnings announcement months than during non-announcement months. We document that this earnings announcement premium exists across the globe. Moreover, it is not isolated to a few countries. Of the 20 countries with enough data to conduct a within-country analysis, nine exhibit a significantly positive premium. A cross-country analysis finds that the premium is strongest in countries with the greatest increase in idiosyncratic volatility around the time of their firms' earnings announcements, suggesting that uncertainty over the earnings information to be disclosed is a primary driver of the global announcement premium.     

An examination of the effects of management earnings forecast form and explanations on financial analyst forecast revisions

Using a sample of 978 quarterly management earnings-per-share forecasts made during the period 1993 to 1999, we document that financial analyst revisions to management earnings forecasts are a function of management forecast form. More precise forecasts (measured three different ways) lead to greater revision of financial analyst consensus EPS forecasts for a given level of unexpected earnings as predicted by Kim and Verrecchia (1991) and Bayesian adjustment models. Also, consistent with our arguments, maximum forecasts are interpreted as bad news by analysts. Our results, while consistent with theory, are inconsistent with recent experimental studies which do not reject the null hypothesis of no effect of management earnings forecast form on the association between unexpected earnings and financial analyst forecast revisions. We also re-examine Baginski, Hassell, and Kimbrough's (2004) finding that attributions used to explain management forecasts affect the reaction to the forecast using analyst data. Consistent with their findings using stock prices, the attribution presence (especially external attributions) increases financial analyst revisions pursuant to management forecasts.