名义价格幻觉——基于证券分析师目标价格预测的经验证据

本文利用证券分析师发布的股票目标价格预测,为名义价格幻觉提供了能够直接反映心理预期的经验证据。研究发现,证券分析师对低价股未来收益的心理预期显著高于高价股,该行为偏误在规模小、上市时间短、股票波动性大、财务透明度低和无形资产占比高等估值难度更大的股票中表现得更加明显。我们还利用股票送转,对证券分析师是否受到名义价格幻觉的影响做进一步验证,发现由送转引起的与基本面无关的名义价格下降显著提升了证券分析师对股票未来回报的心理预期。进一步研究表明,上述发现并不是因为证券分析师准确预见了低价股和高价股未来有不同的投资机会,也不是为了最大化其供职证券公司的利益而有意迎合投资者。     

Confirming Management Earnings Forecasts, Earnings Uncertainty, and Stock Returns

In this study we examine the association among confirming management forecasts, stock prices, and analyst expectations. Confirming management forecasts are voluntary disclosures by management that corroborate existing market expectations about future earnings. This study provides evidence that these voluntary disclosures affect stock prices and the dispersion of analyst expectations. Specifically, we find that the market's reaction to confirming forecasts is significantly positive, indicating that benefits accrue to firms that disclose such forecasts. In addition, although we find no significant change in the mean consensus forecasts (a proxy for earnings expectations) around the confirming forecast date, evidence indicates a significant reduction in the mean and median consensus analyst dispersion (a proxy for earnings uncertainty). Finally, we document a positive association between the reduction of dispersion of analysts' forecasts and the magnitude of the stock market response. Overall, the evidence suggests that confirming forecasts reduce uncertainty about future earnings and that investors price this reduction of uncertainty.     

Analysts and anomalies

Analysts' price targets and recommendations contradict stock return anomaly variables. Using an index based on 125 anomalies, we find that analysts' annual stock return forecasts are 11% higher for anomaly-shorts than for anomaly-longs. Anomaly-shorts’ return forecasts are excessively optimistic, exceeding realized returns by 34%. Recommendations also tend to be more favorable for anomaly-shorts, although this result varies across anomaly types. Consistent with analysts' slowly incorporating anomaly information, anomalies forecast revisions in both price targets and recommendations. Our findings imply that investors who follow analysts' actionable information contribute to mispricing.     

Can security analyst forecasts predict gold returns?

This paper examines whether security analyst earnings forecasts for firms primarily operating in the gold market can be utilised to predict returns on the price of gold. We first demonstrate that analysts are at least in part basing their earnings forecasts for gold firms on the return expectations of the gold commodity market. We show this by providing evidence that analyst coverage impounds not only market-wide and industry information, but also gold price information for these firms — as measured via its impact on stock return synchronicity. We then examine if the difference between forecast and observed earnings for these firms has predictive value for changes in the price of gold whilst controlling for a number of macroeconomic factors. We find that this difference does hold predictive power, but also has some limitations. However, there is potential for it to be used as an additional variable within gold forecasting frameworks.     

Why Do Managers Explain Their Earnings Forecasts?

Managers often explain their earnings forecasts by linking forecasted performance to their internal actions and the actions of parties external to the firm. These attributions potentially aid investors in the interpretation of management forecasts by confirming known relationships between attributions and profitability or by identifying additional causes that investors should consider when forecasting earnings. We investigate why managers choose to provide attributions with their forecasts and whether the attributions are related to security price reactions to management earnings forecasts. Using a sample of 951 management earnings forecasts issued from 1993 to 1996, we find that attributions are more likely for larger firms, less likely for firms in regulated industries, less likely for forecasts issued over longer horizons, more likely for bad news forecasts, and more likely for forecasts that are maximum type. Furthermore, attributions are associated with greater absolute price reactions to management forecasts, more negative price reactions to management forecasts (forecast news held constant), and a greater price reaction per dollar of unexpected earnings. Our findings hold after control for the aforementioned determinants of attributions and after control for other firm‐ and forecast‐specific variables that are often associated with security prices.     

Do sell-side analysts exhibit differential target price forecasting ability?

We examine the overall and individual analyst performance of 12-month-ahead target price forecasts over the 10 years from 2000 through 2009. Implied target price-based returns exceed actual returns by an average of 15 %, and absolute target price forecast errors average 45 %. At the end of the 12-month forecast horizon, only 38 % of target prices are met, but 64 % are met at some time during the forecast horizon. We find statistically significant but economically weak evidence of persistent differential abilities by sell-side analysts to forecast target prices. Target price announcement period return analyses indicate no differential market reactions to analysts’ target price revisions conditional on their recent target price forecast performance. This finding is consistent with the market understanding that analysts have, at best, limited abilities to persistently provide accurate target price forecasts.     

Thinking about Prices versus Thinking about Returns in Financial Markets

Prices and returns are alternative ways to present information and to elicit expectations in financial markets. But do investors think of prices and returns in the same way? We present three studies in which subjects differ in the level of expertise, amount of information, and type of incentive scheme. The results are consistent across all studies: asking subjects to forecast returns as opposed to prices results in higher expectations, whereas showing them return charts rather than price charts results in lower expectations. Experience is not a useful remedy but cognitive reflection mitigates the impact of format changes.     

Cross-sectional forecasts of the equity premium

If investors are myopic mean-variance optimizers, a stock's expected return is linearly related to its beta in the cross-section. The slope of the relation is the cross-sectional price of risk, which should equal the expected equity premium. We use this simple observation to forecast the equity-premium time series with the cross-sectional price of risk. We also introduce novel statistical methods for testing stock-return predictability based on endogenous variables whose shocks are potentially correlated with return shocks. Our empirical tests show that the cross-sectional price of risk (1) is strongly correlated with the market's yield measures and (2) predicts equity-premium realizations, especially in the first half of our 1927–2002 sample.     

Earnings expectations,investor trade size,and anomalous returns around earnings announcements

We provide evidence that identifiable subsets of investors use significantly different information sets. Investors initiating large trades respond to analysts’ earnings forecast errors, while investors initiating small trades respond to a less-sophisticated signal that underestimates the implications of current earnings innovations for future earnings levels. This suggests small investors exhibit the behavior that Bernard and Thomas [Journal of Accounting and Economics 13, 305–340] theorize causes post-earnings announcement drift. We also use analysts’ forecasts to significantly improve the predictability of returns around earnings announcements previously documented by Bernard and Thomas. Finally, results attempting to link return predictability to the prevalence of small-investor trading are mixed.     

The best of all possible worlds: unraveling target price optimism using analysts’ scenario-based valuations

We document that the relative placement of analysts’ target price within their subjective distribution of scenario-based valuations for the covered firm (i.e., tilt) is informative to investors. When analysts forecast price appreciation, tilt incrementally predicts ex post valuation errors and realized returns; the predictive value of tilt disappears when analysts forecast price declines. In additional analyses, we find that tilt appears to reflect an optimistic bias in target price forecasts as opposed to information about asymmetric state-contingent risk payoffs. Finally, we document that investors can use estimates of implied tilt based on observable firm characteristics to distinguish between investments with equally optimistic target price forecasts, yet lacking scenario-based information.     

Do Analysts and Auditors Use Information in Accruals?

Existing research indicates that firms with high accruals are more likely to experience future earnings problems, but that investors' expectations, as reflected in stock prices, do not appear to anticipate these problems. In this paper, we directly examine the published opinions of two types of professional investor intermediaries to see if they provide investors with information concerning the future earnings problems experienced by firms with high accruals. First, we examine the earnings forecasts of sell-side analysts. We show that analysts' earnings forecasts do not incorporate the predictable future earnings declines associated with high accruals. Second, we examine the behavior of independent auditors. We find no evidence that auditors signal the future earnings problems associated with high accruals through either their audit opinions or through auditor changes. Overall, our evidence indicates that analysts and auditors do not alert investors to the future earnings problems associated with high accruals, thus corroborating previous findings that investors do not appear to anticipate these problems.     

Does the midpoint of range earnings forecasts represent managers’ expectations?

The accounting literature has used the midpoint of range forecasts in various research settings, assuming that the midpoint is the best proxy for managers’ earnings expectations revealed in range forecasts. We argue that given managers’ asymmetric loss functions regarding earnings surprises, managers are unlikely to place their true earnings expectations at the midpoint of range forecasts. We predict that managers’ true expectations are close to the upper bound of range forecasts. We find evidence consistent with these predictions in 1996–2010, especially in the recent decade. Despite their role as sophisticated information intermediaries, analysts barely unravel the pessimistic bias that managers embed in range forecasts. Furthermore, we find that the upper bound rather than the midpoint better represents investors’ interpretation of managers’ expectations in recent times. Our study cautions researchers to refine their research designs that use management range forecasts and sheds light on the role of financial analysts in the earnings expectations game.     

Value relevance of analyst earnings forecasts in emerging markets

Even though research in accounting and finance has extensively examined the role of financial analysts in developed economies, this issue has not been thoroughly examined in an emerging market setting. In this paper, I examine whether, following a market opening, analyst forecast accuracy and the market's reliance on analyst forecasts increase with time. Accuracy is expected to increase over time as analysts exert more effort and gain valuable forecasting experience. Results indicate that time is positively related to analyst forecast accuracy after controlling for a number of other firm and country characteristics. Second, I posit that time should also be related to the market's propensity to use analyst forecasts to form earnings expectations. As markets open and investors become more sophisticated, the reliance on analyst forecasts should also increase. Results are consistent with this expectation. In particular, I find that in the first sub-period earnings expectations based on random walk exhibit greater relative information content than earnings expectations based on analyst forecasts. This pattern is reversed in the third sub-period where analyst forecast errors better explain returns. Incremental information content tests produce similar results. Future research should further investigate the relation between financial analysts and other important market characteristics in emerging economies.     

Do management EPS forecasts allow returns to reflect future earnings? Implications for the continuation of management’s quarterly earnings guidance

Using 18,253 firm-year observations from 1998 through 2003, we build on literature suggesting that more informative disclosures allow returns to better reflect future earnings and test whether management earnings per share forecasts and their characteristics influence the future earnings response coefficient (FERC). We find that FERCs are greater for forecasting firms and when forecasts are more frequent or precise. We suggest that more frequent and more precise forecasts assist investors in better predicting future earnings. Importantly, we find that quarterly and short-term forecasts incrementally increase the association between returns and future earnings beyond annual and long-term forecasts; thus, even short-term, quarterly forecasts allow investors to form better expectations about future earnings. This suggests a benefit of quarterly earnings forecasts possibly overlooked in recommendations from the United States Chamber of Commerce, CFA Institute, Business Roundtable Institute for Corporate Ethics, and The Conference Board to eliminate quarterly earnings guidance.     

The effect of Regulation FD on the properties of management earnings forecasts

We investigate Regulation FD’s (FD) effect on management earnings forecast properties. We posit FD’s prohibition on private manager-analyst communication reduces (increases) optimism (pessimism) in management earnings forecasts. Prior to FD, managers could avoid publicly retracting prior optimistic forecasts by privately communicating with analysts, who could lower investor expectations with a new analyst forecast. After FD, managers with optimistic forecasts must either publicly admit their optimism by issuing a new management forecast or they must negatively surprise investors at the earnings announcement. Further, FD forces managers to use public forecasts instead of private communications to establish beatable expectations. Our evidence suggests FD reduced optimism in management forecasts. This reduction in optimistic bias is not offset by an increase in pessimistic bias. Consistent with this, we further find post-FD improvements in forecast accuracy and informativeness. We find no such changes around several potentially confounding events or for foreign firms surrounding FD. Overall, our evidence suggests FD improved firms’ forecast properties (less bias, greater accuracy, and greater informativeness).     

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.     

Analysis of efficient markets

A simple trading model is presented in which Bayes’ rule is used to aggregate traders’ forecasts about risky assets’ future returns. In this financial market, Bayes’ rule operates like an omnipotent market-maker performing functions that in 1776 Adam Smith attributed to an “invisible hand.” We have analyzed two distinct cases: in the first scenario, the traders’ forecast errors are uncorrelated, and in the second scenario, the traders’ forecast errors are correlated. The contribution of our paper is fourfold: first, we prove that the “efficient market” mean-return can be expressed as a complex linear combination of the traders’ forecasts. The weights depend on the forecast variances, as well as on the correlations among the traders’ forecasts. Second we show that the “efficient” variance is equal to the inverse of the sum of the traders’ precision errors, and is also related to the correlations among the traders’ forecast errors. Third, we prove that the efficient market return is the best linear minimum variance estimator (BLMVE) of the security’s mean return (in the sense that it minimizes the sum of the traders’ mean squared forecast errors). Thus, an efficient market aggregates traders’ heterogeneous information in an optimal way. Fourth, we prove that an efficient market produces a mean return (price) as a Blackwell sufficient (most informative) experiment among all possible aggregated expected return (price) forecasts.     

Forecasting the past: the case of US interest rate forecasts

This study evaluates 10-year US government bond yield forecasts and three-month US Treasury bill rate forecasts for the period between October 1989 and December 2004. In total, 136 forecast time series with approximately 13,800 forecast data were scrutinized, making this the most extensive analysis of interest rate forecasts to date. Not one of the forecast time series proved to be unbiased. In the majority of cases, information from the past was not efficiently integrated into the forecasts. The sign accuracy is significantly better than random walk forecasts in only a very few of the forecast time series. The modified Diebold–Mariano test for forecast encompassing reveals that the information content of most of the forecast time series is lower than that of the naïve forecasts, the simple ARIMA models, the implicit forward rates, or average interest rate expectations. The forecasting process is dominated by the present and past market situation.     

The accuracy of management dividend forecasts in Australia

Dividends have direct cash flow consequences for investors and are important for signalling reasons. Consequently, investors, analysts and managers typically forecast future dividends and report them in various ways. Yet the accuracy of dividend forecasts has been largely neglected in empirical finance. We examine the accuracy of managers' dividend forecasts in Australian IPO prospectuses (a companion paper examines the analysts' dividend forecasts). Managers' dividend forecasts are optimistically biased. Nevertheless, they are substantially more accurate and less biased than their earnings counterparts. Differences in retained ownership and the predictability of earnings help explain why some dividend forecasts are more accurate than others.     

Mean-variance optimization using forward-looking return estimates

Despite its theoretical appeal, Markowitz mean-variance portfolio optimization is plagued by practical issues. It is especially difficult to obtain reliable estimates of a stock’s expected return. Recent research has therefore focused on minimum volatility portfolio optimization, which implicitly assumes that expected returns for all assets are equal. We argue that investors are better off using the implied cost of capital based on analysts’ earnings forecasts as a forward-looking return estimate. Correcting for predictable analyst forecast errors, we demonstrate that mean-variance optimized portfolios based on these estimates outperform on both an absolute and a risk-adjusted basis the minimum volatility portfolio as well as naive benchmarks, such as the value-weighted and equally-weighted market portfolio. The results continue to hold when extending the sample to international markets, using different methods for estimating the forward-looking return, including transaction costs, and using different optimization constraints.