Price and Volume Reactions to Public Information Releases: An Experimental Approach Incorporating Traders' Subjective Beliefs*

This paper examines how market prices, volume, and traders' dividend expectations respond to public information releases in laboratory markets for a long-lived financial asset. The objective is to study deviations from the symmetric information risk-neutral rational expectations (RE) benchmark, which predicts no trade in such settings. The results of a series of double-auction and call markets are reported in which traders manage a portfolio of cash and asset shares over 15 rounds of trading. A public signal regarding the value of the liquidating dividend is released every third round, and traders' subjective expectations of the liquidating dividend are elicited each round as cash-motivated forecasts. We find that, despite the public dividend signal, traders' dividend forecasts are heterogeneous. Forecasts and prices both underreact to the public signals, with prices under-reacting more than forecasts. In general, price changes are not closely associated with public signals, and there is greater excess price volatility in double auctions than in call markets. Forty-three percent of trades are inconsistent with the trader's forecasts, and inconsistent trades occur more frequently in the double-auction markets. On average, approximately 10 percent of the outstanding shares are traded in each round, and trading volume is increasing in the mean absolute forecast revision and decreasing in the contemporaneous dispersion in forecasts. These results suggest that differential processing of the public signal and/or speculative trading for short-term gain may help to explain why symmetric information RE predictions are often not supported in empirical and experimental settings. They also suggest that market reactions to public information releases may be influenced by market microstructure.     

The reaction of Canadian securities to revisions of earnings forecasts*

Abstract. This first study of Canadian securities' earnings forecasts published by Institutional Brokers Estimate System (IBES) focuses on changes in the mean earnings per share forecasts of 159 to 188 companies from 1985 to 1987. Cumulative average residuals are used to detect the announcement effects of large earnings forecast revisions. The main results of this study are the following. First, an investor with access to changes of earnings per share forecasts at the beginning of the month of publication could realize abnormal excess returns. Second, trading strategies based on earnings forecasts revisions can also yield abnormal returns, but the magnitude of the revision, the sector of the company, and the month in which the revision is realized must be considered. Third, when financial analysts' forecasts are published, the informational content of large revisions in forecasts has already been discounted by the market. This result is similar to findings of U.S.– and U.K.–based studies. Finally, large forecasts revisions coincide with a period of abnormal returns. However, the information content of the announcement of forecasts changes cannot be established. The gains are larger if the trade is undertaken before the diffusion of the forecast revision to the IBES subscribers. These results do not vary with the model chosen to predict company returns. This does not necessarily indicate the existence of a market inefficiency because information acquisition and analysis costs, as well as transaction costs, may diminish considerably these abnormal trading gains.     

Investors' Misweighting of Firm-Level Information and the Market's Expectations of Earnings

Prior studies use fundamental earnings forecasts to proxy for the market's expectations of earnings because analyst forecasts are biased and are available for only a subset of firms. We find that as a proxy for market expectations, fundamental forecasts contain systematic measurement errors analogous to those in analysts' biased forecasts. Therefore, these forecasts are not representative of investors' beliefs. The systematic measurement errors from using fundamental forecasts to proxy for market expectations occur because investors misweight the information in many firm-level variables when estimating future earnings, but fundamental forecasts are formed using the historically efficient weights on firm-level variables. Thus, we develop an alternative ex ante proxy for the market's expectations of future earnings (“the implied market forecast”) using the historical (and inefficient) weights, as reflected in stock returns, that the market places on firm-level variables. A trading strategy based on the implied market forecast error, which is measured as the difference between the implied market forecast and the fundamental forecast, generates excess returns of approximately 9 percent per year. These returns cannot be explained by investors' reliance on analysts' biased forecasts. Overall, our results reveal that market expectations differ from both fundamental forecasts and analysts' forecasts.     

An Analysis of Historical and Future-Oriented Information in Accounting-Based Security Valuation Models*

The Ohlson (1995) and Feltham and Ohlson (1995) valuation model provides a rigorous framework for summarizing the information in expected future earnings and book values. However, the model provides little guidance on selecting an empirical proxy for expected future earnings. We examine whether and under what circumstances historical earnings and analyst earnings forecasts offer comparable explanation of security prices. This issue is of particular interest because analyst forecasts are less readily available than historical data. Under appropriate circumstances, historical data may allow wider use of the Feltham-Ohlson valuation model by researchers and investors. A related issue is the incremental explanatory power of historical earnings and realized future earnings (perfect-foresight forecasts) for security prices beyond analyst forecasts. If historical earnings are incrementally informative, that would suggest that analyst forecasts do not fully reflect price-relevant information in past earnings. If future earnings are incrementally informative, that would suggest that security prices reflect investors' implicit earnings forecasts beyond analyst forecasts. We examine these issues using a historical model (based on past earnings), a perfect-foresight model (based on realized future earnings), and a forecast model (based on Value Line earnings forecasts). All three models provide significant explanatory power for security prices, and each set of earnings data provides incremental explanatory power for prices when used with the other sets of earnings data. We estimate the models separately for firms with moderate and extreme earnings-to-price (E/P) ratios, a proxy for earnings permanence. For moderate-E/P firms, the historical model's explanatory power exceeds that of the perfect foresight model, and is indistinguishable from that of the analyst forecast model. In contrast, for extreme-E/P firms, the perfect-foresight model offers greater explanatory power than the historical model, but lower explanatory power than analyst forecasts. Our results suggest that financial analysts' forecasting efforts are best focused on firms whose earnings contain large temporary components (extreme E/P firms). However, in general, both historical data and analyst forecasts are complementary information sources for security valuation.     

Why Do Large Firms' Prices Anticipate Earnings Earlier than Small Firms' Prices?*

This paper presents evidence that the positive association between firm size and price leads of earnings is not solely a function of private search incentives for firm‐specific information. Specifically, we find that small‐firm prices also lag large‐firm prices with respect to industry‐wide information. Our empirical analysis extends Collins, Kothari, and Rayburn 1987 and Freeman 1987, who document that security‐price leads of earnings are positively associated with market capitalization. In particular, we examine the association between firm size and the timing of security returns for two components of annual earnings changes: the average change for a firm's industry and the firm's idiosyncratic change. We find that large firms' prices have a longer lead than small firms' prices with respect to both components. Large firms' early lead on industry‐wide earnings suggests that returns of large firms predict returns of same‐industry small firms. To test this implication, we construct a portfolio of long (short) positions in small firms when the prior month's returns of large firms in their industry are above (below) average for large firms in other industries. This zero investment portfolio earns 4.5 percent over 12 months.     

An Approach to Adjusting Analysts' Consensus Forecasts for Selection Bias*

Many recent empirical studies have concluded that analysts' earnings forecasts are optimistic on average. In this paper, we attempt to undo the effect of one potential source of optimistic bias in analysts' earnings forecasts. Assuming forecasts come from a truncated normal distribution, we estimate the “true” population mean using maximum likelihood. We find that our estimates of earnings are more accurate and less biased than standard measures of sample mean and median. However, we do not find a closer relationship between excess market returns and forecast errors from our maximum likelihood estimate than from the sample mean. This may suggest that the market does not fully incorporate analysts' incentives in generating expectations about future earnings.     

Reciprocity information and wage personalization

This paper considers a modified principal-agent environment, where principals can use personalized offers based on agents' reciprocity-related information. With such information, principals can either impose stronger financial incentives or try to “trigger” agents' positive reciprocity by offering a higher fixed rate. Theory suggests that principals who believe in agents' reciprocity would personalize offers so that reciprocal agents increase their effort beyond the self-regarding benchmark. Using a lab experiment, we test the behavior of principals and agents. Our experimental market witnesses significant wage personalization when reciprocity information is available. However, agents' effort levels and principals' payoffs are lower under wage personalization, compared with the sessions where principals cannot personalize offers. Our structural analysis shows that, under wage personalization, agents expect higher fixed wages and reciprocate higher wages less. Information about agents' individual reciprocity is more correlated with the expected wages, rather than the strength of reciprocity toward higher or lower wages. Principals grant higher fixed wages to workers with lower wage expectations, but because principals cannot personalize offers effectively according to the strength of reciprocity, the performance of wage personalization is limited.     

Valuation Implications of Unconditional Accounting Conservatism: Evidence from Analysts' Target Prices

We examine whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism affects reported earnings, conservatism per se does not have an effect on the present value of future cash flows. We examine whether analysts adjust for the effect of conservatism included in their earnings forecasts when using these forecasts to estimate target prices. We find that signed target price errors (actual minus forecast) have a significant positive association with the degree of conservatism in forward earnings, suggesting that target prices are biased due to accounting conservatism. Cross‐sectional analysis suggests that more sophisticated analysts and superior long‐term forecasters adjust for conservatism to a greater extent than other analysts. In additional analyses, we explore the mechanism through which conservatism leads to bias in target prices. We first show that analysts' earnings forecasts are negatively associated with the degree of conservatism; that is, analysts include the effect of unconditional conservatism in their earnings forecasts. Based on alternative earnings‐based valuation models that analysts may use, our evidence suggests that analysts fail to appropriately adjust their valuation multiple for the effect of conservatism included in their earnings forecasts when using these forecasts to derive target prices. As a consequence, we find that, for extreme changes in conservatism, the bias in analysts' target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that analysts may not appreciate the valuation implications of conservative accounting which could inhibit price discovery.     

Investor Overreaction to Earnings Surprises and Post‐Earnings‐Announcement Reversals

Prior literature suggests that the market underreacts to the positive correlation in a typical firm's seasonal earnings changes, which leads to a post‐earnings‐announcement drift (PEAD) in prices. We examine the market reaction for a distinct set of firms whose seasonal earnings changes are uncorrelated and show that the market incorrectly assumes that the earnings changes of these firms are positively correlated. We also document that positive (negative) seasonal earnings changes in the current quarter are associated with negative (positive) abnormal returns in the next quarter. Thus, we observe a reversal of abnormal returns, consistent with a systematic overreaction to earnings, rather than the previously documented PEAD. Additional analysis indicates that financial analysts similarly overestimate the autocorrelation of these firms, although to a lesser extent. We also find that the magnitude of overestimation and the subsequent price reversal are inversely related to the richness of the information environment. Our results challenge the notion that investors recognize but consistently underestimate earnings correlation and provide a new perspective on the inability of prices to fully reflect the implications of current earnings for future earnings. That is, we show that investors predictably overestimate correlation when it is lacking, but underestimate it when it is present.     

Consensus,dispersion et prix des titres*

Résumé. Cette étude établit et teste, dans un cadre d'équilibre d'anticipations rationnelles bruité, l'existence d'une relation linéaire formelle entre le prix des titres, la moyenne (le consensus) et la dispersion des anticipations des agents. Les variations de la moyenne et de la dispersion des anticipations des agents, mesurées par les prévisions de bénéfices réalisées par les analystes financiers transmises par I/B/E/S, ont respectivement un effet positif et négatif sur le prix des titres. Les difficultés soulevées par cette estimation, ainsi que les dimensions institutionnelles de l'industrie de l'analyse financière sont examinées. Les principaux résultats sont les suivants: 1) les variations les plus importantes du consensus (en valeur absolue) correspondent aux variations les plus importantes (en valeur absolue) de la dispersion des prévisions d'analystes, 2) les changements dans le consensus et la dispersion des prévisions sont respectivement liés positivement et négativement aux rendements des actions canadiennes mais en raison du décalage entre la réalisation et la diffusion des prévisions, une part importante de l'ajustement de prix a lieu avant la diffusion publique des changements dans les prévisions, 3) l'effet des variations du consensus sur le rendement des titres domine l'effet des variations de la dispersion des prévisions. Il semble donc que l'impact de l'arrivée d'information sur le prix des titres ne dépende pas uniquement du sens et de l'ampleur de la révision moyenne des anticipations, mais aussi du sens et de l'ampleur du changement dans la dispersion des anticipations.     

Horizon‐Dependent Underreaction in Financial Analysts' Earnings Forecasts*

This paper provides empirical evidence that underreaction in financial analysts' earnings forecasts increases with the forecast horizon, and offers a rational economic explanation for this result. The empirical portion of the paper evaluates analysts' responses to earnings‐surprise and other earnings‐related information. Our empirical evidence suggests that analysts' earnings forecasts underreact to both types of information, and the underreaction increases with the forecast horizon. The paper also develops a theoretical model that explains this horizon‐dependent analyst underreaction as a rational response to an asymmetric loss function. The model assumes that, for a given level of inaccuracy, analysts' reputations suffer more (less) when subsequent information causes a revision in investor expectations in the opposite (same) direction as the analyst's prior earnings‐forecast revision. Given this asymmetric loss function, underreaction increases with the risk of subsequent disconfirming information and with the disproportionate cost associated with revision reversal. Assuming that market frictions prevent prices from immediately unraveling these analyst underreac‐tion tactics, investors buying (selling) stock on the basis of analysts' positive (negative) earnings‐forecast revisions also benefit from analyst underreaction. Therefore, the asymmetric cost of forecast inaccuracy could arise from rational investor incentives consistent with a preference for analyst underreaction. Our incentives‐based explanation for underreaction provides an alternative to psychology‐based explanations and suggests avenues for further research.     

Evidence that Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings: An Experimental Markets Approach*

Abstract. Analysts have been found to underweight the innovation in the most recent quarterly earnings when forecasting next-quarter earnings, and these expectations have been posited as an explanation for post-earnings-announcement drift. This study uses an experimental asset market to examine whether similar errors in forecasting quarterly earnings are made by student-subjects. We examine two aspects of their behavior: (1) do subjects underestimate the autocorrelation in quarterly earnings when forming earnings expectations? and (2) are asset prices consistent with a subject's underestimation of the autocorrelation in quarterly earnings? We observe subject errors in forecasts that underweight extreme innovations in the most recent quarterly earnings by approximately 40 percent. The prices in the experimental markets also fail to reflect fully the most recent innovation in quarterly earnings. We are able to predict the sign of the incorrect pricing, from the mean initial earnings predictions of the subjects, in 74 percent of the 135 markets. These forecast errors observed in this study are consistent with forecast errors observed for analysts, and this consistency suggests that errors in analysts' forecasts may be at least partially attributable to the use of judgmental heuristics.     

Financial Statement Complexity and Meeting Analysts’ Expectations

We examine whether firms with greater financial statement complexity are more likely to meet or beat analysts’ earnings expectations. We proxy for financial statement complexity using the firm's industry and year adjusted accounting policy disclosure length. Firms with more complex financial statements are more likely to just beat expectations than just miss expectations. Firms with complex financial statements appear to use expectations management to beat expectations, but do not use earnings management. Corroborating these findings, we find analysts rely more on management guidance for more complex firms. Firms with complex financial statements are also more likely to have analysts exclude items from actual “street earnings,” but tests suggest this strategy is not specifically used by complex firms to beat expectations. The effect we document is specific to analyst forecasts and not to other alternative benchmarks.     

Do Monetary Policy Announcements Affect Exchange Rate Returns and Volatility of Returns? Some Evidence from High‐Frequency Intra‐Day South African Data

This paper examines the temporal effect of domestic monetary policy surprises on both returns and volatility of returns of the South African rand/U.S. dollar exchange rate. The analysis in this “event study” proceeds using intra‐day minute‐by‐minute exchange rate data, repo rate data from the South African Reserve Bank's scheduled monetary policy announcements, and market consensus repo rate forecasts. A carefully selected sample over the period August 2003 to November 2017 ensures that the change in monetary policy is exogenous to the exchange rate. We find statistically and economically significant responses in intra‐day high‐frequency South African rand/U.S. dollar exchange rate returns and volatility of exchange rate returns to domestic interest rate surprises, but anticipated changes have no bearing on exchange rate returns and their volatility. The empirical results also indicate that there is an instantaneous response of the rand/dollar exchange rate to monetary policy surprises and that monetary policy news is an important determinant of the exchange rate until at least 42 minutes after the pronouncement – suggesting a high degree of market “efficiency” in its mechanical sense (although not necessarily in the deeper economic‐informational sense) in processing this information. Essentially, the asymmetric GARCH results exhibit no leverage effects – positive and negative information shocks have symmetric effects on conditional variance.     

The Effect of Limited Liability on the Informativeness of Earnings: Evidence from the Stock and Bond Markets*

Previous empirical research on the informativeness of earnings has focused on stockholders, and has not examined differences in earnings' informativeness for stockholders and bondholders. Because stockholders are residual claimants and bondholders are fixed claimants, the informativeness of earnings should differ for these two types of investors. When a firm's default risk is low, changes in its financial condition should be of limited relevance to bondholders, but should be relevant to stockholders. In contrast, as the likelihood of financial distress increases, stockholders' limited liability allows them to abandon the firm to the bondholders (Fischer and Verrecchia 1997). Accordingly, as a firm's default risk increases, changes in its financial condition should be increasingly important to bondholders and less important to shareholders. Because earnings provide information on firm value, the stock return-earnings association should decrease as the firm's financial strength declines, while the bond return-earnings association should increase. We use two measures of a firm's financial strength: the firm's bond rating and its reporting of a loss. Consistent with our hypotheses, we find that the association between stock returns and changes in annual earnings decreases as bond ratings decline, while the association between bond returns and changes in annual earnings increases. These results suggest that as the company's financial condition deteriorates, earnings become less relevant for stock valuation and more relevant for bond valuation. When we partition firms based on their loss status, we find a stronger association between stock returns and annual earnings changes for firms with positive earnings (profit firms) than for firms with losses, consistent with earlier studies. In contrast, we find that the association between bond returns and earnings changes is greater for loss firms than for profit firms. These results suggest that losses reduce the informativeness of earnings for stockholders but increase informativeness for bondholders, suggesting that investors view losses as indicating increased credit risk.     

The Incremental Informativeness of Stock Prices for Future Accounting Earnings*

This study extends previous research that documents a stock price reaction leading accounting earnings. The primary issue is that prior studies use a naive earnings expectation model (random walk) as the benchmark for the information content of lagged returns and do not adequately address the “incremental” information content of lagged returns. This study identifies and estimates firm-specific models of earnings to control directly for the autocorrelation in earnings. The explanatory power of lagged prices with respect to this earnings residual is investigated using both a multiple regression model of lagged returns and a multiple time-series vector autoregressive model. In-sample estimation of the models provides clear evidence that stock prices impound information about future earnings incremental to the information contained in historical earnings data. Holdout period analysis of the earnings forecasts from these lagged return models finds that both models outperform the naive seasonal random walk expectation, but neither model outperforms the more sophisticated Box-Jenkins forecasts. On an individual firm basis, earnings forecasts supplemented with the lagged return data tend to be less precise than the Box-Jenkins forecasts, but the price-based models demonstrate an ability to rank the earnings forecast errors from the time-series models. The analysis helps to characterize the limitations of lagged returns as a means of predicting future earnings innovations.     

A Re-Examination of Financial Analysts' Differential Earnings Forecast Accuracy*

Abstract. This research re-examines whether there are differences in the forecast accuracy of financial analysts through a comparison of their annual earnings per share forecasts. The comparison of analyst forecast accuracy is made on both an ex post (within sample) and an ex ante (out of sample) basis. Early examinations of this issue by Richards (1976), Brown and Rozeff (1980), O'Brien (1987), Coggin and Hunter (1989), O'Brien (1990), and Butler and Lang (1991) were ex post and suggest the absence of analysts who can provide relatively more accurate forecasts over multiple years. Contrary to the results of prior research and consistent with the belief in the popular press, we document that differences do exist in financial analysts' ex post forecast accuracy. We show that the previous studies failed to find differences in forecast accuracy due to inadequate (or no) control for differences in the recency of forecasts issued by the analysts. It has been well documented in the literature that forecast recency is positively related to forecast accuracy (Crichfield, Dyckman, and Lakonishok 1978; O'Brien 1988; Brown 1991). Thus, failure to control for forecast recency may reduce the power of tests, making it difficult to reject the null hypothesis of no differences in forecast accuracy even if they do exist. In our analysis, we control for the differences in recency of analysts' forecasts using two different approaches. First, we use an estimated generalized least squares estimation procedure that captures the recency-induced effects in the residuals of the model. Second, we use a matched-pair design whereby we measure the relative forecast accuracy of an analyst by comparing his/her forecast error to the forecast error of another randomly selected analyst making forecasts for the same firm in the same year on or around the same date. Using both approaches, we find that differential forecast accuracy does exist amongst analysts, especially in samples with minimum forecast horizons of five and 60 trading days. We show that these differences are not attributable to differences in the forecast issuance frequency of the financial analysts. In sum, after controlling for firm, year, forecast recency, and forecast issuance frequency of individual analysts, the analyst effect persists. To validate our findings, we examine whether the differences in the forecast accuracy of financial analysts persist in holdout periods. Analysts were assigned a “superior” (“inferior”) status for a firm-year in the estimation sample using percentile rankings on the distribution of absolute forecast errors for that firm-year. We use estimation samples of one- to four-year duration, and consider two different definitions of analyst forecast superiority. Analysts were classified as firm-specific “superior” if they maintained a “superior” status in every year of the estimation sample. Furthermore, they were classified as industry-specific “superior” if they were deemed firm-specific “superior” with respect to at least two firms and firm-specific “inferior” with respect to no firm in that industry. Using either definition, we find that analysts classified as “superior” in estimation samples generally remain superior in holdout periods. In contrast, we find that analysts identified as “inferior” in estimation samples do not remain inferior in holdout periods. Our results suggest that some analysts' earnings forecasts should be weighted higher than others when formulating composite earnings expectations. This suggestion is predicated on the assumption that capital markets distinguish between analysts who are ex ante superior, and that they utilize this information when formulating stock prices. Our study provides an ex ante framework for identifying those analysts who appear to be superior. When constructing weighted forecasts, a one-year estimation period should be used because we obtain the strongest results of persistence in this case.     

The Use of Trade Association Disclosures by Investors and Analysts: Evidence from the Semiconductor Industry*

This paper investigates the relation between industry-wide information disclosures by the trade association for the semiconductor industry and both share prices and analyst forecasts. Such disclosures may have little impact on investors and analysts, since prior theoretical research suggests that trade associations may be unable to secure reliable data from firms in an industry. At the same time, such disclosures may be important, since prior empirical research suggests that share prices and analyst forecasts reflect industry-wide earnings effects earlier than firm-specific effects. We document significant stock price movements on release dates of industry Flash Reports by the Semiconductor Industry Association (SIA) each month that contain aggregate industry data on new orders and shipments. The magnitude of the price revisions on Flash Report disclosure dates is positively associated with changes in the numbers disclosed and varies across sample firms in a manner associated with identifiable characteristics of the firms. Further tests indicate that the Flash Report provides mainly forward-looking information on new orders that is linked to firm-specific sales changes and has explanatory power for quarterly stock prices beyond firm-specific earnings. This information is used by security analysts mainly in assessing the persistence of firm-specific quarterly sales changes. Our findings support the hypothesis that the SIA is able to obtain data from firms, compile it into reliable aggregate statistics, and then distribute these statistics in a timely fashion.     

Inflation and Inflation Expectations in South Africa: an Attempt at Explanation

This paper examines the relationship between inflation and inflation expectations in South Africa. We use inflation expectations derived from the quarterly surveys conducted by the Bureau of Economic Research from 2001Q1 to 2011Q4 . Using these data, we estimate the model assuming that private sector expectations are a linear function of the inflation target and lagged inflation. The results indicate that economic agents' expectations largely depend on lagged inflation. This suggests that the South African Reserve Bank (SARB) has not been successful in anchoring expectations of the private sector since the adoption of the inflation targeting (IT) regime in 2000. We also find evidence indicating that the SARB's implicit inflation target lies above the upper bound of the official IT band. Finally, it appears that the SARB has been more concerned about output stabilisation than inflation stabilisation.     

Using climate models to improve Indonesian food security

El Niño Southern Oscillation (ENSO) events exert significant influence on Southeast Asian rice output and markets. This paper measures ENSO effects on Indonesia's national and regional rice production and on world rice prices, using the August Niño 3.4 sea surface temperature anomaly (SSTA) to gauge climate variability. It shows that each degree Celsius change in the August SSTA produces a 1,318,000 metric ton effect on output and a $21/metric ton change in the world price for lower quality rice. Of the inter-annual production changes due to SSTA variation, 90% occur within 12 provinces, notably Java and South Sulawesi. New data and models offer opportunities to understand the agricultural effects of ENSO events, to reach early consensus on coming ENSO effects, and to use forecasting to improve agencies' and individuals' capacity to mitigate climate effects on food security. We propose that Indonesia hold an ‘ENSO summit’ each September to analyse the food-security implications of upcoming climate events.