The Role of Media for Inflation Forecast Disagreement of Households and Professional Forecasters

This paper investigates the effects of media coverage about consumer price inflation on inflation forecast disagreement of German households and professional forecasters. We adopt a Bayesian learning model in which media coverage of inflation affects forecast disagreement by influencing information sets as well as predictor choice. Our empirical results show that disagreement of households depends on the heterogeneity of story content and on the reporting intensity, especially of news on rising inflation. Disagreement of professional forecasters does not depend on media coverage. With respect to the influence of macroeconomic variables, we provide evidence that disagreement of professional forecasters primarily depends on the inflation rate and on inflation volatility. The response of households to inflation is much less pronounced.     

News on Inflation and the Epidemiology of Inflation Expectations

This paper examines the nexus between news coverage on inflation and households’ inflation expectations. In doing so, we test the epidemiological foundations of the sticky information model (Carroll 2003, 2006 ). We use both aggregate and household‐level data from the Survey Research Center at the University of Michigan. We highlight a fundamental disconnection among news on inflation, consumers’ frequency of expectation updating, and the accuracy of their expectations. Our evidence provides at best weak support to the epidemiological framework, as most of the consumers who update their expectations do not revise them toward professional forecasters’ mean forecast.     

Analyst underreaction and the post-forecast revision drift

The post-forecast revision drift (PFRD), the phenomenon of delayed stock price reactions to analyst forecast revisions, is a well-documented market anomaly. Prior research attributes PFRD to underreaction by investors to analyst forecast revisions. This study investigates the role of the analyst forecast revision process itself in the PFRD anomaly. Using a large sample of US firms, we confirm prior findings of a positive serial correlation (momentum) in individual analysts’ revisions to their earnings forecasts and, based on both indirect and direct tests, document a positive association between this momentum and PFRD. Further analyses reveal that both the forecast revision momentum and PFRD vary in similar ways with respect to the nature of the news driving the revisions and the information environment. Collectively, our findings show that underreaction by individual analysts in the forecast revision process is an important contributor to the PFRD phenomenon.     

Disagreement and Biases in Inflation Expectations

Disagreement in inflation expectations observed from survey data varies systematically over time in a way that reflects the level and variance of current inflation. This paper offers a simple explanation for these facts based on asymmetries in the forecasters' costs of over- and underpredicting inflation. Our model implies (i) biased forecasts, (ii) positive serial correlation in forecast errors, (iii) a cross-sectional dispersion that rises with the level and the variance of the inflation rate, and (iv) predictability of forecast errors at different horizons by means of the spread between the short- and long-term variance of inflation. We find empirically that these patterns are present in inflation forecasts from the Survey of Professional Forecasters. A constant bias component, not explained by asymmetric loss and rational expectations, is required to explain the shift in the sign of the bias observed for a substantial portion of forecasters around 1982.     

Information interpretation or information discovery: which role of analysts do investors value more?

This study provides evidence that a significant percentage of analyst forecast revisions are issued promptly after a broad set of corporate public disclosures and that investors perceive these prompt revisions as more valuable than nonprompt revisions. These results hold for all revisions, revisions outside of the earnings announcement window, or revisions in weeks preceding the earnings announcements and are also robust to various sensitivity tests. Investors particularly value analysts?? prompt interpretation of earnings announcements, Form 8-K filings, or certain qualitative news. To the extent that prompt revisions are more likely to reflect analysts?? information interpretation role, our results suggest that investors value more highly analysts?? ability to interpret public disclosures, especially less structured or non-financial disclosures, than their ability for information discovery.     

New evidence on price impact of analyst forecast revisions

Previous research shows a positive relationship between consensus forecast revisions and stock returns in developed markets. We obtain new evidence from four major Asia-Pacific markets that suggest that abnormal returns are related to latest forecast revisions. The price impact of negative revisions is consistently stronger than that of the positive revisions. We also found considerable differences in price impact between developed and emerging markets for positive revisions, while no such difference is detected for negative revisions. The latest forecast revisions and category of analysts (those working in international broking firms) appear to be two key determinants of abnormal stock returns.     

R&D Shocks and News Shocks

Most of the theoretical work in the news shock literature abstracts away from structural explanations, assuming instead that news is a pure signal giving agents advance notice that aggregate technology will undergo exogenous change at some future point. This paper proposes that a surprise improvement in sector‐specific productivity in the research and development sector can be seen as news about aggregate productivity. I not only offer a deeper explanation for the news but also show that the model performs modestly better in matching empirical facts than a standard, one‐sector neoclassical growth model augmented with exogenous news shocks does.     

Do Macroforecasters Herd?

We show that typical tests of whether forecasters herd will falsely indicate herding behavior for a variety of types of behavior and forecasting environments that give rise to disagreement among forecasters. We establish that forecasters will appear to herd if differences between them reflect noise as opposed to private information, or if they arise from informational rigidities. Noise can have a behavioral interpretation and if so will depend on the behavioral model under consideration. An application of the herding tests to U.S. quarterly survey forecasts of inflation and output growth data 1981–2013 does not support herding behavior.     

The Impact of Analysts' Forecast Errors and Forecast Revisions on Stock Prices

Abstract:  We present a comprehensive analysis of the association between stock returns, quarterly earnings forecast errors, and quarter-ahead and year-ahead earnings forecast revisions. We find that forecast errors and the two forecast revisions have significant effects on stock prices, indicating each conveys information content. Findings also show that the fourth quarter differs from other quarters—the relative importance of the forecast error (quarter-ahead forecast revision) is lower (higher). We also find a marked upward shift over time in the forecast error and forecast revision coefficients, consistent with the I/B/E/S database reflecting an improved quality of both earnings forecasts and actual earnings.     

On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies

This paper provides a full characterization of inflation rate forecasts using the mean values from Consensus Economics for a sample of 78 advanced and emerging economies between 1989 and 2014. It also assesses the performance of inflation rate forecasts around business cycles’ turning points. As expected, that inflation forecasts start to mirror the actual data as the forecast horizon draws to a close, particularly in advanced economies. The mean forecast error is positive and larger than one point when we pool all countries, but this masks inter-group differences. Moreover, we find evidence for biasedness, inefficiency or information rigidities, with a clear tendency for “forecast smoothing”. Accounting for cross-country informational linkages is important: forecasters fail to adjust their inflation forecasts quick enough in response to domestic news and news from abroad. Finally, during recession episodes forecasts generally appear to be inefficient. The same holds true for recoveries.     

Information aggregation around macroeconomic announcements: Revisions matter

I show that an empirical relation exists between stock returns on macroeconomic news announcement days and the future revisions of the released data but that this link differs across the business cycle. Using three major macroeconomic series that undergo significant revisions (nonfarm payroll, gross domestic product, and industrial production), I present evidence that daily returns on the Standard & Poor's 500 index and revisions are positively related in expansions and negatively related in recessions. The results suggest that revisions do matter, i.e., that investors care about the final revised value of a macroeconomic series, that they infer accurate information from the release of the preliminary inaccurate report, and that the more precise information is aggregated into prices on the day of the initial announcement. The results are consistent with the predictions of rational expectations trading models around public announcements combined with well-established empirical results on the asymmetric interpretation of information across the business cycle.     

Survey forecasts in Brazil: A prismatic assessment of epidemiology,performance, and determinants

This paper assesses the behavior of survey forecasts in Brazil during the inflation targeting regime, when managing expectations is one of the cornerstones of the conduct of monetary policy. The distinctive database of the survey conducted by the Central Bank of Brazil (BCB) among professional forecasters allows for a thorough investigation of the epidemiology, determinants, and performance of forecasts. The main results are: i) top performing forecasters are influential to other forecasters; ii) survey forecasts perform better than vector autoregressive model-based forecasts; iii) common forecast errors prevail over idiosyncratic components across respondents; iv) inflation targets play an important role in inflation expectations; and v) agents perceive the BCB as following a Taylor rule consistent with inflation targeting. The last two suggest high credibility of the monetary authority.     

The sensitivity of the credit default swap market to financial analysts’ forecast revisions

We examine the impact of analysts’ earnings per share (EPS) and cash flow per share (CPS) forecast revisions on the market for credit default swaps. We find that while the issuance of both EPS and CPS forecast revisions are inversely associated with changes in credit default swap (CDS) spreads, cash flow forecast revisions have a larger effect. We demonstrate that the relationship between CPS forecast revisions and CDS spreads tends to be stronger in cases of financial distress. We provide evidence that cash flow forecasts dominate earnings forecasts in some situations and that participants in the CDS market discriminate between analysts' forecast revisions and recommendation changes.     

Effects of Preannouncements on Analyst and Stock Price Reactions to Earnings News

This study examines the effects of earnings preannouncements on financial analyst and stock price reactions to earnings news. Prior experimental research documents that when the signs of a preannouncement surprise and subsequent earnings announcement surprise are consistent (i.e., both either positive or negative), analysts make larger magnitude revisions to their future period earnings forecasts in response to the total earnings news conveyed in the preannouncement and earnings announcement than when the surprise signs are inconsistent. This study extends this research by examining a sample of actual preannouncements from 1993–1997 to determine whether the effects documented in laboratory settings manifest at the aggregate market level in stock prices and consensus analyst forecast revisions. Results indicate that after controlling for the sign of earnings news, sign of earnings, and sign of the earnings announcement surprise, stock prices and analyst forecast revisions respond more strongly when a preannouncement and subsequent earnings announcement elicit the same surprise signs than when the surprise signs are inconsistent. Further analysis indicates that the consistency of the signs of a preannouncement surprise and earnings announcement surprise is not associated with future earnings, suggesting that the magnified reaction of investors and analysts to consistent surprise signs is not a rational reaction to associations observed in market settings.     

Accounting earnings and gross domestic product

We document that aggregate accounting earnings growth is an incrementally significant leading indicator of growth in nominal Gross Domestic Product (GDP). Professional macro forecasters, however, do not fully incorporate the predictive content embedded in publicly available accounting earnings data. As a result, future nominal GDP growth forecast errors are predictable based on accounting earnings data that are available to professional macro forecasters in real time.     

Top investment banks,confirmation Bias,and the market pricing of forecast revisions

We investigate the impact of top investment banks (hereafter top IBs) on the pricing of forecast revisions through the investors' attention channel by examining the distraction effect and confirmation bias theories. The distraction effect theory predicts that investors' attention shifts to consensus revisions that align with revisions from top IBs, resulting in inattention to other revisions. This theory implies that top IBs primarily benefit investors by directing them to high-quality revisions. In contrast, the confirmation bias theory predicts that top IBs magnify market reaction to forecast revisions and benefit investors by partially offsetting investors' initial underreaction to revisions. Our findings indicate the presence of confirmation bias. We further examine the potential effects of the information content of revisions, analyst agreement, news sentiment, and information uncertainty to test the robustness of our results. Our findings suggest that top IBs ultimately contribute to the price discovery process by attracting investors' attention and this effect does not channel through the quality of consensus revisions.     

Investor and (Value Line) Analyst Underreaction to Information about Future Earnings: The Corrective Role of Non-Earnings-Surprise Information

Prior research suggests that financial analysts' earnings forecasts and stock prices underreact to earnings news. This paper provides evidence that analysts and investors correct this underreaction in response to the next earnings announcement and to other (non-earnings-surprise) information available between earnings announcements. Our evidence also suggests that analysts and investors underreact to information reflected in analysts' earnings forecast revisions and that non-earnings-surprise information helps correct this underreaction as well. Controlling for corrective non-earnings-surprise information significantly increases estimates of the degree to which analysts' forecasting behavior can explain drifts in returns following both earnings announcements and analysts' earnings forecast revisions.     

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.     

An Empirical Analysis of Qualitative Management Earnings Forecasts

Despite efforts by the Securities and Exchange Commission (SEC) to encourage corporate disclosure of quantitative management earnings projections, only a small fraction of firms voluntarily do so. Instead of quantitative estimates, a large number of firms choose to disclose qualitative (verbal) assessments of their earnings prospects. This paper is a study of the information characteristics and the usefulness of this alternative form of forecast disclosure to investors. The study examines a sample of qualitative forecast statements from the 1979–1985 period and finds associations between these forecasts and percentage changes in realized earnings per share, the direction of financial analysts' forecast revisions following the disclosure of these forecasts, and abnormal stock returns on the date of their disclosure. These associations are, however, shown to be more significant for negative (bad news) than for positive (good news) forecasts.     

Can News Be a Major Source of Aggregate Fluctuations? A Bayesian DSGE Approach

We examine whether the news shocks, as explored in Beaudry and Portier (2004) , can be a major source of aggregate fluctuations. For this purpose, we extend a standard dynamic stochastic general equilibrium model of Christiano, Eichenbaum, and Evans (2005) and Smets and Wouters (2003, 2007) by allowing news shocks on the total factor productivity (TFP), and estimate the model using Bayesian methods. Estimation results on the U.S. and Japanese economies suggest that (i) news shocks play a relatively more important role in the United States than in Japan, (ii) a news shock with a longer forecast horizon has larger effects on nominal variables, and (iii) the overall effect of the TFP on hours worked becomes ambiguous in the presence of news shocks.