Range has it: decoding the information content of forecast ranges

ABSTRACT: Previous studies concerning the relative accuracy of management and financial analyst earnings forecasts have produced conflicting conclusions. Resolving this conflicting evidence is important because of the role relative accuracy potentially plays in such issues as the imposition of mandatory management forecast disclosures, the information content of management versus analyst forecast releases, and the motive of management in providing earnings forecasts to the market. Using weekly consensus (mean) financial analyst earnings forecasts, we document a close association between relative forecast accuracy and the timing of the release of the forecasts. We find that management forecasts issued subsequently to, coincidentally with, and up to four weeks prior to analyst forecasts are significantly more accurate than the analysts' estimates. The consensus analyst forecasts are more accurate beginning the ninth week after the release of the management forecast. Thus, by more closely controlling for the timing of the analysts' forecasts, we are able to provide a more precise picture of the dynamic nature of relative forecast accuracy.

We study circumstances when analysts’ forecasts diverge from managers’ forecasts after management guidance, and the consequences of this divergence for investors and analysts. Our results show that investors’ return response to earnings surprises based on analyst forecasts is significantly weaker when analyst and management forecasts diverge, and that this attenuating effect is stronger when the management forecast is more credible. When the divergent management forecast is more accurate than the analyst consensus forecast, the subsequent‐quarter analyst consensus forecast is significantly more accurate than that of the current quarter, and exhibits less serial correlation. Overall, our findings suggest that, when analyst and management forecasts diverge, investors find the two sources to contain complementary information, and analysts learn to improve their subsequent forecasts.

ABSTRACT: This study examines the relative accuracy of analyst earnings forecasts prepared both before (prior forecasts) and after (posterior forecasts) voluntary management earnings forecasts. The motivation for the study stems directly from recent studies which document statistically significant stock price reactions associated with management forecasts. The results of these studies suggest that management conveys new (or inside) information about earnings through its forecasts. Based on these results, one would expect that management forecasts would be more accurate than prior analyst forecasts while management and posterior analyst forecasts would be equally accurate. This paper reports results fully consistent with both of these predictions. These results, however, are conditional upon caveats about the estimation dates for analyst forecasts used to classify them as prior or posterior Several previous studies have also investigated similar issues but have produced conflicting results. The tests reported here are based on larger samples than those found in previous studies. This suggests that any accuracy differences between management and analysts are of such magnitude that they can be detected only in relatively large samples.

Meeting Individual Analyst Expectations

The Joint Effect of Management's Prior Forecast Accuracy and the Form of Its Financial Forecasts on Investor Judgment

ABSTRACTWe investigate the stock returns subsequent to quarterly earnings surprises, where the benchmark for an earnings surprise is the consensus analyst forecast. By defining the surprise relative to an analyst forecast rather than a time‐series model of expected earnings, we document returns subsequent to earnings announcements that are much larger, persist for much longer, and are more heavily concentrated in the long portion of the hedge portfolio than shown in previous studies. We show that our results hold after controlling for risk and previously documented anomalies, and are positive for every quarter between 1988 and 2000. Finally, we explore the financial results and information environment of firms with extreme earnings surprises and find that they tend to be “neglected” stocks with relatively high book‐to‐market ratios, low analyst coverage, and high analyst forecast dispersion. In the three subsequent years, firms with extreme positive earnings surprises tend to have persistent earnings surprises in the same direction, strong growth in cash flows and earnings, and large increases in analyst coverage, relative to firms with extreme negative earnings surprises. We also show that the returns to the earnings surprise strategy are highest in the quartile of firms where transaction costs are highest and institutional investor interest is lowest, consistent with the idea that market inefficiencies are more prevalent when frictions make it difficult for large, sophisticated investors to exploit the inefficiencies.

The Role of Management Forecast Precision in Predicting Management Forecast Error

This study investigates whether the Bank of Japan's (BOJ's) interval forecast publications have an added value relative to its point forecast publications by focusing on the range forecasts released by its policy board members. We find that the width of the BOJ's range forecasts has additional information for predicting inflation over point forecasts for the policy decision periods of 12–18 months. The predictive power of the range forecast is robust to the state of the economy, the recently introduced negative interest rate policy, and economic uncertainty measures. Furthermore, both the point and range forecasts influence professional forecasts. Our findings suggest that the source of the central bank's influence is closely related to its information content, not to forecasting accuracy. Therefore, range forecasts are important tools for monetary policy communication.

Mean reversion in profitability and growth is a well-documented phenomenon; however, comparatively less is known about the level of analysis that best captures mean reversion. In this study, we find that analyzing firms by life cycle stage improves the out-of-sample accuracy of profitability and growth forecasts over analyzing firms pooled across the economy and analyzing firms by industry. The improved accuracy is robust to both short-term and long-term forecasts of profitability and growth. We also find that the improvement in accuracy of forecasts from life cycle analyses is greatest for firms in the introduction and decline stages and for firms with greater uncertainty. Finally, we examine market participants' use of life cycle information in forming expectations. We find inefficient use of life cycle information in analyst forecasts, but not in management forecasts. We also find that life cycle forecasts are associated with year-ahead abnormal stock returns.

We examine how the market's ability to assess the truthfulness of management earnings forecasts affects how managers bias their forecasts, and we evaluate whether the market's response to management forecasts is consistent with it identifying predictable forecast bias. We find managers' willingness to misrepresent their forwardlooking information as a function of their incentives varies with the market's ability to detect misrepresentation. We examine incentives induced by the litigation environment, insider trading activities, firm financial distress, and industry concentration. With regard to the stock price response to forecasts, we find the market varies its response with the predictable bias in the forecast. The efficiency of the market's response, however, varies with the forecast news.

SYNOPSIS Prior literature has firmly established the relationship between IT capability and firm performance. In this paper, we extend the research in this field and investigate (1) whether IT capability contributes to management forecast accuracy, and (2) whether IT capability improves the informativeness of management forecasts and enhances the extent to which analysts incorporate management forecasts in their revisions. Using firms listed on InformationWeek 500 as our high IT capability group, we empirically demonstrate that firms with high IT capability are able to increase management forecast accuracy, and that analysts incorporate more information from management forecasts in their revisions if the firm has high IT capability.

In November 2007, the Federal Open Market Committee (FOMC) announced a change in the way it communicates its view of the economic outlook: It increased the frequency of its forecasts from two to four times per year, and it increased the length of the forecasting horizon from two to three years. The FOMC does not release the individual members' forecasts or standard measures of consensus such as the mean or median. Rather, it continues to release the forecast information as a range of forecasts, both the full range between the high and the low and a central tendency that omits the extreme values. This paper uses individual forecaster data from the Survey of Professional Forecasters (SPF) to mimic the FOMC's method for creating their central tendency. The authors show that the midpoint of the central tendency of the SPF is a reliable measure of the consensus, suggesting that the FOMC reporting method is also a reliable measure of consensus. For the dates when both are available, the authors also compare the relative forecast accuracy of the FOMC and SPF consensus forecasts for output growth and inflation. Overall, the differences in forecast accuracy are too small to be statistically significant.

Analyst Forecasts: Sales and Profit Margins

This study investigates the impact that the quality of reported earnings has on the accuracy of financial analysts earnings forecasts. Extant research indicates that earnings attributes are important considerations to users of accounting information. One such attribute is earnings quality; often measured as the magnitude of accruals that do not convert to cash in a timely manner, where a poor match of cash flows and accruals indicates low earnings quality. Such accruals could reduce the usefulness of financial reports. This study uses two measurements of forecast accuracy to assess the impact that earnings quality has on the forecast accuracy of financial analysts. Following prior research, one measurement considers the environment in which the analyst operates and compares their accuracy to that of their peers. The second compares the individual analyst forecast to the actual reported earnings. For both measurements of accuracy the results show that higher earnings quality is associated with improved forecast accuracy.

This paper evaluates the informativeness of analysts' ratings and earnings forecast information contained in analyst reports beyond what is publicly provided by management earnings forecasts. Using only analyst reports that have been released practically simultaneously with management forecasts, I find that both analysts' ratings and earnings forecasts have incremental information content conditional on management forecasts. Further analysis also reveals that analysts' earnings forecasts are significantly more accurate than concurrently-announced management earnings forecasts. Overall, the findings in this paper present strong evidence that analysts offer informational value to the market beyond information that is provided by company management.