Identifying the News in Analysts’ Earnings Forecasts Revisions: An Alternative to the Random Walk Expectation

2021 ◽  
Author(s):  
Ray Pfeiffer ◽  
Karen Teitel ◽  
Susan Wahab ◽  
Mahmoud Wahab
Keyword(s):  
Random Walk ◽  
Stock Returns ◽  
Earnings Forecasts ◽  
Simple Random Walk ◽  
Analyst Forecast ◽  
Forecast Errors ◽  
Earnings Expectations ◽  
Forecast Revisions ◽  
Conditioning Information ◽  
Using Data

Previous research indicates that analysts’ forecasts are superior to time series models as measures of investors’ earnings expectations. Nevertheless, research also documents predictable patterns in analysts’ forecasts and forecast errors. If investors are aware of these patterns, analysts’ forecast revisions measured using the random walk expectation are an incomplete representation of changes in investors’ earnings expectations. Investors can use knowledge of errors and biases in forecasts to improve upon the simple random walk expectation by incorporating conditioning information. Using data from 2005 to 2015, we compare associations between market-adjusted stock returns and alternative specifications of forecast revisions to determine which best represents changes in investors’ earnings expectations. We find forecast revisions measured using a ‘bandwagon expectations’ specification, which includes two prior analysts’ forecast signals and provides the most improvement over random-walk-based revision measures. Our findings demonstrate benefits to considering information beyond the previously issued analyst forecast when representing investors’ expectations of analysts’ forecasts.

scholarly journals The Role of Anchoring Bias in the Equity Market: Evidence from Analysts’ Earnings Forecasts and Stock Returns

2012 ◽  
Vol 48 (1) ◽  
pp. 47-76 ◽  
Author(s):  
Ling Cen ◽  
Gilles Hilary ◽  
K. C. John Wei
Keyword(s):  
Stock Returns ◽  
Earnings Forecasts ◽  
Equity Market ◽  
Stock Splits ◽  
Forecast Errors ◽  
Forecast Revisions ◽  
Earnings Per Share ◽  
Earnings Surprises ◽  
Anchoring Bias

AbstractWe test the implications of anchoring bias associated with forecast earnings per share (FEPS) for forecast errors, earnings surprises, stock returns, and stock splits. We find that analysts make optimistic (pessimistic) forecasts when a firm’s FEPS is lower (higher) than the industry median. Further, firms with FEPS greater (lower) than the industry median experience abnormally high (low) future stock returns, particularly around subsequent earnings announcement dates. These firms are also more likely to engage in stock splits. Finally, split firms experience more positive forecast revisions, more negative forecast errors, and more negative earnings surprises after stock splits.

Do Investors Fully Unravel Persistent Pessimism in Analysts' Earnings Forecasts?

2017 ◽  
Vol 93 (3) ◽  
pp. 349-377 ◽  
Author(s):  
David Veenman ◽  
Patrick Verwijmeren
Keyword(s):  
Stock Returns ◽  
Earnings Forecasts ◽  
Analyst Forecast ◽  
Short Term ◽  
Market Prices ◽  
Earnings Expectations ◽  
Earnings Surprises ◽  
Announcement Returns ◽  
Low Probability ◽  
Jel Classifications

ABSTRACT This study presents evidence suggesting that investors do not fully unravel predictable pessimism in sell-side analysts' earnings forecasts. We show that measures of prior consensus and individual analyst forecast pessimism are predictive of both the sign of firms' earnings surprises and the stock returns around earnings announcements. That is, we find that firms with a relatively high probability of forecast pessimism experience significantly higher announcement returns than those with a low probability. Importantly, we show that these findings are driven by predictable pessimism in analysts' short-term forecasts, as opposed to optimism in their longer-term forecasts. We further find that this mispricing is related to the difficulty investors have in identifying differences in expected forecast pessimism. Overall, we conclude that market prices do not fully reflect the conditional probability that a firm meets or beats earnings expectations as a result of analysts' pessimistically biased short-term forecasts. JEL Classifications: G12; G14; G20.

Investors' Trade Size and Trading Responses around Earnings Announcements: An Empirical Investigation

2001 ◽  
Vol 76 (2) ◽  
pp. 221-244 ◽  
Author(s):  
Nilabhra Bhattacharya
Keyword(s):  
Random Walk ◽  
Earnings Announcements ◽  
Random Walk Model ◽  
Analyst Forecast ◽  
Forecast Errors ◽  
Analyst Following ◽  
Earnings Expectations ◽  
Trading Activities ◽  
Trading Response ◽  
Small Traders

Prior research suggests that the earnings expectations of a segment of the market can be described by the seasonal random-walk model. Prior research also provides evidence that less wealthy and less informed investors tend to make smaller trades (small traders) than wealthier and betterinformed investors (large traders). I hypothesize that it is the earnings expectations of small traders that are associated with predictions from the seasonal random-walk model. By directly analyzing the trading activities of small and large traders, this study provides evidence that is largely consistent with the hypotheses. Specifically, small traders' trading response around earnings announcements is increasing in the magnitude of seasonal random-walk forecast errors, even after controlling for absolute analyst forecast errors, contemporaneous price changes, and market-wide trading. Supplementary analysis reveals that this effect is largely confined to firms with relatively impoverished information environments (i.e., smaller firms and firms with little to moderate analyst following).

The Trend in Firm Profitability and the Cross-Section of Stock Returns

2017 ◽  
Vol 92 (5) ◽  
pp. 1-32 ◽  
Author(s):  
Ferhat Akbas ◽  
Chao Jiang ◽  
Paul D. Koch
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Cross Section ◽  
The Other ◽  
Analyst Forecast ◽  
Forecast Errors ◽  
Earnings Surprise ◽  
Firm Profitability ◽  
Earnings Momentum ◽  
Jel Classifications

ABSTRACT This study shows that the recent trajectory of a firm's profits predicts future profitability and stock returns. The predictive information contained in the trend of profitability is not subsumed by the level of profitability, earnings momentum, or other well-known determinants of stock returns. The profit trend also predicts the earnings surprise one quarter later, and analyst forecast errors over the following 12 months, suggesting that sophisticated investors underreact to the information in the profit trend. On the other hand, we find no evidence of investor overreaction, and our results cannot be explained by well-known risk factors. JEL Classifications: G12; G14.

scholarly journals Earnings Expectations during the COVID-19 Crisis*

2020 ◽  
Vol 10 (4) ◽  
pp. 598-617 ◽  
Author(s):  
Augustin Landier ◽  
David Thesmar
Keyword(s):  
Risk Premium ◽  
Earnings Forecasts ◽  
Earnings Expectations ◽  
Forecast Revisions ◽  
Asset Risk ◽  
Equity Values ◽  
Oxford University ◽  
Risk Free Rate ◽  
Published Paper ◽  
Free Rate

Abstract We analyze the dynamics of earnings forecasts and discount rates implicit in valuations during the COVID-19 crisis. Forecasts over 2020 earnings have been progressively reduced by 16%. Longer-run forecasts have reacted much less. We estimate an implicit discount rate going from 8.5% in mid-February to 11% at the end of March and reverting to its initial level in mid-May. Over the period, the unlevered asset risk premium increases by 50bp, the leverage effect also increases by 50bp, while the risk free rate decreases by 100bp. Hence, analysts’ forecast revisions explain all of the decrease in equity values between January 2020 and mid-May 2020. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

scholarly journals Earnings Predictability And Broker-Analysts’ Earnings Forecast Bias

2017 ◽  
Vol 33 (6) ◽  
pp. 1285-1302
Author(s):  
Michael Eames ◽  
Steven Glover
Keyword(s):  
Private Information ◽  
Alternative Model ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Earnings Expectations ◽  
Forecast Bias ◽  
Analyst Expectations ◽  
Earnings Predictability ◽  
Using Data ◽  
Short Horizon

Scholars have reasoned that analysts issue optimistic forecasts to improve their access to managers’ private information when earnings are unpredictable. While this requires a managerial preference for analyst forecast optimism, the observed walk-down of analyst expectations to beatable forecasts is consistent with a managerial preference for pessimism in short-horizon forecasts. Using data from various sample periods, alternative model specifications, and various measures of earnings unpredictability, we find that pessimism, not optimism, in short-horizon forecasts is associated with increasingly unpredictable earnings. Our results suggest that firms can more effectively manage analysts’ earnings expectations downward when earnings are relatively unpredictable.

scholarly journals Returns to buying upward revision and selling downward revision stocks

2016 ◽  
Vol 42 (11) ◽  
pp. 1110-1124
Author(s):  
Tony Chieh-Tse Hou ◽  
Phillip McKnight ◽  
Charlie Weir
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Information Diffusion ◽  
Trading Strategy ◽  
Good News ◽  
Analyst Forecast ◽  
Earnings Forecast ◽  
Content Type ◽  
Forecast Revisions ◽  
New Information

Purpose The purpose of this paper is to investigate the role of earnings forecast revisions by equity analysts in predicting Canadian stock returns Design/methodology/approach The sample covers 420 Canadian firms over the period 1998-2009. It analyses investors’ reactions to 27,271 upward revisions and 32,005 downward revisions of analysts’ forecasts for Canadian quoted companies. To test whether analysts’ earnings forecast revisions affect stock return continuation, forecast revision portfolios similar to Jegadeesh and Titman (2001) are constructed. The paper analyses the returns gained from a trading strategy based on buying the strong upward revisions portfolio and short selling the strong downward revisions portfolio. It also separates the sample into upward and downward revisions. Findings The authors find that new information in the form of analyst forecast revisions is not impounded efficiently into stock prices. Significant returns persist for a trading strategy that buys stocks with recent upward revisions and short sells stocks with recent downward revisions. Good news is impounded into stock prices more slowly than bad news. Post-earnings forecast revisions drift is negatively related to analyst coverage. The effect is strongest for stocks with greatest number of upward revisions. The introduction of the better disclosure standards has made the Canadian stock market more efficient. Originality/value The paper adds to the limited evidence on the effect of analyst forecast revisions on the returns of Canadian stocks. It sheds light on the importance of analysts’ earnings forecast information and offers support for the investor conservatism and information diffusion hypotheses. It also shows how policy can improve market efficiency.

Tax-Motivated Loss Shifting

2013 ◽  
Vol 88 (5) ◽  
pp. 1657-1682 ◽  
Author(s):  
Merle M. Erickson ◽  
Shane M. Heitzman ◽  
X. Frank Zhang
Keyword(s):  
Earnings Forecasts ◽  
Data Availability ◽  
Analyst Forecast ◽  
Forecast Errors ◽  
Corporate Reporting ◽  
Earnings Surprises ◽  
Reporting Decisions ◽  
Tax Payments ◽  
Tax Loss ◽  
Do So

ABSTRACT: This paper examines the implications of tax loss carryback incentives for corporate reporting decisions and capital market behavior. During the 1981 through 2010 sample period, we find that firms increase losses in order to claim a cash refund of recent tax payments before the option to do so expires, and we estimate that firms with tax refund-based incentives accelerate about $64.7 billion in losses. Tax-motivated loss shifting is reflected in both recurring and nonrecurring items and is more evident for financially constrained firms. Analysts do not generally incorporate tax-motivated loss shifting into their earnings forecasts, resulting in more negative analyst forecast errors for firms with tax-based incentives than for firms without. Holding earnings surprises constant, however, investors react less negatively to losses reported by firms with tax loss carryback incentives. Data Availability: Data are available from sources identified in the paper.

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