scholarly journals Market Participants Neither Commit Predictable Errors nor Conform to REH: Evidence from Survey Data of Inflation Forecasts

2021 ◽  
Author(s):  
Roman Frydman ◽  
◽  
Joshua Stillwagon ◽  
Keyword(s):  
Survey Data ◽  
Forecast Errors ◽  
Forecast Revisions ◽  
Market Participants ◽  
Inflation Forecasts

We develop a novel characterization of participants’ forecasts with a mixture of normal variables arising from a Markov component. Using this characterization, we formulate five behavioral specifications, including four implied by the diagnostic expectations approach, as well as three implied by REH, and derive several new predictions for Coibion and Gorodnichenko.s regression of forecast errors on forecast revisions. Predictions of all eight specifications are inconsistent with the observed instability of individual CG regressions’ coefficients, based on inflation forecasts from 24 professionals. Our findings suggest how to build on key insights of the REH and behavioral approaches in specifying individuals’ forecasts.

scholarly journals Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting

2020 ◽  
Vol 2020 (089) ◽  
pp. 1-56
Author(s):  
Andrew C. Chang ◽  
◽  
Trace J. Levinson ◽  
Keyword(s):  
Forecast Errors ◽  
Time Varying ◽  
Open Market ◽  
Federal Open Market Committee ◽  
Forecast Revisions ◽  
Consumption Expenditures ◽  
Inflation Forecasts ◽  
Board Of Governors ◽  
Personal Consumption ◽  
Reserve System

We introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) inflation forecasts produced by the staff of the Board of Governors of the Federal Reserve System. In contrast to the eight Greenbook forecasts a year the staff produces for Federal Open Market Committee (FOMC) meetings, our dataset has roughly weekly forecasts. We use these new data to study whether the staff forecasts efficiently and whether efficiency, or lack thereof, is time-varying. Prespecified regressions of forecast errors on forecast revisions show that the staff's GDP forecast errors correlate with its GDP forecast revisions, particularly for forecasts made more than two weeks from the start of a FOMC meeting, implying GDP forecasts exhibit time-varying inefficiency between FOMC meetings. We find some weaker evidence for inefficient inflation forecasts.

The Use of DuPont Analysis by Market Participants

2008 ◽  
Vol 83 (3) ◽  
pp. 823-853 ◽  
Author(s):  
Mark T. Soliman
Keyword(s):  
Accounting Information ◽  
Abnormal Returns ◽  
Financial Statement ◽  
Delayed Response ◽  
Forecast Errors ◽  
Financial Statement Analysis ◽  
Forecast Revisions ◽  
Market Participants ◽  
Dupont Analysis ◽  
Asset Turnover

DuPont analysis, a common form of financial statement analysis, decomposes return on net operating assets into two multiplicative components: profit margin and asset turnover. These two accounting ratios measure different constructs and, accordingly, have different properties. Prior research has found that a change in asset turnover is positively related to future changes in earnings. This paper comprehensively explores the DuPont components and contributes to the literature along three dimensions. First, the paper contributes to the financial statement analysis literature and finds that the information in this accounting signal is in fact incremental to accounting signals studied in prior research in predicting future earnings. Second, it contributes to the literature on the stock market's use of accounting information by examining immediate and future equity return responses to these components by investors. Finally, it adds to the literature on analysts' processing of accounting information by again testing immediate and delayed response of analysts through contemporaneous forecast revisions as well as future forecast errors. Consistent across both groups of market participants, the results show that the information is useful as evidenced by associations between the DuPont components and stock returns as well as analyst forecast revisions. However, I find predictable future forecast errors and future abnormal returns indicating that the information processing does not appear to be complete. Taken together, the analysis indicates that the DuPont components represent an incremental and viable form of information about the operating characteristics of a firm.

scholarly journals OGLE-2009-BLG-023/MOA-2009-BLG-028: characterization of a binary microlensing event based on survey data

2011 ◽  
Vol 413 (2) ◽  
pp. 1244-1250
Author(s):  
K.-H. Hwang ◽  
C. Han ◽  
A. Udalski ◽  
T. Sumi ◽  
A. Gould ◽  
...  
Keyword(s):  
Survey Data ◽  
Event Based

scholarly journals Coordinating expectations through central bank projections

2020 ◽  
Author(s):  
Fatemeh Mokhtarzadeh ◽  
Luba Petersen
Keyword(s):  
Central Bank ◽  
Rational Expectations ◽  
Inflation Targeting ◽  
Aggregate Stability ◽  
Central Banks ◽  
Output Gap ◽  
Forecast Errors ◽  
Market Participants ◽  
Wide Range ◽  
Ex Ante

AbstractCentral banks are increasingly communicating their economic outlook in an effort to manage the public and financial market participants’ expectations. We provide original causal evidence that the information communicated and the assumptions underlying a central bank’s projection can matter for expectation formation and aggregate stability. Using a between-subject design, we systematically vary the central bank’s projected forecasts in an experimental macroeconomy where subjects are incentivized to forecast the output gap and inflation. Without projections, subjects exhibit a wide range of heuristics, with the modal heuristic involving a significant backward-looking component. Ex-Ante Rational dual projections of the output gap and inflation significantly reduce the number of subjects’ using backward-looking heuristics and nudge expectations in the direction of the rational expectations equilibrium. Ex-Ante Rational interest rate projections are cognitively challenging to employ and have limited effects on the distribution of heuristics. Adaptive dual projections generate unintended inflation volatility by inducing boundedly-rational forecasters to employ the projection and model-consistent forecasters to utilize the projection as a proxy for aggregate expectations. All projections reduce output gap disagreement but increase inflation disagreement. Central bank credibility is significantly diminished when the central bank makes larger forecast errors when communicating a relatively more complex projection. Our findings suggest that inflation-targeting central banks should strategically ignore agents’ irrationalities when constructing their projections and communicate easy-to-process information.

scholarly journals Overreaction in Macroeconomic Expectations

2020 ◽  
Vol 110 (9) ◽  
pp. 2748-2782 ◽  
Author(s):  
Pedro Bordalo ◽  
Nicola Gennaioli ◽  
Yueran Ma ◽  
Andrei Shleifer
Keyword(s):  
Rational Expectations ◽  
Bayesian Updating ◽  
Learning Model ◽  
Forecast Errors ◽  
Full Information ◽  
Distortion Parameter ◽  
Forecast Revisions ◽  
Financial Variables ◽  
Consensus Forecasts ◽  
Important Variation

We study the rationality of individual and consensus forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), who examine predictability of forecast errors from forecast revisions. We find that individual forecasters typically overreact to news, while consensus forecasts under-react relative to full-information rational expectations. We reconcile these findings within a diagnostic expectations version of a dispersed information learning model. Structural estimation indicates that departures from Bayesian updating in the form of diagnostic overreaction capture important variation in forecast biases across different series, yielding a belief distortion parameter similar to estimates obtained in other settings. (JEL C53, D83, D84, E13, E17, E27, E47)

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.

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