Dissecting the Association between Stock Returns and GDP Growth Forecast Errors: Implications for Interdisciplinary Capital Markets Research in Accounting

2014 ◽  
Author(s):  
Panos N. Patatoukas
Keyword(s):  
Stock Returns ◽  
Capital Markets ◽  
Gdp Growth ◽  
Forecast Errors

On the Association Between Analysts' Forecast Errors and Past Stock Returns: A Re-Examination

2002 ◽  
Author(s):  
Xia NMI Chen ◽  
Qiang Cheng
Keyword(s):  
Stock Returns ◽  
Forecast Errors

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 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.

scholarly journals Modeling Judgment in Macroeconomic Forecasts

2021 ◽  
Author(s):  
Philip Hans Franses
Keyword(s):  
Time Series ◽  
Formal Method ◽  
Econometric Model ◽  
Time Series Model ◽  
Gdp Growth ◽  
Forecast Errors ◽  
African Countries ◽  
Empirical Results ◽  
Real Gdp

AbstractMany macroeconomic forecasts are the outcome of a judgmental adjustment to a forecast from an econometric model. The size, direction, and motivation of the adjustment are often unknown as usually only the final forecast is available. This is problematic in case an analyst wishes to learn from forecast errors, which could lead to improving the model, the judgment or both. This paper therefore proposes a formal method to include judgment, which makes the combined forecast reproducible. As an illustration, a forecast from a benchmark simple time series model is only modified when the value of a factor, estimated from a multitude of variables, exceeds a user-specified threshold. Simulations and empirical results for forecasting annual real GDP growth in 52 African countries provide an illustration.

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.

FRACTALITY EVIDENCE AND LONG-RANGE DEPENDENCE ON CAPITAL MARKETS: A HURST EXPONENT EVALUATION

Fractals ◽  
2014 ◽  
Vol 22 (04) ◽  
pp. 1450010 ◽  
Author(s):  
CAMELIA OPREAN ◽  
CRISTINA TĂNĂSESCU
Keyword(s):  
Random Walk ◽  
Stock Returns ◽  
Long Range ◽  
Capital Markets ◽  
Hurst Exponent ◽  
Efficient Market Hypothesis ◽  
Long Range Dependence ◽  
Fluctuation Analysis ◽  
Random Walk Hypothesis ◽  
Detrended Fluctuation

Since the existence of market memory could implicate the rejection of the efficient market hypothesis, the aim of this paper is to find any evidence that selected emergent capital markets (eight European and BRIC markets, namely Hungary, Romania, Estonia, Czech Republic, Brazil, Russia, India and China) evince long-range dependence or the random walk hypothesis. In this paper, the Hurst exponent as calculated by R/S fractal analysis and Detrended Fluctuation Analysis is our measure of long-range dependence in the series. The results reinforce our previous findings and suggest that if stock returns present long-range dependence, the random walk hypothesis is not valid anymore and neither is the market efficiency hypothesis.

scholarly journals Economic Growth, Corporate Earnings And Equity Returns: Evidence From Central And Eastern European Countries

2016 ◽  
Vol 19 (3) ◽  
pp. 93-111
Author(s):  
Jerzy Gajdka ◽  
Piotr Pietraszewski
Keyword(s):  
Economic Growth ◽  
Stock Returns ◽  
Emerging Market ◽  
Equity Returns ◽  
European Countries ◽  
Gdp Growth ◽  
Eastern European ◽  
Corporate Earnings ◽  
Eastern European Countries ◽  
The Impact

This paper discusses the links between economic growth, corporate earnings and stock returns. Cross-country correlation studies do not confirm the intuitive assumption that higher returns on equities are more likely in the fastergrowing countries. The problem can be analysed more deeply by analysing stock returns with respect to the growth of earnings per share (EPS) and changes in valuation (P/E ratio). Within this framework, two types of factors explaining the lack of correlation between GDP growth and stock returns are distinguished. The empirical research on developed and emerging market countries reveals that in the long run stock price returns are driven by companies’ earnings, and that the lack of correlation between GDP growth and equity returns is almost fully explained by the divergence between GDP growth and EPS growth. In this article the results of an investigation into this area, based on a sample of post-communist Central and Eastern European countries, are presented and discussed. It was found that in these countries changes in valuation (P/E ratio) appear to play an important role, cancelling the impact of EPS growth on stock returns.

Earnings forecast errors: Comparative evidence from the Pacific-Basin capital markets

1997 ◽  
Vol 5 (1) ◽  
pp. 115-129 ◽  
Author(s):  
Arthur Allen ◽  
Jang Youn Cho ◽  
Kooyul Jung
Keyword(s):  
Capital Markets ◽  
Pacific Basin ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
The Pacific

The Association between the Magnitude of Quarterly Earnings Forecast Errors and Risk-Adjusted Stock Returns

1984 ◽  
Vol 22 (2) ◽  
pp. 526 ◽  
Author(s):  
Robert L. Hagerman ◽  
Mark E. Zmijewski ◽  
Pravin Shah
Keyword(s):  
Stock Returns ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Quarterly Earnings
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