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Analyst Earnings Forecasts and the Cross-Section of Stock Returns

Analyst Earnings Forecasts and the Cross-Section of Stock Returns PDF Author: Grawehr Louis-Emmanuel
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
This thesis analyzes the ability of a value-to-price ratio (V/P) to predict the cross-section of European stock returns, where V is based on the residual income valuation model using analysts' consensus earnings estimates from I/B/E/S. The V/P ratio is designed to identify stocks where market expectations of earnings are not accurately impounded into prices. For the constituents of the Stoxx Europe 600 index in the years 2002-2014, I test whether a self-financing portfolio taking a long position in the top quintile of V/P and a short position in the bottom quintile of V/P generates abnormal returns. I find that this strategy does not exhibit a statistically significant positive alpha in the context of standard asset pricing models. I argue that stock prices reflect analyst forecasts more accurately and more quickly than before, leading to the unprofitability of the strategy. The strategy does however have a positive and significant exposure to the Quality-Minus-Junk factor proposed by Asness, Frazzini and Pedersen (2014). Indeed, the V/P ratio is positively related to a self-constructed quality index incorporating the dimensions profitability, growth, safety and payout. This suggests that returns from picking stocks where market earnings expectations are not accurately reflected in prices are in large part driven by their quality characteristics.

Analyst Earnings Forecasts and the Cross-Section of Stock Returns

Analyst Earnings Forecasts and the Cross-Section of Stock Returns PDF Author: Grawehr Louis-Emmanuel
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
This thesis analyzes the ability of a value-to-price ratio (V/P) to predict the cross-section of European stock returns, where V is based on the residual income valuation model using analysts' consensus earnings estimates from I/B/E/S. The V/P ratio is designed to identify stocks where market expectations of earnings are not accurately impounded into prices. For the constituents of the Stoxx Europe 600 index in the years 2002-2014, I test whether a self-financing portfolio taking a long position in the top quintile of V/P and a short position in the bottom quintile of V/P generates abnormal returns. I find that this strategy does not exhibit a statistically significant positive alpha in the context of standard asset pricing models. I argue that stock prices reflect analyst forecasts more accurately and more quickly than before, leading to the unprofitability of the strategy. The strategy does however have a positive and significant exposure to the Quality-Minus-Junk factor proposed by Asness, Frazzini and Pedersen (2014). Indeed, the V/P ratio is positively related to a self-constructed quality index incorporating the dimensions profitability, growth, safety and payout. This suggests that returns from picking stocks where market earnings expectations are not accurately reflected in prices are in large part driven by their quality characteristics.

Analyst Forecasts and the Cross-Section of European Stock Returns

Analyst Forecasts and the Cross-Section of European Stock Returns PDF Author: Steven K. Todd
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
We examine revisions to earnings forecasts by equity analysts and their role in predicting stock returns. We provide evidence that European stocks with net upward revised forecasts earn higher future returns than otherwise similar stocks. This effect is not concentrated in small stocks, stocks with low analyst coverage, or stocks with low book-to-market ratios. We find differences in the return continuation patterns of stocks with upward versus downward revisions, namely, bad news travels quickly, but good news travels slowly. This result is consistent with investors' attaching greater significance to poor earnings forecasts, but adopting a wait-and-see approach to good news.

Do Errors in Expectations Explain the Cross-Section of Stock Returns

Do Errors in Expectations Explain the Cross-Section of Stock Returns PDF Author: G. Mujtaba Mian
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
Value stocks have historically outperformed growth stocks in most of the major international markets. Many researchers attribute this phenomenon to overly optimistic (pessimistic) expectations of investors for growth (value) stocks. In this paper, we use professional analysts' earnings forecasts from Japan to test this errors-in-expectations hypothesis. We compare the magnitude of the forecast errors, the proportion of optimistic and pessimistic forecasts, and the likelihood of downward forecast revisions, across growth and value stocks. In contrast to the predictions of the hypothesis, we do not find any evidence that earnings forecasts are systematically more optimistic for growth than for value stocks. Our results also suggest that the alleged correlation between book-to-market value, a common measure of growth, and forecast errors is the result of a measurement bias in computing the magnitude of the latter variable.

Expectations and the Structure of Share Prices

Expectations and the Structure of Share Prices PDF Author: John G. Cragg
Publisher: University of Chicago Press
ISBN: 0226116727
Category : Business & Economics
Languages : en
Pages : 185

Book Description
John G. Cragg and Burton G. Malkiel collected detailed forecasts of professional investors concerning the growth of 175 companies and use this information to examine the impact of such forecasts on the market evaluations of the companies and to test and extend traditional models of how stock market values are determined.

Analyst Forecasts and Stock Returns

Analyst Forecasts and Stock Returns PDF Author: James S. Ang
Publisher:
ISBN:
Category :
Languages : en
Pages : 34

Book Description
This study seeks to determine the relation between stock returns and analyst forecast properties, specifically, the dispersion and error of annual earnings forecasts. The results of portfolio sorts, Fama-MacBeth cross-sectional regression models, and Fama and French (1993) factor models indicate firms with low dispersion or error outperform firms with high dispersion or error. Robustness tests show the results are not explained by liquidity, momentum, industry, post-earnings announcement drift, or traditional risk measures. An investment strategy based on forecast properties is shown to produce zero-cost returns of 13% per year, yielding positive returns in all 19 years using an error measure. The results are not attributable to several potential theories. Risk-related theories are eliminated as firms with low dispersion or error (quot;transparentquot;) outperform firms with high dispersion or error (quot;opaquequot;). This remains true even after controlling for volatility measures. Behavioral theories based on optimism are also eliminated as optimistic forecasts only explain a small part of the results. Finally, the results are not related to contrarian-value strategies as the transparent firms outperform in both up and down markets.

Expectations and the Cross-Section of Stock Returns

Expectations and the Cross-Section of Stock Returns PDF Author: Rafael La Porta
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. I test for the existence of systematic errors using survey data on forecasts by stock market analysts. I show that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme.

Financial Analysts' Forecasts and Stock Recommendations

Financial Analysts' Forecasts and Stock Recommendations PDF Author: Sundaresh Ramnath
Publisher: Now Publishers Inc
ISBN: 1601981627
Category : Business & Economics
Languages : en
Pages : 125

Book Description
Financial Analysts' Forecasts and Stock Recommendations reviews research related to the role of financial analysts in the allocation of resources in capital markets. The authors provide an organized look at the literature, with particular attention to important questions that remain open for further research. They focus research related to analysts' decision processes and the usefulness of their forecasts and stock recommendations. Some of the major surveys were published in the early 1990's and since then no less than 250 papers related to financial analysts have appeared in the nine major research journals that we used to launch our review of the literature. The research has evolved from descriptions of the statistical properties of analysts' forecasts to investigations of the incentives and decision processes that give rise to those properties. However, in spite of this broader focus, much of analysts' decision processes and the market's mechanism of drawing a useful consensus from the combination of individual analysts' decisions remain hidden in a black box. What do we know about the relevant valuation metrics and the mechanism by which analysts and investors translate forecasts into present equity values? What do we know about the heuristics relied upon by analysts and the market and the appropriateness of their use? Financial Analysts' Forecasts and Stock Recommendations examines these and other questions and concludes by highlighting area for future research.

Cross-sectional Variation of Measurement Error and Predictability of Earnings and Stock Returns

Cross-sectional Variation of Measurement Error and Predictability of Earnings and Stock Returns PDF Author: Jung Hoon Kim
Publisher:
ISBN:
Category :
Languages : en
Pages : 69

Book Description
In capital markets research, market expectation of future earnings plays a vital role. However, almost all proxies inevitably measure the market expectation of future earnings with error, which results in unsatisfactory empirical outcomes in prior research (e.g., small empirical values of earnings response coefficient and poor quality estimates of expected rates of return). Using analysts' consensus forecasts, this study investigates how noisy measurement of the market expectation of future earnings affects the predictability of future earnings and stock returns. Based on the errors-in-variables approach, this study first provides a framework to capture cross-sectional variation of the measurement error in analysts' consensus forecasts. With this framework in place, this study documents that analysts' consensus forecasts with more measurement error have less ability to predict future earnings and stock returns, and that incorporating information about cross-sectional variation of the measurement error can improve the predictability of future earnings and stock returns. These findings will be useful to accounting research that relies on the market expectation of future earnings and to practitioners seeking to forecast profitability and stock returns.

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

The Trend in Firm Profitability and the Cross Section of Stock Returns PDF Author: Ferhat Akbas
Publisher:
ISBN:
Category :
Languages : en
Pages : 91

Book Description
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 twelve 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.

Estimating the Cost of Capital Implied by Market Prices and Accounting Data

Estimating the Cost of Capital Implied by Market Prices and Accounting Data PDF Author: Peter Easton
Publisher: Now Publishers Inc
ISBN: 1601981945
Category : Business & Economics
Languages : en
Pages : 148

Book Description
Estimating the Cost of Capital Implied by Market Prices and Accounting Data focuses on estimating the expected rate of return implied by market prices, summary accounting numbers, and forecasts of earnings and dividends. Estimates of the expected rate of return, often used as proxies for the cost of capital, are obtained by inverting accounting-based valuation models. The author describes accounting-based valuation models and discusses how these models have been used, and how they may be used, to obtain estimates of the cost of capital. The practical appeal of accounting-based valuation models is that they focus on the two variables that are commonly at the heart of valuations carried out by equity analysts -- forecasts of earnings and forecasts of earnings growth. The question at the core of this monograph is -- How can these forecasts be used to obtain an estimate of the cost of capital? The author examines the empirical validity of the estimates based on these forecasts and explores ways to improve these estimates. In addition, this monograph details a method for isolating the effect of any factor of interest (such as cross-listing, fraud, disclosure quality, taxes, analyst following, accounting standards, etc.) on the cost of capital. If you are interested in understanding the academic literature on accounting-based estimates of expected rate of return this monograph is for you. Estimating the Cost of Capital Implied by Market Prices and Accounting Data provides a foundation for a deeper comprehension of this literature and will give a jump start to those who have an interest in these topics. The key ideas are introduced via examples based on actual forecasts, accounting information, and market prices for listed firms, and the numerical examples are based on sound algebraic relations.