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Author: Patricia Dechow
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
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Book Description
We investigate the determinants of analysts' target price implied returns and the implication of our findings for investment decision-making. We identify four broad sets of factors that help explain the cross-sectional variation in target price implied returns: future realized stock returns, errors in forecasting fundamentals, errors in forecasting the expected return to risk, and biases relating to analysts' incentives. Our results suggest that all four sets help explain target price implied returns, with errors in forecasting the expected return to empirical risk proxies having the greatest impact. Collectively, these variables explain nearly a quarter of the cross-sectional variation in target price implied returns. We use our model to predict the optimistic bias in target price implied returns and evaluate whether investors correctly ignore the predictable bias. The results suggest that investors make similar valuation errors to analysts and/or do not perfectly back out the predicted bias in target prices.
Author: Patricia Dechow
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
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Book Description
We investigate the determinants of analysts' target price implied returns and the implication of our findings for investment decision-making. We identify four broad sets of factors that help explain the cross-sectional variation in target price implied returns: future realized stock returns, errors in forecasting fundamentals, errors in forecasting the expected return to risk, and biases relating to analysts' incentives. Our results suggest that all four sets help explain target price implied returns, with errors in forecasting the expected return to empirical risk proxies having the greatest impact. Collectively, these variables explain nearly a quarter of the cross-sectional variation in target price implied returns. We use our model to predict the optimistic bias in target price implied returns and evaluate whether investors correctly ignore the predictable bias. The results suggest that investors make similar valuation errors to analysts and/or do not perfectly back out the predicted bias in target prices.
Author: Patricia Dechow
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
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Book Description
We investigate the determinants of analysts' target price forecasts and evaluate their relative importance for explaining the cross-sectional variation in target price implied returns. We identify four broad determinants: the informational component predictive of future stock returns, errors in forecasting fundamentals, errors in forecasting the expected return to risk, and biases relating to analysts' incentives. Our findings indicate that analysts have a limited ability to predict short-term future returns, and incorrect fundamental forecasts marginally impact target price valuations. Errors in forecasting the expected return to empirical risk proxies such as beta and idiosyncratic volatility have the greatest impact and induce significant noise and optimism into target prices. Job-related incentives induce incremental optimism in target prices. We use our target price determinants model to predict the optimistic bias in target price forecasts and evaluate whether investors correctly ignore the predictable bias. The results suggest that investors make similar valuation errors to analysts and/or do not perfectly back out the predicted bias in target prices.
Author: Noor Hashim
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This thesis presents three essays on analyst target prices. The essays contribute to the major debate on the value of analyst target prices in the capital market by addressing the following three questions: Does a bull-bear valuation analysis increase the accuracy of analysts' target prices? Does analyst ranking affect how informative target prices are to institutional investors? And, do analysts use their cash flow forecasts when setting target prices?In the first essay, I explore whether conducting a bull-bear analysis (BBA) increases target price accuracy. A bull-bear analysis is a risk assessment tool that analysts use to enhance the credibility of their valuations and limit target price uncertainty. Using propensity score matching to control for selection bias, combined with a difference-in-differences estimation to allow for company- and analyst-specific effects, I estimate the effect of supplementing target prices with a BBA on the target price accuracy of US stocks during 2008-2009. The results suggest that target prices are more accurate when analysts supplement them with a BBA. The findings contribute to the literature exploring the determinants of analyst ability to produce accurate target prices. The second essay examines whether analyst ranking status affects institutional investors' decisions to incorporate target price information into their investment strategies. Evidence shows that market participants value analyst target prices. There is limited evidence, however, on how target price revisions influence the decisions of sophisticated investors. The examination of this study is relevant for the economic question: Does analyst reputation mitigate or exacerbate the conflicts of interest that analysts face? Consistent with institutional investor trades being based on superior information, I observe differences in the information content of target price revisions by star and non-star analysts. Additionally, a duration analysis shows that the quality of analyst target price revisions significantly increases the hazard of analysts losing their star ranking. In the final essay, I examine whether analysts' decisions to issue cash flow forecasts depend endogenously on their decision to use these forecasts to set target prices. Using an endogenous switching regression model, with analyst report regimes of disclosure and non-disclosure of cash flow forecasts, I find that cash flow revisions are more important than earnings revisions in explaining the magnitude of target price revisions in the cash flow disclosure regime. Cash flow forecasts influence and are influenced by analyst valuation choices. Additional analysis shows that cash flow-based pseudo-target prices play a greater role in explaining target price implied returns than do earnings-based pseudo-target prices. These findings provide insights into analysts' valuation decision processes and their sophisticated valuation input choices.
Author: Bertram Bettac
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This study examines the impact of broker- and recommendation-specific factors on variations in target price accuracy. Using a sample of 2,273 target price revisions for SMI companies from 2010 to 2015, I find that target price forecasts are systematically biased with target price implied returns exceeding realized returns by an average of 17%. With regards to recommendation-specific factors, the size of the forecast error increases with the level of optimism an analyst exhibits via his target price forecast. This holds true even after adjusting for stock-specific risk differences. The systematic positive bias in target prices is reflected in the investment recommendation distribution with buy recommendations exceeding sell recommendations by a factor of six. Target price errors vary significantly between recommendation classes and target prices associated with sell recommendations are systematically more accurate than those associated with buy and hold recommendations. With regards to broker-specific factors, there is no conclusive evidence on differential forecasting abilities between highly ranked and unranked brokers as well as Swiss and foreign brokers.
Author: Turan G. Bali
Publisher:
ISBN:
Category :
Languages : en
Pages : 71
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Book Description
Motivated by the nature of asset pricing models, we investigate the cross-sectional relation between the market's ex-ante view of a stock's risk and the stock's ex-ante expected return. We demonstrate that an ex-ante measure of expected returns based on analyst price targets is highly related to the market's required rate of return. Using this measure, we show that ex-ante measures of volatility, skewness, and kurtosis derived from option prices are positively related to ex-ante expected returns. We then decompose the risk measures into systematic and unsystematic components and find that while expected returns are related to both systematic and unsystematic variance risk, only the unsystematic components of skewness and kurtosis are important for explaining the cross-section of expected stock returns. The results are consistent using two different approaches to measuring ex-ante risk and robust to controls for other variables related to stock returns and analyst bias.
Author: Stefano Bonini
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
In this paper we examine the profitability of trading strategies based on target prices embedded in equity research reports. We adopt target prices as information signals to build our portfolio strategy. At the first stage, we exploit implicit returns (difference between the current price and the target price) as a buying or short selling signal to open every transaction in the portfolio. Next, we use raw and adjusted target prices as a closing transaction signal. We build three different strategies to verify if the overshooting of target prices revealed by several studies could affect the profitability of a trading strategy based on these target prices. We have formed four portfolios within every strategy to verify whether analysts' target prices have any investment value. We find that all strategies deliver positive abnormal returns against the market. In particular, the highest and lowest implicit return classes exhibit the highest stock returns and abnormal returns. In the last part control these returns for systematic risk, factors through the CAPM and the Fama amp; French three factor model. The positive performances of our strategies persist and, in particular, our strategies beat the market with consistent abnormal returns in all the four implicit return classes analyzed. From the three factors equation, it seems that analysts tend to advise buying stocks with risk above the average market risk, with growth profile and with large market value. Conversely analysts advise selling value stocks and those with a negative beta.
Author: Benjamin Carl Anderson
Publisher:
ISBN: 9781321885781
Category : Stocks
Languages : en
Pages : 220
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Book Description
Target prices are analysts' forecasts of a firm's stock price. Although target prices can be used to help market participants make investment decisions, much is still unknown about how analysts make these forecasts. Because prior literature documents momentum in stock returns, in this paper, I examine whether target prices reflect the information in returns over the six months prior to the target price announcement date. I find that target prices systematically underestimate the persistence of these six month returns. I further find that the forecasted return in target price revisions is more pessimistic following periods of very good stock performance and more optimistic following periods of very poor stock performance. However, I find that target prices made by 'All-Star' analysts reflect the information in six month returns when these target prices follow a period of very poor stock performance.
Author: Zhi Da
Publisher:
ISBN:
Category :
Languages : en
Pages : 43
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Book Description
This paper examines the informativeness of analysts' target price forecasts by relating the investment value of target prices to their primary drivers. Decomposing target price forecasts into near-term earnings forecasts and price-to-earnings ratio forecasts, we show that target price revisions reflect information from both components. In addition, we also find that the relative importance of each component in target price revisions is related to firm characteristics. A portfolio based on target price implied expected returns delivers significant abnormal returns. More importantly, we find that the abnormal returns are associated with both earnings and price-to-earnings forecasts, which suggests that the informativeness of target price forecasts comes not only from analysts' ability to forecast short-term earnings but also from their ability to assess risk and long-term growth prospect implied in price-to-earnings forecasts.
Author: Johnathan Loudis
Publisher:
ISBN:
Category :
Languages : en
Pages : 153
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Book Description
This paper provides evidence that the market does not efficiently incorporate expected returns implied by analyst price targets into prices. I use a novel decomposition to extract information and bias components from these analyst-expected returns and develop an asset pricing framework that helps interpret price reactions to each component. A one-standard-deviation increase in the information (bias) component is associated with a five (one) percentage point increase in announcement-month returns. The positive reaction to bias implies the market does not fully debias analyst-expected returns before incorporating them into prices. Prices overreact to bias and reverse their initial reaction within three to six months. Prices underreact to information and returns drift an additional one percentage point beyond their initial reaction in the following 12 months. Announcement-window returns forecast future returns, which provides model-free evidence of underreaction, and that underreaction dominates overreaction. Trading against underreaction generates average monthly returns of 1.12% with a Sharpe ratio of 1.08, and the returns survive controlling for exposure to many standard factors.
Author: Alexander Alsop
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 43
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Book Description
There has been a considerable amount of literature on equity research analysts and their price targets, but much of it does not address how it could be used to generate alpha in a practical way. When the research does address accuracy, it does not consider that analyst's bias and inaccuracy can be accounted for through an econometric model. This paper seeks to address these issues and determine whether there is information contained in analysts' price targets that could be used to outperform the market. This paper employs an OLS regression model to determine if the analyst's predicted alpha, implied through the price target, is a good predictor of realized alpha. The resulting power of the model is significantly stronger than that employed in previous research which used statistical models as the predictor rather than analyst price targets. There is also evidence that some analyst's price targets contain more predictive power than others and some indication that this higher than average predicative power is persistent. This provides evidence that analyst price targets could be used in a portfolio construction model to outperform the S&P 500 on a risk-adjusted basis.
