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Author: Marius del Giudice Rodriguez
Publisher:
ISBN:
Category : Corporate profits
Languages : en
Pages : 132
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Book Description
This dissertation contains three self-contained chapters dealing with specific aspects of financial analysts' earnings forecasts. After recent accounting scandals, much attention has turned to the incentives present in the career of professional financial analysts. The literature points to several reasons why financial analysts behave overoptimistically when providing their predictions. In particular, analysts may wish to maintain good relations with firm management, to please the underwriters and brokerage houses at which they are employed, and to broaden career choice. While the literature has focused more on analysts' strategic behavior in these situations, less attention has been paid to the implications these factors have on financial analysts' loss functions. The loss function dictates the criteria that analysts use in order to build their forecasts. Using a simple compensation scheme in which the sign of prediction errors affect their incomes differently, in the first chapter we examine the implications this has on their loss function. We show that depending on the contract offered, analysts have a strict preference for under-prediction or over-prediction and the size of this asymmetric behavior depends on the parameter that governs the financial analyst's preferences over wealth. This is turn affects the bias in their forecasts. Recent developments in the forecasting literature allow for the estimation of asymmetry parameters after observing data on forecasts. Moreover, they allow for a more general test of rationality once asymmetries are present. We make use of forecast data from financial analysts, provided by I/B/E/S, and present evidence of asymmetries and weak evidence against rationality. In the second chapter we study the evolution over time in the revisions to financial analysts' earnings estimates for the 30 Dow Jones firms over a 20 year period. If analysts' forecasts used information efficiently, earnings revisions should not be predictable. However, we find strong evidence that earnings revisions can in fact be predicted by means of the sign of the last revision or by using publicly available information such as short interest rates and past revisions. We propose a three-state model that accounts for the very different magnitude and persistence of positive, negative and `no change' revisions and find that this model forecasts earnings revisions significantly better than an autoregressive model. We also find that our forecasts of earnings revisions predict the actual earnings figure beyond the information contained in analysts' earnings estimates. Finally, the empirical literature on financial analysts' forecast revisions of corporate earnings has focused on past stock returns as the key determinant. The effects of macroeconomic information on forecast revisions is widely discussed, yet rarely tested in the literature. In the third chapter, we use dynamic factor analysis for large data sets to summarize a large cross-section of macroeconomic variables. The estimated factors are used as predictors of the average analyst's forecast revisions for different sectors of the economy. Our analysis suggests that factors extracted from macroeconomic variables do, indeed, improve on the current model with only past stock returns. In trying to explain what drives financial analysts' forecast revisions, the factors representing the macroeconomic environment must be considered to avoid a potential omitted variable problem. Moreover, the explanatory power and direction of such factors strongly depend on the industry in question.
Author: Marius del Giudice Rodriguez
Publisher:
ISBN:
Category : Corporate profits
Languages : en
Pages : 132
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Book Description
This dissertation contains three self-contained chapters dealing with specific aspects of financial analysts' earnings forecasts. After recent accounting scandals, much attention has turned to the incentives present in the career of professional financial analysts. The literature points to several reasons why financial analysts behave overoptimistically when providing their predictions. In particular, analysts may wish to maintain good relations with firm management, to please the underwriters and brokerage houses at which they are employed, and to broaden career choice. While the literature has focused more on analysts' strategic behavior in these situations, less attention has been paid to the implications these factors have on financial analysts' loss functions. The loss function dictates the criteria that analysts use in order to build their forecasts. Using a simple compensation scheme in which the sign of prediction errors affect their incomes differently, in the first chapter we examine the implications this has on their loss function. We show that depending on the contract offered, analysts have a strict preference for under-prediction or over-prediction and the size of this asymmetric behavior depends on the parameter that governs the financial analyst's preferences over wealth. This is turn affects the bias in their forecasts. Recent developments in the forecasting literature allow for the estimation of asymmetry parameters after observing data on forecasts. Moreover, they allow for a more general test of rationality once asymmetries are present. We make use of forecast data from financial analysts, provided by I/B/E/S, and present evidence of asymmetries and weak evidence against rationality. In the second chapter we study the evolution over time in the revisions to financial analysts' earnings estimates for the 30 Dow Jones firms over a 20 year period. If analysts' forecasts used information efficiently, earnings revisions should not be predictable. However, we find strong evidence that earnings revisions can in fact be predicted by means of the sign of the last revision or by using publicly available information such as short interest rates and past revisions. We propose a three-state model that accounts for the very different magnitude and persistence of positive, negative and `no change' revisions and find that this model forecasts earnings revisions significantly better than an autoregressive model. We also find that our forecasts of earnings revisions predict the actual earnings figure beyond the information contained in analysts' earnings estimates. Finally, the empirical literature on financial analysts' forecast revisions of corporate earnings has focused on past stock returns as the key determinant. The effects of macroeconomic information on forecast revisions is widely discussed, yet rarely tested in the literature. In the third chapter, we use dynamic factor analysis for large data sets to summarize a large cross-section of macroeconomic variables. The estimated factors are used as predictors of the average analyst's forecast revisions for different sectors of the economy. Our analysis suggests that factors extracted from macroeconomic variables do, indeed, improve on the current model with only past stock returns. In trying to explain what drives financial analysts' forecast revisions, the factors representing the macroeconomic environment must be considered to avoid a potential omitted variable problem. Moreover, the explanatory power and direction of such factors strongly depend on the industry in question.
Author: Dong Hyun Son
Publisher:
ISBN:
Category : Business analysts
Languages : en
Pages : 130
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Author: Quoc Tuan Quoc Ho
Publisher:
ISBN:
Category :
Languages : en
Pages :
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In this thesis, I study three aspects of sell-side analysts' stock price forecasts, henceforth target prices: analyst teams' target price forecast characteristics, analysts' use of information to revise target prices, and determinants of target price disagreement between analysts. The first essay studies the target price forecast performance of team analysts in the UK and finds that teams issue timelier but not less accurate target prices. Unlike evidence from previous studies, my findings suggest that analyst teamwork may improve forecast timeliness without sacrificing forecast accuracy. However, market reactions to team target price revisions are not significantly different from those to individual analyst target price revisions, suggesting that although target prices issued by analyst teams are timelier and not less accurate than those of individual analysts, investors do not consider analyst team target prices more informative. I conjecture that analysts may work in teams to meet the demand to cover more companies while maintaining the quality of research by individual team members rather than to issue more informative reports. In the second essay, I study how analysts revise their target prices in response to new information implicit in recent market returns, stock excess returns and other analysts' target price revisions. The results suggest that analysts' target price revisions are significantly influenced by market returns, stock excess return and other analysts' target price revisions. I also find that the correlation between target price revisions and stock excess returns is significantly higher when the news implicit in these returns is bad rather than good. I conjecture that analysts discover more bad news from the information in stock excess returns because firms tend to withhold bad news, disclosing it only when it becomes inevitable, while they disclose good news early. Using a new measure of bad to good news concentration, I show that the asymmetric responsiveness of target price revisions to positive and negative stock excess returns is significant for firms with the highest concentration of bad news but is insignificant for firms with the lowest concentration of bad news. I argue that firms with the highest concentration of bad news are more likely to withhold and accumulate bad news. The findings, therefore, support my hypothesis that analysts discover more bad news than good news from stock returns because firms tend to withhold bad news, disclosing it only when it is inevitable. The third essay examines the determinants of analyst target price disagreement. I find that while disagreement in short-term earnings and in long-term earnings growth forecasts are significant determinants, recent 12-month idiosyncratic return volatility has the strongest explanatory power for target price disagreement. The findings suggest that target price disagreement is driven not only by analyst disagreement about short-term earnings and long-term earnings growth, but also by differences in analysts' opinions about the impact of recent firm-specific events on value drivers beyond short-term future earnings and long-term growth, which are eventually reflected in past idiosyncratic return volatility.
Author: Dorothy Alexander-Smith
Publisher:
ISBN:
Category : Business forecasting
Languages : en
Pages : 143
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Essay 1: The Association of Earnings Quality with Financial Analysts' Earnings Forecast Attributes. This study investigates the association between firms' earnings quality and analysts' forecast errors and dispersion. The findings suggest that the quality of earnings is inversely related to analysts' forecast errors but is not associated with forecast dispersion. These results are better understood by an examination of the relationship of forecast error and dispersion with the major sub-components of earnings quality- the quality of the innate accrual component (quality of accruals related to the complexity of the firm's operations) and the quality of the discretionary accrual component (quality of managements' judgment as reflected in accruals used to project future performance). The inverse association between earnings quality and forecast error is driven primarily by the quality of the firm's innate accrual component (InnAQ). As firm complexity and variability increase, earnings contain larger amounts of management judgment and estimation. The larger amount of management estimation included in earnings renders it relatively less reliable and thus forecasting difficulty (reflected in greater forecast errors and dispersion) is amplified for poorer InnAQ. This inverse association is the dominant effect in earnings quality's association with analysts' forecast errors. The quality of firms' discretionary accrual components depends upon whether managers use of their discretion to provide value relevant information, or whether they use the discretionary component to incorporate manipulative and noisy discretionary accruals. In a regression of the of firms' discretionary earnings components on forecast dispersion I find an inverse relationship between the magnitude of the firm's discretionary earnings component and analysts' forecast dispersion. This is consistent with managers using the discretionary component to provide information on firm performance, thus facilitating more precision in analysts' forecasts. This essay contributes to two controversial areas of accounting research. The study indirectly provides evidence supporting managers' (on average) use of their discretion to provide value relevant information in earnings; and it simultaneously demonstrates analysts' expertise in incorporating information related to EQ and its sub components into their forecasts. Essay 2: The Influence of Earnings Quality on Financial Analysts' Herding Behavior. Essay 2 investigates how firms' EQ and its innate (the quality of accruals related to the complexity of the firm's operations) and discretionary (the quality of accruals based on managements' discretion) sub-components affect analysts' motivation to issue herding forecasts. Herding forecasts are forecasts which mimic those issued by other analysts and ignore the analyst's own private information. Although theoretical studies have linked herding behavior to analysts' rational reputational concerns, herding reduces the information available to investors in the market and hence negatively impacts market efficiency. Conversely, bold forecasts, forecasts issued which move away from the consensus (linked in prior studies to greater private information release and higher accuracy) are likely to contribute to improved market efficiency. As capital market intermediaries, financial analysts are charged with facilitating investors' investment decisions. The literature documents that poor earnings quality reduces investors' ability to evaluate firm performance. This essay contributes to the literature by providing evidence on how financial analysts' herding behavior is influenced by EQ and its sub components. Results show that the quality of the firm's innate accrual component is the major driver of analysts' bold forecasting. The negative association between forecast boldness and firms' innate accrual quality indicates that analysts issue bolder forecasts when investors have more difficulty determining firm value (noisier signal from innate accrual component). Given the prior literature finds that bolder forecasts contain more private information and are more accurate, the results suggests that analysts are effectively performing their market intermediary function. The lack of a significant association between bold forecasting and the discretionary earnings component is in line with prior literature's documentation of analysts' poor utilization of the discretionary information in their forecasts. However, this study's evidence of a positive association between bold forecasts and analysts' firm specific experience implies that analysts with more firm specific experience have a greater understanding of managers' discretionary signals and exploit their advantage by issuing bolder forecasts. Results show a negative association between firms' overall EQ and analysts' forecast boldness implying that analysts herd more the higher the firm's EQ. This finding underscores the importance of reputational concerns and the demand for analysts' investment advice for analysts' herding behavior.
Author: Wenjuan Xie
Publisher:
ISBN:
Category :
Languages : en
Pages : 138
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Author: Zhu Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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"The dissertation consists of two essays in financial analysts and one essay in corporate disclosure, all utilizing textual analysis. In the first essay, I decompose analysts’ estimates of weighted average cost of capital (WACC) into abnormal and expected components using a risk characteristic-based model. I find that the abnormal component predicts future stock returns, especially when combined with EPS and dispersion of EPS forecasts. Additional analysis shows that the abnormal component of WACC predicts underlying firms’ future fundamental performance, particularly for experienced analysts and firms with low information intensity. My findings highlight that the abnormal component of analysts’ WACC estimates is informative. Analysts’ decision process to map their forecast inputs such as EPS forecasts and risk assessment to their investment opinions such as target price and recommendation remains to be a black box in the previous literature. In the second essay, I find that analysts’ estimate of WACC is negatively associated with their target price forecasts. It provides empirical evidence that analysts would rationalize the DCF model. From the investor’s perspective, I find that investors generally overreact to the information in WACC estimates when evaluating analysts’ target price forecasts. The extent of the overreaction depends on whether target price changes are conflicted by WACC changes. In light of psychological theories, I provide empirical evidence that when the investors' optimistic verifiable expectation is rejected, they switch to the unverifiable component - WACC for information. At last, I show similar empirical evidence for analyst recommendation.In the third essay, using 4,262 Form 20-F filings from 37 countries, we find that corporate risk-taking is positively associated with managerial expectation as measured by forward-looking statement (FLS) tone, particularly for firms from countries with strong institutions and for FLS tone related to macroeconomics. Our study advances the measure of overall managerial expectations and links it to corporate risk-taking in an international setting"--
Author: Alexander von Nandelstadh
Publisher:
ISBN: 9789515557865
Category :
Languages : en
Pages : 131
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Author: Seongyeon Lim
Publisher:
ISBN:
Category : Investment analysis
Languages : en
Pages :
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Abstract: This dissertation studies how psychological and reputational considerations affect the behavior of individual investors and security analysts. The first essay examines investors' preference for framing their gains and losses using trading records of individual investors at a large discount brokerage firm. I find that investors tend to bundle sales of losers on the same day and separate sales of winners over different days. The result is consistent with the principles of mental accounting (Thaler (1985)), according to which individuals attain higher utility by integrating losses and segregating gains. Alternative explanations based on tax-loss selling strategies, margin calls, the number of winners and losers in a portfolio, the difference in the potential proceeds from selling winners and losers, and correlations among winners and losers in a portfolio do not fully account for the observed behavior. Logistic analyses show that investors are more likely to sell multiple stocks when they realize losses, after controlling for various factors including market and portfolio returns, overall sales activity during the day, and investor characteristics. The second essay provides a theoretical and empirical analysis of analysts' incentives to incorporate public information in their earnings forecasts. The model show that analysts may underreact to public news due to their reputational concerns, and that an analyst's incentive to underreact to public information 1) decreases with the size of unexpected news; 2) decreases with the uncertainty of earnings; 3) increases with the analyst's initial reputation; and 4) increases with how much the analyst values his/her current reputation relative to forecast accuracy. I test the implications of the model and find that analysts underreact to earnings news less when the size of unexpected earnings is large, when there is more uncertainty about the earnings, and when they have long track records. The model also implies that the strategic biases of analysts can lead to divergent responses of forecasts to public announcements. Furthermore, the stock market may react to revisions in analysts' forecasts made in response to information that has already been incorporated into stock prices.
Author: Zhongwei Huang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This dissertation consists of three chapters that present three standalone essays on the monitoring role of financial analysts. Chapter 1 investigates the monitoring role of financial analysts in the financial reporting process by examining the informativeness and monitoring effect of their written comments on earnings quality. I find that these comments have incremental predictability with respect to future accounting restatements, and convey information to investors beyond that in the earnings forecasts, stock ratings, price targets, and other qualitative text in analyst reports. Further analyses suggest that the market's reaction to these comments is primarily driven by negative comments and comments written with certainty. In addition, controlling for accrual reversals, I find that firms significantly reduce the level of accruals-based earnings management after receiving negative comments, and this reduction is not accompanied by an increase in real activities management. Overall, the first chapter provides direct evidence on analysts' monitoring role in financial reporting. Chapter 2 examines whether and how analysts' monitoring of the financial reporting process alleviates a well-known agency problem in which a manager inflates her compensation by manipulating earnings. I argue that analysts' monitoring reduces a manager's ability to conceal earnings management from directors, thus facilitating directors' adjustment of executive compensation in the presence of earnings management. Consistent with this argument, I find that earnings carry a lower weight in the determination of CEO compensation in firms that are criticized by analysts regarding earnings quality, but only when directors are likely to be aware of the critical analyst reports. The main findings are robust to matching on performance and controlling for firm-fixed effects and are not driven by other text in the analyst reports. Additional analyses suggest that the weight placed on earnings decreases as the actual accruals deviate from analysts' accruals forecasts. Overall, the second chapter emphasizes analysts' monitoring role in alleviating managerial rent extraction in executive compensation. Chapter 3 provides evidence on the impact of recent analyst independence reforms (the National Association of Securities Dealers [NASD] Rule 2711 and the companion New York Stock Exchange [NYSE] Rule 472 Amendment, and the Global Settlement) on analysts' monitoring role in the financial reporting process. The NASD Rule 2711 requires brokerage firms to structurally separate investment banking from equity research; meanwhile, the Global Settlement mandates the participating banks to fund independent research firms to the amount of 432.5 million dollars from 2004 to 2009. I find evidence consistent with an increase in analysts' monitoring effectiveness following the reforms. Further analyses suggest that this increase is primarily driven by the Global Settlement, rather than by the adoption of NASD Rule 2711. The evidence is robust to a difference-in-difference specification with Canadian firms as the control group. Moreover, I document a reversal of the increase in monitoring effectiveness following the end of the Global Settlement's five-year funding. Overall, the third chapter highlights the interaction between the monitoring role of financial analysts and the regulatory environment.
Author: Ritong Qu
Publisher:
ISBN:
Category :
Languages : en
Pages : 230
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My thesis has two themes: The first theme is about studying investors' expectations and the relation to asset prices; while the second theme is about evaluating forecasting performance. Both themes focus on what we can learn from a panel of data. The first chapter of my dissertation studies rational investors' expectation of consumption growth at the presence of structure breaks and asset pricing implications. While the first chapter studies how rational individuals should do, the second and third chapters focus on forecasters' behavior in real world, by developing tools to evaluate forecasters' performance about multiple variables, across many forecasters and at single time periods. In Chapter 1, we use data on multiple consumption goods to identify infrequent, but persistent breaks to consumption growth dynamics. Over a sixty-year sample, we find four breaks, all of which are associated with major macroeconomic and financial market events such as oil price shocks, the Great Moderation, the end of the tech stock market bubble, and the Covid pandemic. The impact of the breaks on consumption growth is highly uncertain and heterogeneous across consumption goods. We explore the asset pricing implications of our novel empirical evidence in the context of a Lucas tree model in which investors use information on multiple consumption goods to learn about model parameters. We find that break risk in consumption growth, combined with investor learning, helps resolve a number of asset pricing puzzles such as high risk premium and volatility of market returns, as well as cross-sectional anomalies such as momentum. Chapter 2 is joint work with Allan Timmermann and Yinchu Zhu. Forecasting skills are often identified by comparing predictive accuracy across large numbers of forecasts. This generates a multiple hypothesis testing problem that can trigger many false positives. We develop a new bootstrap test approach for identifying superior predictive accuracy that applies to multi-dimensional panel settings with arbitrarily many forecasts, outcome variables, horizons, and time periods. Our approach controls the family-wise error rate while retaining the ability to identify truly skilled forecasters. An empirical analysis of the IMF's World Economic Outlook forecasts across 185 countries, five variables and several forecast horizons shows how our approach can be used to identify variables and countries for which the IMF's forecasts improve significantly at shorter horizons as well as cases where they fail to improve. Chapter 3 is also joint work with Allan Timmermann and Yinchu Zhu. We develop new methods for pairwise comparisons of predictive accuracy with cross-sectional data. Using a common factor setup, we establish conditions on cross-sectional dependencies in forecast errors which allow us to test the null of equal predictive accuracy on a single cross-section of forecasts. We consider both unconditional tests of equal predictive accuracy as well as tests that condition on the realization of common factors and show how to decompose forecast errors into exposures to common factors and idiosyncratic components. An empirical application compares the predictive accuracy of financial analysts' short-term earnings forecasts across six brokerage firms.
