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Author: Alexander von Nandelstadh
Publisher:
ISBN: 9789515557865
Category :
Languages : en
Pages : 131
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Book Description
Author: Alexander von Nandelstadh
Publisher:
ISBN: 9789515557865
Category :
Languages : en
Pages : 131
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Book Description
Author: Sundaresh Ramnath
Publisher: Now Publishers Inc
ISBN: 1601981627
Category : Business & Economics
Languages : en
Pages : 125
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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.
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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Book Description
Author: Sundaresh Ramnath
Publisher:
ISBN:
Category :
Languages : en
Pages : 117
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Book Description
This paper reviews research regarding the role of financial analysts in capital markets. The paper builds on the perspectives provided by Schipper (1991) and Brown (1993). We categorize papers published mainly since 1992 and selectively discuss aspects of these papers that address or suggest key research topics of ongoing interest in seven broad areas: analysts' decision processes, the determinants of analyst expertise and distributions of individual analysts' forecasts, the informativeness of analysts' research outputs, analyst and market efficiency with respect to information, effects of analysts' economic incentives on their research outputs, effects of the institutional and regulatory environment (including cross-country comparisons), and the limitations of databases and various research paradigms.
Author: Quoc Tuan Quoc Ho
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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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Book Description
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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Book Description
Author: Jon Danielsson
Publisher: John Wiley & Sons
ISBN: 1119977118
Category : Business & Economics
Languages : en
Pages : 307
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Book Description
Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.
Author: Cheng-Few Lee
Publisher: Center for PBBEFR & Airiti Press
ISBN: 9868430763
Category : Business & Economics
Languages : en
Pages : 302
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Book Description
Advances in Quantitative Analysis of Finance and Accounting (New Series) is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting as well as applications of quantitative methods to problems in financial management, financial accounting, and business management. The objective is to promote interaction between academic research in finance and accounting and applied research in the financial community and the accounting profession. The papers in this volume cover a wide range of topics including corporate finance and debt management, earnings management, equity market, auditing, option pricing theory, and interest rate theory. In this volume there are eleven chapters, five of them are corporate finance and debt management: 1. Liquidity and Adverse Selection: Evidence from the Five-or-Fewer Rule Change; 2. Changing Business Environment and the Value of Relevance of Accounting Information; 3. Pricing Risky Securities in Hidden Markov-Modulated Poisson Processes; 4. An Empirical Assessment of Alternative Dividend Expectation Models; 5. Quantitative Market Risk Disclosure, Bond Default Risk and The Cost of Debt: Why Value At Risk? There are two of the other six chapters which cover interest rate theory: 1. Positive Interest Rates and Yields: Additional Serious Considerations; 2. Collapse of Dimensionality in the Interest Rate Term Structure. The remaining four chapters cover financial analysts earnings forecasts, equity market, auditing, and option pricing theory. These four papers are: 1. Investors’ Apparent Under-weighting of Financial Analysts’ Earnings Forecasts: The Role of Share Price Scaling and Omitted Risk Factors; 2. Predicting Stock Price by Applying the Residual Income Model and Bayesian Statistics; 3. Intertemporal Associations Between Non-Audit Services and Auditors’ Tendency to Allow Discretionary Accruals; 4. Put Option Portfolio Insurance vs. Asset Allocation.
