Download or read book The Role of Other Information in Analysts Forecasts in Understanding Stock Return Volatility written by Yaowen Shan and published by . This book was released on 2013 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study proposes and validates “other information” in analysts' forecasts as a legitimate proxy for future cash flows, and examines its incremental role in explaining stock return volatility. We suggest that “other information” contains information about fundamentals beyond that reflected in current financial statements, and reflects firms' fundamentals on a more timely basis than dividends or earnings. The link between “other information” and volatility can be derived from a combination of the accounting version of the Campbell-Shiller model (Campbell and Shiller 1988a, 1988b; Vuolteenaho 2002) and Ohlson's (1995) linear information dynamics. Using standardized regressions we find volatility increases when current “other information” is more uncertain, and increases more in response to unfavorable news compared to favorable news. Variance decomposition analysis shows that the variance contribution of “other information” dominates that of expected-return news. The incremental role of “other information” is at least half of the effect of earnings in explaining future volatility. The results are valid for measures of both systematic and idiosyncratic volatility, and are more pronounced for firms with poor information environments. Overall, our results highlight the importance of including “other information” as an additional cash-flow proxy in future studies of stock prices and volatility.

Download or read book The Role of Non Accounting Information in Understanding Stock Return Volatility written by Yaowen Shan and published by . This book was released on 2018 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty about firms' future payoffs is the dominant factor in explaining stock return volatility at the firm level. However, summary financial statement numbers such as earnings only provide a limited measure of expected payoffs, as they do not reflect firms' fundamentals on a timely basis. We demonstrate theoretically and empirically that information about firms' fundamentals contained in analysts' forecasts (which we label as quot;non-accounting informationquot;) is expected to influence future stock return volatility. When combined with Ohlson's (1995) linear information dynamics, the accounting version of the Campbell-Shiller model (Campbell and Shiller 1988a, 1988b; Vuolteenaho 2002) implies that if current non-accounting information is more uncertain, then future stock returns are expected to be more volatile. Our empirical evidence supports the theoretical predictions, and the results are valid for measures of both systematic and idiosyncratic volatility. Additional analysis yields some evidence that both favourable and unfavourable news from non-accounting information increases future stock return volatility. Overall, our results highlight the relevance of information in analysts' forecasts beyond what is contained in the current financial statements.

Download or read book Analysts Forecasts and Future Stock Return Volatility written by Yaowen Shan and published by . This book was released on 2006 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting Volatility in the Financial Markets written by John L. Knight and published by Butterworth-Heinemann. This book was released on 2002 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modeling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.

Download or read book Financial Analysts Forecasts and Stock Recommendations written by Sundaresh Ramnath and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Financial Analysts and Information Processing on Financial Markets written by Jan-Philipp Matthewes and published by BoD – Books on Demand. This book was released on 2015-01-28 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial analysts play an ambivalent role on financial markets: On the one hand investors and the media frequently follow their advice, on the other hand they are regularly discredited when their forecasts or recommendations prove to be erroneous. This cumulative thesis explores the informational content of financial analysts’ forecasts for investors by addressing three specific topics: Consensus size as a rudimentary investment signal, the association of analysts’ target prices with business sentiment, and the consistency of analysts’ different investment signals in the context of the 2008 financial crisis. Overall, the thesis provides additional evidence that investors can profit from analysts’ forecasts and recommendations. However, it is also shown that investors need to be very selective about which signal to rely on and in which context to use these because analysts’ investment signals can also be heavily biased and erroneous. About the author: Jan-Philipp Matthewes studied ‘Economics’ at the University of Cologne, Germany, and holds a Dean’s Award from the Faculty of Economics and Social Sciences. His research focus on financial analysts evolved while working in equity research at a leading German bank. The PhD-thesis was supervised by Prof. Dr. Martin Wallmeier, Finance and Accounting, at the University of Fribourg, Switzerland. Since 2013 Jan-Philipp Matthewes is the managing director of the boutique private equity firm ‘Matthewes Capital Invest GmbH’.

Download or read book Analyst Forecast Dispersion and Future Stock Return Volatility written by Madhu Kalimipalli and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we examine the relationship between analysts' forecast dispersion and future stock return volatility using monthly data for a cross section of 160 US firms from 1981 to 1996. We find that there is a strong and positive relationship between analysts' forecast dispersion and future return volatility. The dispersion measure has incremental information content even after accounting for market volatility. These results are robust across sub-sample periods and sub-samples based on based on number of analysts following a firm, forecast dispersion and market capitalization. There is also a strong seasonal relationship between the dispersion measure and future volatility. The importance of dispersion on future return volatility is high in January and the first few months of the year, and declines thereafter. Such information content of analysts' earnings forecast dispersion is of great importance for active portfolio management, option pricing and arbitrage trading strategies.

Download or read book Correlated Beliefs Returns and Stock Market Volatility written by Joel M. David and published by . This book was released on 2015 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Firm-level stock returns exhibit comovement above that in fundamentals, and the gap tends to be higher in developing countries. We investigate whether correlated beliefs among sophisticated, but imperfectly informed, traders can account for the patterns of return correlations across countries. We take a unique approach by turning to direct data on market participants' information - namely, real-time firm-level earnings forecasts made by equity market analysts. The correlations of firm-level forecasts exceed those of fundamentals and are strongly related to return correlations across countries. A calibrated information-based model demonstrates that the correlation of beliefs implied by analyst forecasts leads to return correlations broadly in line with the data, both in levels and across countries - the correlation between predicted and actual is 0.63. Our findings have implications for market-wide volatility - the model-implied correlations alone can explain 44% of the cross-section of aggregate volatility. The results are robust to controlling for a number of alternative factors put forth by the existing literature.

Download or read book Stock Market Volatility written by Greg N. Gregoriou and published by CRC Press. This book was released on 2009-04-08 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel

Download or read book The Informational Role of Sell side Analysts Forecast Horizon written by Xuan Wang and published by . This book was released on 2019 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation explores the informational role of sell-side analysts' change in forecasting horizon. I find that portfolios formed by buying stocks with large increase in analyst horizon and shorting stocks with large decrease in analyst horizon generate superior future return. Horizon change has information incremental to analyst earnings forecast and recommendation revisions, as well as firm fundamentals. Large increase in horizon mainly drives the result. I find that analysts who contribute to strong horizon increase are associated with higher forecast accuracy. This increase is likely associated with the career concerns of inexperienced analysts. The return predictability associated with analyst forecast horizon change exists in the information environment of high liquidity and low volatility, at the times when analyst forecasts are the most accurate. Moreover, analyst forecast horizon is partially related to analysts' profitability prediction and firm risk assessment, although the horizon change, the component predictable by firm fundamentals notwithstanding, is still able to predict return in the short-run. Overall, the findings reported in this dissertation support the view that sell-side analysts are important rational-information providers in the financial industry.

Download or read book Understanding Analysts Use and Under Use of Stock Returns and Other Analysts Forecasts when Forecasting Earnings written by Michael B. Clement and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, we examine how analysts are affected by the public actions of investors and other analysts by closely examining how analysts revise their earnings forecasts after an earnings announcement. In particular, we hypothesize that analysts observe the actions of investors and other analysts in order to more accurately forecast earnings and have the expertise to determine when these actions are most informative about future earnings. Consistent with our hypotheses, we find that analysts revise their earnings forecasts more strongly in response to returns and other analysts' revisions when these signals are more informative about future earnings changes. We also find that, consistent with analysts being conservative while facing uncertain information, underreactions are strongest (not weakest) when analysts are responding most strongly to these signals (i.e., when the signals are most informative). Lastly, we find that analysts who are most sensitive to the informativeness of others' actions are relatively more accurate in forecasting earnings, suggesting that the ability to extract information from the actions of others serves as a source of expertise for at least some analysts.

Download or read book Financial Gatekeepers written by Yasuyuki Fuchita and published by Brookings Institution Press. This book was released on 2007-02-01 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Brookings Institution Press and Nomura Institute of Capital Markets Research publication Developed country capital markets have devised a set of institutions and actors to help provide investors with timely and accurate information they need to make informed investment decisions. These actors have become known as "financial gatekeepers" and include auditors, financial analysts, and credit rating agencies. Corporate financial reporting scandals in the United States and elsewhere in recent years, however, have called into question the sufficiency of the legal framework governing these gatekeepers. Policymakers have since responded by imposing a series of new obligations, restrictions, and punishments—all with the purpose of strengthening investor confidence in these important actors. Financial Gatekeepers provides an in-depth look at these new frameworks, especially in the United States and Japan. How have they worked? Are further refinements appropriate? These are among the questions addressed in this timely and important volume. Contributors include Leslie Boni (University of New Mexico), Barry Bosworth (Brookings Institution), Tomoo Inoue (Seikei University), Zoe-Vonna Palmrose (University of Southern California), Frank Partnoy (University of San Diego School of Law), George Perry (Brookings Institution), Justin Pettit (UBS), Paul Stevens (Investment Company Institute), Peter Wallison (American Enterprise Institute).

Download or read book Three Essays on Financial Analysts Stock Price Forecasts written by Quoc Tuan Quoc Ho and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mutual Fund Herding and Dispersion of Analysts Earnings Forecasts written by Kalok Chan and published by . This book was released on 2005 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: We examine the relation between herding of mutual funds and dispersion of analysts' earnings forecasts to ascertain whether it is the lack of information or the arrival of correlated information that induces herding. Results show that the level of herding in individual stocks is positively related to the dispersion measure. Herding is also related to other information quality variables such as stock return volatility and analyst coverage. Our results suggest that fund managers herd in response to lack of reliable information, rather than to exploit correlated fundamental information. Although market capitalization and trading volume are also related to herding, they seem to capture the firm characteristic to which mutual funds are attracted to (or repelled from). Our evidence indicates that buy- and sell-herding respond asymmetrically to information uncertainty. Sell-herding is more prevalent and is positively related to forecast dispersion. Buy-herding, on the other hand, is not related to dispersion. The asymmetric relationship between herding and information uncertainty is consistent with the quot;prospect theoryquot; and quot;sharing-of-the-blamequot; under bad news.

Download or read book Forecasting Volatility in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-02-24 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting Volatility in the Financial Markets, Third Edition assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey Leading thinkers present newest research on volatility forecasting International authors cover a broad array of subjects related to volatility forecasting Assumes basic knowledge of volatility, financial mathematics, and modelling

Download or read book Forecasting Daily Stock Volatility written by Ana-Maria Fuertes and published by . This book was released on 2013 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several recent studies advocate the use of nonparametric estimators of daily price variability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample fit analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Forecast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t-1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. The results have implications for value-at-risk analysis.

Download or read book The Effect of Analysts Forecasts on Stock Market Returns written by Stefano Bonini and published by . This book was released on 2009 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stock returns forecasting is one of the major objectives of financial analysts. Equity Analysts' forecasts, on the other side, are one of the major sources of information used by less informed investors in their asset allocation decisions. Therefore, analysing which major drivers affect time series of stock returns could allow to shed light over the price revelation process in capital markets. In this paper we propose a model aimed at predicting stock market by combining both macroeconomic and microeconomic factors. We first develop a standard APT approach with multiple macroeconomic factors as regressors. We then integrate the model by explicitly including a metric for intrinsic equity value, basing upon a proxy derived by the weighted average of Stock Market Consensus Forecasts by equity analysts. Third, we complete the model by imposing an ARMA specification for the error term, which allows identifying stock returns' stationarity moving over time. The resulting model shows both a strong fitting capability when tested in the in-sample period and a good predictive capability when applied to an out-of-sample period of monthly Italian stock market returns. In particular, we employed specific estimation procedures based upon recently developed statistics aimed at testing for both factors' equal predicting power and forecast encompassing. As a major empirical finding, our model suggests that the information conveyed by analysts' forecasts is indeed a factor in determining future stock prices, even if there is the possibility that the information transferred could be biased.