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| Author | : Mr. Eric Chi-Ying So |
| Publisher | : |
| Total Pages | : |
| Release | : 2012 |
| Genre | : |
| ISBN | : |
Download A New Approach to Predicting Analyst Forecast Errors Book in PDF, ePub and Kindle
I provide evidence that investors overweight analyst forecasts by demonstrating that prices do not fully reflect predictable components of analyst errors, which conflicts with conclusions in prior research. I highlight estimation bias in traditional approaches and develop a new approach that reduces this bias. I estimate 'characteristic forecasts' that map current firm characteristics into forecasts of future earnings. Contrasting characteristic and analyst forecasts predicts analyst forecast errors and revisions. I document abnormal returns to strategies that sort firms by predicted forecast errors, consistent with investors overweighting analyst forecasts and predictable biases in analyst forecasts influencing the information content of prices.
| Author | : Rob J Hyndman |
| Publisher | : OTexts |
| Total Pages | : 380 |
| Release | : 2018-05-08 |
| Genre | : Business & Economics |
| ISBN | : 0987507117 |
Download Forecasting: principles and practice Book in PDF, ePub and Kindle
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
| Author | : Lawrence D. Brown |
| Publisher | : |
| Total Pages | : 8 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
Download Analyst Forecasting Errors and Their Implications for Security Analysis Book in PDF, ePub and Kindle
Dreman and Berry (1995) have offered a perspective on analyst earnings forecast errors and their implications for security analysis. Among other arguments, they contend that the errors are too large to be reliably used by investors, the forecasts are less accurate than forecasts by time-series models, the errors are increasing over time, the analysts' forecasts are too optimistic, and the investment community relies too heavily on analyst forecasts. An alternative perspective on these issues is offered. The argument is that analysts' forecast errors are within 3% of an appropriate benchmark (namely, stock price), that their forecasts generally are significantly more accurate than forecasts by naive or sophisticated time-series models, that analyst forecast errors have not been increasing over time, that analysts have been too pessimistic in recent years, and that the investment community, by placing too much weight on forecasts made by time-series models, relies too little on analysts' forecasts.
| Author | : Michael Gilliland |
| Publisher | : John Wiley & Sons |
| Total Pages | : 419 |
| Release | : 2016-01-05 |
| Genre | : Business & Economics |
| ISBN | : 111922456X |
Download Business Forecasting Book in PDF, ePub and Kindle
A comprehensive collection of the field's most provocative, influential new work Business Forecasting compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative ideas from forecasting researchers and practitioners, on topics including accuracy metrics, benchmarking, modeling of problem data, and overcoming dysfunctional behaviors. Its coverage includes often-overlooked issues at the forefront of research, such as uncertainty, randomness, and forecastability, as well as emerging areas like data mining for forecasting. The articles present critical analysis of current practices and consideration of new ideas. With a mix of formal, rigorous pieces and brief introductory chapters, the book provides practitioners with a comprehensive examination of the current state of the business forecasting field. Forecasting performance is ultimately limited by the 'forecastability' of the data. Yet failing to recognize this, many organizations continue to squander resources pursuing unachievable levels of accuracy. This book provides a wealth of ideas for improving all aspects of the process, including the avoidance of wasted efforts that fail to improve (or even harm) forecast accuracy. Analyzes the most prominent issues in business forecasting Investigates emerging approaches and new methods of analysis Combines forecasts to improve accuracy Utilizes Forecast Value Added to identify process inefficiency The business environment is evolving, and forecasting methods must evolve alongside it. This compilation delivers an array of new tools and research that can enable more efficient processes and more accurate results. Business Forecasting provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes.
| Author | : Tatiana Fedyk |
| Publisher | : |
| Total Pages | : 30 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
Download Refining Financial Analysts' Forecasts by Predicting Earnings Forecast Errors Book in PDF, ePub and Kindle
Prior research on financial analyst' quarterly earnings forecasts has documented serial correlation in forecast errors. This paper examines the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm's industry and the analyst's experience and brokerage house affiliation. Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, I model consensus forecast errors as an autoregressive process. I demonstrate that the model of forecast errors that best fits the data is AR(1), and use the obtained autoregressive coefficients to predict consensus forecast errors. Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors, and proposes a series of refinements to the consensus. These refinements were not presented in prior literature, and can be useful to financial analysts and investors.
| Author | : Till Weigt |
| Publisher | : |
| Total Pages | : |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
Download A New Combination Approach to Reducing Forecast Errors with an Application to Volatility Forecasting Book in PDF, ePub and Kindle
| Author | : Cintia M. Easterwood |
| Publisher | : |
| Total Pages | : |
| Release | : 2009 |
| Genre | : |
| ISBN | : |
Download New Evidence on Serial Correlation in Analyst Forecast Errors Book in PDF, ePub and Kindle
We reexamine the serial correlation of forecast errors using a method that allows analysts to react differently to good and bad news. Our method also controls for the influence of a normal non-zero, firm-specific component of forecast error. Our results indicate that forecast errors exhibit positive serial correlation when there is bad news in the prior forecast error, negative serial correlation when there is good news in the prior forecast error, and no serial correlation when there is no news in the prior forecast error. These findings are consistent with analysts having optimistic reactions to new information.
| Author | : Kenneth C. Land |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 376 |
| Release | : 2012-12-06 |
| Genre | : Science |
| ISBN | : 9400940114 |
Download Forecasting in the Social and Natural Sciences Book in PDF, ePub and Kindle
Social and natural scientists often are called upon to produce, or participate, in the pro duction of forecasts. This volume assembles essays that (a) describe the organizational and political context of applied forecasting, (b) review the state-of-the-art for many fore casting models and methods, and (c) discuss issues of predictability, the implications of forecaSt errors, and model construction, linkage and verification. The essays should be of particular interest to social and natural scientists concerned with forecasting large-scale systems. This project had its origins in discussions of social forecasts and forecasting method ologies initiated a few years ago by several social and natural science members of the Social Science Research Council's Committee on Social Indicators. It became appar ent in these discussions that certain similar problems were confronted in forecasting large-scale systems-be they social or natural. In response, the Committee hypothesized that much could be learned through more extended and systematic interchanges among social and natural scientists focusing on the formal methodologies applied in forecasting. To put this conjecture to the test, the Committee sponsored a conference at the National Center for Atmospheric Research in Boulder, Colorado, on June 10-13, 1984, on forecasting in the social and natural sciences. The conference was co-chaired by Committee members Kenneth C. Land and Stephen H. Schneider representing, respectively, the social and natural science mem bership of the Committee. Support for the conference was provided by a grant to the Council from the Division of Social and Economic Science of the National Science Foundation.
| Author | : Patricia C. O'Brien |
| Publisher | : Forgotten Books |
| Total Pages | : 134 |
| Release | : 2018-03-07 |
| Genre | : Mathematics |
| ISBN | : 9780364062012 |
Download Analysts' Forecasts as Earnings Expectations (Classic Reprint) Book in PDF, ePub and Kindle
Excerpt from Analysts' Forecasts as Earnings Expectations A third contribution of this paper is a methodological refinement of the techniques used to evaluate forecastsp I demonstrate the existence of significant time-period - specific effects in forecast errors. If time series and cross-section data are pooled without taking these effects into account, the statistical results may be overstated, and the results are subject to an aggregation bias. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
| Author | : Ching-Wai (Jeremy) Chiu |
| Publisher | : |
| Total Pages | : 28 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
Download A New Approach for Detecting Shifts in Forecast Accuracy Book in PDF, ePub and Kindle
Forecasts play a critical role at inflation-targeting central banks, such as the Bank of England. Breaks in the forecast performance of a model can potentially incur important policy costs. Commonly used statistical procedures, however, implicitly put a lot of weight on type I errors (or false positives), which result in a relatively low power of tests to identify forecast breakdowns in small samples. We develop a procedure which aims at capturing the policy cost of missing a break. We use data-based rules to find the test size that optimally trades off the costs associated with false positives with those that can result from a break going undetected for too long. In so doing, we also explicitly study forecast errors as a multivariate system. The covariance between forecast errors for different series, though often overlooked in the forecasting literature, not only enables us to consider testing in a multivariate setting but also increases the test power. As a result, we can tailor the choice of the critical values for each series not only to the in-sample properties of each series but also to how the series for forecast errors covary.
