The Performance of Mechanical Earnings Forecasts PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download The Performance of Mechanical Earnings Forecasts PDF full book. Access full book title The Performance of Mechanical Earnings Forecasts by Dieter Hess. Download full books in PDF and EPUB format.
Author: Dieter Hess Publisher: ISBN: Category : Languages : en Pages : 46
Book Description
We analyze three different mechanical models to forecast earnings and compare their forecasts with those of analysts. Moreover, we evaluate implied cost of capital (ICC) estimates that are based on these forecasts. With our analyses we answer three open questions in the literature. 1) Do model forecasts or analysts' forecasts perform better? 2) Are ICCs derived from analysts' forecasts more reliable than ICCs based on model forecasts? And 3) does higher forecast performance also translate into more reliable ICCs? First, we find that analysts' forecasts are even more accurate than the most accurate model forecasts. However, second, we find that model-based ICCs are always more reliable than analyst-based ICCs. Moreover, model-based ICCs are particularly reliable for a sample of firms for which no analysts' forecasts are available. While the lack of reliability of analyst-based ICCs seems to indicate a missing link between forecast performance and ICC reliability, in fact, third, we find that ceteris paribus higher forecast performance translates into more reliable ICCs, that is, within one earnings definition the most accurate forecasts also yield the most reliable ICCs.
Author: Dieter Hess Publisher: ISBN: Category : Languages : en Pages : 46
Book Description
We analyze three different mechanical models to forecast earnings and compare their forecasts with those of analysts. Moreover, we evaluate implied cost of capital (ICC) estimates that are based on these forecasts. With our analyses we answer three open questions in the literature. 1) Do model forecasts or analysts' forecasts perform better? 2) Are ICCs derived from analysts' forecasts more reliable than ICCs based on model forecasts? And 3) does higher forecast performance also translate into more reliable ICCs? First, we find that analysts' forecasts are even more accurate than the most accurate model forecasts. However, second, we find that model-based ICCs are always more reliable than analyst-based ICCs. Moreover, model-based ICCs are particularly reliable for a sample of firms for which no analysts' forecasts are available. While the lack of reliability of analyst-based ICCs seems to indicate a missing link between forecast performance and ICC reliability, in fact, third, we find that ceteris paribus higher forecast performance translates into more reliable ICCs, that is, within one earnings definition the most accurate forecasts also yield the most reliable ICCs.
Author: Philipp Zacharias-Langhans Publisher: ISBN: Category : Languages : en Pages :
Book Description
This study aims to compare the performance of earnings forecasts from various cross-sectional models and the consensus of financial analysts for the European setting. My findings indicate that the models of Harris and Wang (2018) and Azevedo et al. (2017) are able to outperform raw consensus analyst forecasts both in terms of bias and accuracy, while analyst forecasts still contain information that is not incorporated in pure model forecasts. Further, I show that the accuracy of earnings forecasts is significantly impacted by the underlying earnings definition, and therefore argue that studies that use varying earnings definitions in their comparison are inconclusive.
Author: Publisher: GRIN Verlag ISBN: 3668963924 Category : Business & Economics Languages : en Pages : 16
Book Description
Seminar paper from the year 2018 in the subject Business economics - Investment and Finance, grade: 2,7, University of Cologne, course: Bachelorseminar Corporate Finance, language: English, abstract: This paper seeks to examine different models to forecast revenue of companies. This is being achieved by examining costs of capital, which are a good representative therefor. The models examined in this paper can be divided into two sections. First, there are mechanical models, second there is one characteristic-based model. The models stand in contrast to analysts’ forecasts. This paper sums up different authors who illustrate, that mechanical models outperform analysts’ forecasts in terms of revenue forecasting. First, the HVZ mode is introduced which is due to outperform analysts’ forecasts. Second, the EP and RI model are introduced, next to a random walk model (RW model) as a benchmark. Objective of this paper is to find out which advantages go along with mechanical models, and whether the quality of forecast could be influenced positively. The topic of revenue forecast is highly relevant for different stakeholders in the financial industry. Based on revenue forecasts investment decisions are met by investors. One advantage of mechanical models therefore, is the greater feasibility due to the greater coverage. Mechanical models rely on firm fundamentals and are hence available for much more companies. Analysts’ forecasts are only available for firms of a certain size upwards. Costs of capital are a topic of focus not only for investment decisions but also for internal application. Apart from the use as a financial ratio it is negatively associated with customer satisfaction. The paper finds out, that the HVZ model outperforms analysts’ forecasts in terms of forecast bias and earnings response coefficient. However, the HVZ model does not outperform analysts’ forecasts in terms of accuracy. The EP and RI model both outperform the HVZ model in terms of all three criteria: forecast bias, earnings response coefficient and accuracy. The characteristic-based model sets up a linear function solely by firm fundamentals, that avoids including unobservable future covariances. Besides, it concludes certain key findings about abnormal earnings volatility and economy-wide risk.
Author: Labor Dept. (U.S.), Bureau of Labor Statistics Publisher: Bureau of Labor Statistics ISBN: 9780160843174 Category : Business & Economics Languages : en Pages : 900
Book Description
An important resource for employers, career counselors, and job seekers, this handbook contains current information on today's occupations and future hiring trends, and features detailed descriptions of more than 250 occupations. Find out what occupations entail their working conditions, the training and education needed for these positions, their earnings, and their advancement potential. Also includes summary information on 116 additional occupations.
Author: Gordon J. Alexander Publisher: ISBN: Category : Investment analysis Languages : en Pages : 904
Book Description
This introductory text provides a clear framework for understanding and analyzing securities. It also covers the major institutional features and theories of investing in the current economy. This edition has a more international perspective, reflecting the authors' belief that the field of investment is destined to become more global than it currently is.
Author: Dieter Hess
Author: Dieter Hess
Author: Philipp Zacharias-Langhans
Author: 
Author: Philip Brown
Author: Ling Lei
Author: Don Ricketts
Author: 
Author: Labor Dept. (U.S.), Bureau of Labor Statistics
Author: Warren H. Beckcom
Author: Gordon J. Alexander