Download or read book New Determinants of Analysts Earnings Forecast Accuracy written by Tanja Klettke and published by Springer Science & Business. This book was released on 2014-04-28 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial analysts provide information in their research reports and thereby help forming expectations of a firm’s future business performance. Thus, it is essential to recognize analysts who provide the most precise forecasts and the accounting literature identifies characteristics that help finding the most accurate analysts. Tanja Klettke detects new relationships and identifies two new determinants of earnings forecast accuracy. These new determinants are an analyst’s “general forecast effort” and the “number of supplementary forecasts”. Within two comprehensive empirical investigations she proves these measures’ power to explain accuracy differences. Tanja Klettke’s research helps investors and researchers to identify more accurate earnings forecasts.
Download or read book Determinants of Earnings Forecast Error Earnings Forecast Revision and Earnings Forecast Accuracy written by Sebastian Gell and published by Springer Science & Business Media. This book was released on 2012-03-26 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Earnings forecasts are ubiquitous in today’s financial markets. They are essential indicators of future firm performance and a starting point for firm valuation. Extremely inaccurate and overoptimistic forecasts during the most recent financial crisis have raised serious doubts regarding the reliability of such forecasts. This thesis therefore investigates new determinants of forecast errors and accuracy. In addition, new determinants of forecast revisions are examined. More specifically, the thesis answers the following questions: 1) How do analyst incentives lead to forecast errors? 2) How do changes in analyst incentives lead to forecast revisions?, and 3) What factors drive differences in forecast accuracy?
Download or read book Forecasting principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Analyzing the Analysts written by United States. Congress. House. Committee on Financial Services. Subcommittee on Capital Markets, Insurance, and Government Sponsored Enterprises and published by . This book was released on 2001 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimating the Cost of Capital Implied by Market Prices and Accounting Data written by Peter Easton and published by Now Publishers Inc. This book was released on 2009 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating the Cost of Capital Implied by Market Prices and Accounting Data focuses on estimating the expected rate of return implied by market prices, summary accounting numbers, and forecasts of earnings and dividends. Estimates of the expected rate of return, often used as proxies for the cost of capital, are obtained by inverting accounting-based valuation models. The author describes accounting-based valuation models and discusses how these models have been used, and how they may be used, to obtain estimates of the cost of capital. The practical appeal of accounting-based valuation models is that they focus on the two variables that are commonly at the heart of valuations carried out by equity analysts -- forecasts of earnings and forecasts of earnings growth. The question at the core of this monograph is -- How can these forecasts be used to obtain an estimate of the cost of capital? The author examines the empirical validity of the estimates based on these forecasts and explores ways to improve these estimates. In addition, this monograph details a method for isolating the effect of any factor of interest (such as cross-listing, fraud, disclosure quality, taxes, analyst following, accounting standards, etc.) on the cost of capital. If you are interested in understanding the academic literature on accounting-based estimates of expected rate of return this monograph is for you. Estimating the Cost of Capital Implied by Market Prices and Accounting Data provides a foundation for a deeper comprehension of this literature and will give a jump start to those who have an interest in these topics. The key ideas are introduced via examples based on actual forecasts, accounting information, and market prices for listed firms, and the numerical examples are based on sound algebraic relations.
Download or read book Accounting for Income Taxes written by John R. Graham and published by Now Pub. This book was released on 2012-11-09 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accounting for Income Taxes is the most comprehensive review of AFIT research. It is designed both to introduce new scholars to this field and to encourage active researchers to expand frontiers related to accounting for income taxes. Accounting for Income Taxes includes both a primer about the rules governing AFIT (Sections 3-4) and a review of the scholarly studies in the field (Sections 5-8). The primer uses accessible examples and clear language to express essential AFIT rules and institutional features. Section 3 reviews the basic rules and institutional details governing AFIT. Section 4 discusses ways that researchers, policymakers, and other interested parties can use the tax information in financial statements to better approximate information in the tax return. The second half of the monograph reviews the extant scholarly studies by splitting the research literature into four topics: earnings management, the association between book-tax differences and earnings characteristics, the equity market pricing of information in the tax accounts, and book-tax conformity. Section 5 focuses on the use of the tax accounts to manage earnings through the valuation allowance, the income tax contingency, and permanently reinvested foreign earnings. Section 6 discusses the association between book-tax differences and earnings characteristics, namely earnings growth and earnings persistence. Section 7 explores how tax information is reflected in share prices. Section 8 reviews the increased alignment of accounting for book purposes and tax purposes. The remainder of the paper focuses on topics of general interest in the economics and econometric literatures. Section 9 highlights some issues of general importance including a theoretical framework to interpret and guide empirical AFIT studies, the disaggregated components of book-tax differences and research opportunities as the U.S. moves toward International Financial Reporting Standards (IFRS). Section 10 discusses econometric weaknesses that are common in AFIT research and proposes ways to mitigate their deleterious effects.
Download or read book The Accuracy of Analyst Forecasts written by Patrick J. Butler and published by diplom.de. This book was released on 2002-12-04 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inhaltsangabe:Abstract: This paper investigates the quality of financial analysts' earnings forecasts for companies which conducted initial public offerings (IPOs) during the years 1997 to 1999. The Neue Markt in Frankfurt offers a good setting to also study the development of a young market from the beginning of its operation onwards. I find support for the notion that initial returns and analysts' forecast accuracy are negatively related. I find that analysts' forecasts were by no means accurate. Mean forecast deviation, measured as percent deviation from actual earnings per share for the fiscal year, is 186.61 percent for the average broker. The sample is inhibited by serious availability problems, but all the same allows significant findings. Inhaltsverzeichnis:Table of Contents: 1.Introduction5 2.Literature10 2.1Banking systems the German framework10 2.2Conflict of interest as regulated in the German legal system12 2.3The quality of analysts' forecasts and conflicts of interest16 2.4The long-run underperformance phenomenon23 2.5Predicting the aftermarket performance of IPOs27 2.6Summary39 3.Data41 4.Method49 5.Empirical Results53 5.1IPOs differentiated by year of issue53 5.2Disparities of actual values58 5.3Earning per share found in annual reports as basis62 5.4IPOs differentiated by industry classification67 5.5Percentage deviations differentiated by Brokers73 6.Additional Results80 6.1Large German banks seasoned vs. IPO companies80 6.2The time factor86 6.3The relevance of accounting policy88 7.Summary and Conclusion92 8.References95
Download or read book Business Forecasting written by Michael Gilliland and published by John Wiley & Sons. This book was released on 2021-05-11 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.
Download or read book Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and published by World Scientific. This book was released on 2020-07-30 with total page 5053 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
Download or read book Principles of Forecasting written by J.S. Armstrong and published by Springer Science & Business Media. This book was released on 2001 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook summarises knowledge from experts and empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. Includes a comprehensive forecasting dictionary.
Download or read book SAS for Forecasting Time Series Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.
Download or read book Wall Street Research written by Boris Groysberg and published by Stanford University Press. This book was released on 2013-08-07 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wall Street Research: Past, Present, and Future provides a timely account of the dramatic evolution of Wall Street research, examining its rise, fall, and reemergence. Despite regulatory, technological, and global forces that have transformed equity research in the last ten years, the industry has proven to be remarkably resilient and consistent. Boris Groysberg and Paul M. Healy get to the heart of Wall Street research—the analysts engaged in the process—and demonstrate how the analysts' roles have evolved, what drives their performance today, and how they stack up against their buy-side counterparts. The book unpacks key trends and describes how different firms have coped with shifting pressures. It concludes with an assessment of where equity research is headed in emerging markets, drawing conclusions about this often overlooked corner of Wall Street and the industry's future challenges.
Download or read book Understanding Economic Forecasts written by David F. Hendry and published by MIT Press. This book was released on 2003 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to interpret and evaluate economic forecasts and the uncertainties inherent in them.
Download or read book Superforecasting written by Philip E. Tetlock and published by Crown. This book was released on 2015-09-29 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: NEW YORK TIMES BESTSELLER • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY THE ECONOMIST “The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow.”—Jason Zweig, The Wall Street Journal Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week’s meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught? In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters." In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.
Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Download or read book Corruption and Reform written by Edward L. Glaeser and published by University of Chicago Press. This book was released on 2007-11-01 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite recent corporate scandals, the United States is among the world’s least corrupt nations. But in the nineteenth century, the degree of fraud and corruption in America approached that of today’s most corrupt developing nations, as municipal governments and robber barons alike found new ways to steal from taxpayers and swindle investors. In Corruption and Reform, contributors explore this shadowy period of United States history in search of better methods to fight corruption worldwide today. Contributors to this volume address the measurement and consequences of fraud and corruption and the forces that ultimately led to their decline within the United States. They show that various approaches to reducing corruption have met with success, such as deregulation, particularly “free banking,” in the 1830s. In the 1930s, corruption was kept in check when new federal bureaucracies replaced local administrations in doling out relief. Another deterrent to corruption was the independent press, which kept a watchful eye over government and business. These and other facets of American history analyzed in this volume make it indispensable as background for anyone interested in corruption today.
