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.

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.

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.

​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?

John G. Cragg and Burton G. Malkiel collected detailed forecasts of professional investors concerning the growth of 175 companies and use this information to examine the impact of such forecasts on the market evaluations of the companies and to test and extend traditional models of how stock market values are determined.

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.

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).