​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?

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.

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.

This Handbook presents original research and theory on executives, top management teams, and boards of directors and illustrates the vital importance of this field of study. Top management teams are responsible for the strategic choices and major decisions in organizations. These organizations are a reflection of the members that make up their strategic management. The roles top management play and the impact they have are clearly visible in firms around the world, both large and small. The international group of authors that comprise this volume address questions central to the field of strategy and strategic leadership. They review the determinants of top management team composition, their social networks, and executive dismissal; the psychological and personality profiles of top executives; the methodologies relevant to the study of top teams; and the roles of top executives in cross business unit collaboration, competitive behavior, and strategic entrepreneurship. Each chapter presents path-breaking research and provides a roadmap for new research avenues and agendas. Professors, students and researchers in the area of strategy, management and strategic leadership will find this book an invaluable resource.

Proceedings of the 9th- Annual conference on research in accounting, held at the University of Chicago.

Over the last 50 years, neoclassical financial theory has been dominating our perception of what is happening in financial markets. It has spurred numerous valuable theories and concepts all based on the concept of Homo Economicus, the strictly rational economic man. However, humans do not always act in a strictly rational manner. For students and practitioners alike, our book aims at opening the door to another perspective on financial markets: a behavioral perspective based on a Homo Oeconomicus Humanus. This agent acts with limited rationality when making decisions. He/she uses heuristics and shortcuts and is prone to the influence of emotions. This sounds familiar in real life and can be transferred to what happens in financial markets, too.