Edited by Rajnish Mehra, this volume focuses on the equity risk premium puzzle, a term coined by Mehra and Prescott in 1985 which encompasses a number of empirical regularities in the prices of capital assets that are at odds with the predictions of standard economic theory.

A radical, definitive explanation of the link between loss aversion theory, the equity risk premium and stock price, and how to profit from it The Risk Premium Factor presents and proves a radical new theory that explains the stock market, offering a quantitative explanation for all the booms, busts, bubbles, and multiple expansions and contractions of the market we have experienced over the past half-century. Written by Stephen D. Hassett, a corporate development executive, author and specialist in value management, mergers and acquisitions, new venture strategy, development, and execution for high technology, SaaS, web, and mobile businesses, the book convincingly demonstrates that the equity risk premium is proportional to long-term Treasury yields, establishing a connection to loss aversion theory. Explains stock prices from 1960 through the present including the 2008/09 "market meltdown" Shows how the S&P 500 has consistently reverted to values predicted by the model Solves the equity premium puzzle by showing that it is consistent with findings on loss aversion Demonstrates that three factors drive valuation and stock price: earnings, long term growth, and interest rates Understanding the stock market is simple. By grasping the simplicity, business leaders, corporate decision makers, private equity, venture capital, professional, and individual investors will fully understand the system under which they operate, and find themselves empowered to make better decisions managing their businesses and investment portfolios.

Risk is the deviation from the consensus rather than an exposure to a covariance, and this implies there is no risk premium in general. It also implies that when there are a large number of people buying highly volatile assets, such assets will have negative returns in equilibrium. As there are several independent motivations for people to buy highly volatile assets, intuitively risky assets generally have lower-than-average returns. This novel conception of risk implies many things more consistent with the data than the current theory. Risk taking is an important life skill, so understanding its nature is important, and unfortunately academics who study it full-time are like so many other experts: when not irrelevant, 180 degrees wrong. This book explains the current asset pricing theory, and proposes an alternative, using theory and a unique survey of the data across many asset classes. Familiarity with some MBA level finance is helpful but not necessary to appreciate this book.

The second edition of this authoritative textbook continues the tradition of providing clear and concise descriptions of the new and classic concepts in financial theory. The authors keep the theory accessible by requiring very little mathematical background. First edition published by Prentice-Hall in 2001- ISBN 0130174467. The second edition includes new structure emphasizing the distinction between the equilibrium and the arbitrage perspectives on valuation and pricing, as well as a new chapter on asset management for the long term investor. "This book does admirably what it sets out to do - provide a bridge between MBA-level finance texts and PhD-level texts.... many books claim to require little prior mathematical training, but this one actually does so. This book may be a good one for Ph.D students outside finance who need some basic training in financial theory or for those looking for a more user-friendly introduction to advanced theory. The exercises are very good." --Ian Gow, Student, Graduate School of Business, Stanford University Completely updated edition of classic textbook that fills a gap between MBA level texts and PHD level texts Focuses on clear explanations of key concepts and requires limited mathematical prerequisites Updates includes new structure emphasizing the distinction between the equilibrium and the arbitrage perspectives on valuation and pricing, as well as a new chapter on asset management for the long term investor

Risk and Return for Regulated Industries provides a much-needed, comprehensive review of how cost of capital risk arises and can be measured, how the special risks regulated industries face affect fair return, and the challenges that regulated industries are likely to face in the future. Rather than following the trend of broad industry introductions or textbook style reviews of utility finance, it covers the topics of most interest to regulators, regulated companies, regulatory lawyers, and rate-of-return analysts in all countries. Accordingly, the book also includes case studies about various countries and discussions of the lessons international regulatory procedures can offer. - Presents a unified treatment of the regulatory principles and practices used to assess the required return on capital - Addresses current practices before exploring the ways methods play out in practice, including irregularities, shortcomings, and concerns for the future - Focuses on developed economies instead of providing a comprehensive global reviews - Foreword by Stewart C. Myers

The prediction of the valuation of the “quality” of firm accounting disclosure is an emerging economic problem that has not been adequately analyzed in the relevant economic literature. While there are a plethora of machine learning methods and algorithms that have been implemented in recent years in the field of economics that aim at creating predictive models for detecting business failure, only a small amount of literature is provided towards the prediction of the “actual” financial performance of the business activity. Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify “quality” characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students.

Risk Adjustment, Risk Sharing and Premium Regulation in Health Insurance Markets: Theory and Practice describes the goals, design and evaluation of health plan payment systems. Part I contains 5 chapters discussing the role of health plan payment in regulated health insurance markets, key aspects of payment design (i.e. risk adjustment, risk sharing and premium regulation), and evaluation methods using administrative data on medical spending. Part II contains 14 chapters describing the health plan payment system in 14 countries and sectors around the world, including Australia, Belgium, Chile, China, Columbia, Germany, Ireland, Israel, the Netherlands, Russia, Switzerland and the United States. Authors discuss the evolution of these payment schemes, along with ongoing reforms and key lessons on the design of health plan payment.