EVA ("economic value added" - wirtschaftliche Wertschöpfung) ist eine Maßeinheit zur Ermittlung des echten Finanzergebnisses eines Unternehmens und eine Strategie zur Schaffung von Unternehmens- und Aktionärsvermögen. Das EVA-Prinzip besagt, daß ein Unternehmen kein Vermögen schafft, solange es nicht in der Lage ist, Gewinne einzufahren, die höher sind als die Kapitalkosten. EVA ist auch eine Methode, die Prioritäten innerhalb eines Unternehmens so zu gewichten, daß das Hauptaugenmerk auf der Schaffung von Vermögen liegt, und zwar zum Nutzen aller. Leicht verständlich geschrieben, mit zahlreichen Fallbeispielen bekannter Firmen und einem Minimum an Gleichungen und Finanzjargon. (11/98)

This book, first published in 2002, compiles psychologists' best attempts to answer important questions about intuitive judgment.

Financial Statement Analysis and Earnings Forecasting is the process of analyzing historical financial statement data for the purpose of developing forecasts of future earnings. This process is important because it is central to the valuation of companies and the securities they issue. After a short introduction, Section 2 delves into the question "Why earnings"? Focusing on dividend policy irrelevance, the author describes key analytical results that imply that expected earnings are the fundamental determinant of both equity and enterprise value. Section 3 examines the issues involved in selecting the earnings metric to forecast. Once an earnings metric has been chosen, the next question to ask is "How useful are historical accounting numbers for developing forecasts of that metric?" Sections 4 through 8 focus on this question. Section 4 discusses the general role of econometric modeling. Section 5 reviews time-series models. Section 6 examines the choices a researcher makes when using panel-data approaches and the author describes the advantages of these approaches. Section 7 reviews the role of accounting measurement in determining the usefulness of historical accounting numbers for developing forecasts of future earnings. Section 8 examines approaches for forecasting the higher moments of future earnings and section 9 provides a summary.

Tech Stock Valuation extends the R&D literature by providing detailed direct evidence on the market value implications of inventive and innovative output. Specifically, the text demonstrates that stock-price effects of patent output are most pronounced in the case of high-quality patents, where patent quality is measured by scientific merit. Scientific measures of patent quality give students a valuable new tool that can be used to measure R&D program effectiveness. At the same time, it gives investors a new tool to help them assess the value of hard-to-measure intangible assets. The book is an ideal resource for professionals working in finance and accounting; investment professionals and industry analysts who work for companies that engage in research and development; MBA students; economists working in industrial organizations, microeconomics, and contract theory. - Provides detailed direct evidence on the market value implications of inventive and innovative output - Based on recent research, much of which Dr. Hirschey has pioneered - Gives financial professionals a new tool for assessing R&D quality and its relation to market valuation

Spending on M&A has, in aggregate, grown so fast that it has even overtaken capital expenditure on increasing and maintaining physical assets. Yet McKinsey, the leading management consultancy, reports that "Anyone who has researched merger success rates knows that roughly 70% fail". The idea that businesses might be using huge and increasing sums of shareholders’ money for an activity that more often than not leads to failure calls into question the information on which M&A decisions are based. This book presents statistical studies, case material, and standard-setters’ opinions on company accounting before, during, and after M&A. It documents the manipulation of annual accounts by acquirers ahead of share for share bids, biased forecasts of post-merger earnings by bidders, and devices to flatter earnings when recording the deal. It explores the challenges for standard-setters in regulating information flows during and after M&A, and for account-users wishing to learn from financial statements how a deal has affected performance. Drawing on a wide range of international examples, this readable book is targeted not just at accounting specialists but at anyone who is comfortable reading the serious financial press, is intrigued by what is going on in the massive M&A market, and is concerned with achieving better-informed M&A. As such it might be of particular interest to business executives, lawyers, bankers, and investors involved in M&A as well as graduate students interested in researching or learning about the role of accounting in M&A.