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This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds. Now in its third edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory...
The practical aspects of optimization rarely receive global, balanced examinations. Stephen Satchell's nuanced assembly of technical presentations about optimization packages (by their developers) and about current optimization practice and theory (by academic researchers) makes available highly practical solutions to our post-liquidity bubble environment. The commercial chapters emphasize algorithmic elements without becoming sales pitches, and the academic chapters create context and explore development opportunities. Together they offer an incisive perspective that stretches toward new products, new techniques, and new answers in quantitative finance. - Presents a unique "confrontation" between software engineers and academics - Highlights a global view of common optimization issues - Emphasizes the research and market challenges of optimization software while avoiding sales pitches - Accentuates real applications, not laboratory results
Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.
Competition Science Vision (monthly magazine) is published by Pratiyogita Darpan Group in India and is one of the best Science monthly magazines available for medical entrance examination students in India. Well-qualified professionals of Physics, Chemistry, Zoology and Botany make contributions to this magazine and craft it with focus on providing complete and to-the-point study material for aspiring candidates. The magazine covers General Knowledge, Science and Technology news, Interviews of toppers of examinations, study material of Physics, Chemistry, Zoology and Botany with model papers, reasoning test questions, facts, quiz contest, general awareness and mental ability test in every monthly issue.
This book constitutes the refereed proceedings of the 13th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2008, held in Bertinoro, Italy, in May 2008. The 32 revised full papers presented were carefully reviewed and selected from 95 submissions. The papers cover various aspects of integer programming and combinatorial optimization and present recent developments in theory, computation, and applications in that area. Topics included are such as approximation algorithms, branch and bound algorithms, branch and cut algorithms, computational biology, computational complexity, computational geometry, cutting plane algorithms, diophantine equations, geometry of numbers, graph and network algorithms, integer programming, matroids and submodular functions, on-line algorithms and competitive analysis, polyhedral combinatorics, randomized algorithms, random graphs, scheduling theory and scheduling algorithms, and semidefinite programs.
This volume, inspired by and dedicated to the work of pioneering investment analyst, Jack Treynor, addresses the issues of portfolio risk and return and how investment portfolios are measured. In a career spanning over fifty years, the primary questions addressed by Jack Treynor were: Is there an observable risk-return trade-off? How can stock selection models be integrated with risk models to enhance client returns? Do managed portfolios earn positive, and statistically significant, excess returns and can mutual fund managers time the market? Since the publication of a pair of seminal Harvard Business Review articles in the mid-1960’s, Jack Treynor has developed thinking that has greatly ...
Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general...
This book explores the current state of the art in quantitative investment management across seven key areas. Chapters by academics and practitioners working in leading investment management organizations bring together major theoretical and practical aspects of the field.
This book introduces the readers to the rapidly growing literature and latest results on financial, fundamental and seasonal anomalies, stock selection modeling and portfolio management. Fifty years ago, finance professors taught the Efficient Markets Hypothesis which states that the average investor could not outperform the stock market based on technical, seasonal and fundamental data. Many, if not most faculty and investors, no longer share that opinion. In this book, the authors report original empirical evidence that applied investment research can produce statistically significant stock selection and excess portfolio returns in the US, and larger excess returns in international and emerging markets.