It reflects the latest information (in 2001), including the impact of global competition and rapid technological advances, that have accelerated trends such as shared service centres, outsourcing and just-in-time training. A number of actual company examples demonstrates how concepts are being used in several leading-edge organizations.

    

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    The realistic content of its examples and exercises, the clarity and brevity of its presentation, and the soundness of its pedagogical approach have received the highest remarks from both students and instructors. Now this bestseller is available in a new 6th edition.

    The book studies the development of familiar cultural practices from India and around the world and links the regular to the esoteric and explains everything from Game Theory to the Cobra Effect without depending on graphs or equations-a modern-day miracle!Through disarmingly simple prose, the book demystifies economic theories, offers delightful insights, and provides nuance without jargon. Each chapter of this book will give you the tools to meaningfully engage with a subject that has long been considered alienating but is unavoidable in its relevance.

    This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.-- "Journal of Economics"

    It is also updated to reflect the latest in theory, research, real-world examples, and use of technology. The seamless, integrated ancillary package - done by the authors - is a hallmark of this package that makes the subject more accessible for learners.

    It stresses the economic intuition behind the subject matter while presenting advanced concepts of investment analysis and portfolio management. Readers will also discover the strengths and weaknesses of modern portfolio theory as well as the latest breakthroughs.

    Provides a review of introductory noncalculus-based physics for those who do not have a strong background in mathematics.

    Financial Modeling bridgesthis gap between theory and practice by providing a nuts-and-bolts guide to solvingcommon financial models with spreadsheets. Simon Benninga takes the reader step bystep through each model, showing how it can be solved using Microsoft Excel. Thelong-awaited third edition of this standard text maintains the "cookbook"features and Excel dependence that have made the first and second editions sopopular. It also offers significant new material, with new chapters covering suchtopics as bank valuation, the Black-Litterman approach to portfolio optimization, Monte Carlo methods and their applications to option pricing, and using arrayfunctions and formulas. Other chapters, including those on basic financialcalculations, portfolio models, calculating the variance-covariance matrix, andgenerating random numbers, have been revised, with many offering substantially newand improved material. Other areas covered include financial statement modeling, leasing, standard portfolio problems, value at risk (VaR), real options, durationand immunization, and term structure modeling. Technical chapters treat such topicsas data tables, matrices, the Gauss-Sidel method, and tips for using Excel. The lastsection of the text covers the Visual Basic for Applications (VBA) techniques neededfor the book. The accompanying CD contains Excel worksheets and solutions toend-of-chapter exercises.Simon Benninga is Dean of the Facultyand Professor of Finance at Tel Aviv University and Visiting Professor of Finance atthe Wharton School at the University of Pennsylvania.

    The author successfully introduces Maxwell's equations, wave propagation, network analysis, and design principles as applied to modern microwave engineering. A considerable amount of material in this book is related to the design of specific microwave circuits and components, for both practical and motivational value. It also presents the analysis and logic behind these designs so that the reader can see and understand the process of applying the fundamental concepts to arrive at useful results. The derivations are well laid out and the majority of each chapter's formulas are displayed in a nice tabular format every few pages. This Third Edition offers greatly expanded coverage with new material on: Noise; Nonlinear effects; RF MEMs; transistor power amplifiers; FET mixers; oscillator phase noise; transistor oscillators and frequency multiplier.

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    It can also serve as a one-semester introductory course at the beginning graduate level, as a useful precursor to a more serious study of CFD in advanced books. It is presented in a very readable, informal, enjoyable style.

    This is no ordinary "how-to" manual for CFA candidates. Written by an internationally published author who passed all three CFA exams on the first try, this book is packed with real strategies that get real results. What tactics make the difference? How do passing candidates set themselves apart? Direct Path to the CFA Charter enables you to adopt the right methods and strategies to pass the exams the first time around. With actionable takeaways, sample study schedules, and unique tips for every CFA Level, this book is for the serious candidate who not only wants to understand the CFA Program, but succeed in it.

    Adapted from the comprehensive, even epic, works Derivatives and Paul Wilmott on Quantitative Finance, Second Edition, it includes carefully selected chapters to give the student a thorough understanding of futures, options and numerical methods. Software is included to help visualize the most important ideas and to show how techniques are implemented in practice. There are comprehensive end-of-chapter exercises to test students on their understanding.