In this, he succeeds magnificently. Globalizing Capital will become a classic."--Douglas Irwin, University of ChicagoThe importance of the international monetary system is clearly evident in daily news stories about fluctuating currencies and in dramatic events such as the recent reversals in the Mexican economy. It has become increasingly apparent that one cannot understand the international economy without knowing how its monetary system operates. Now Barry Eichengreen presents a brief, lucid book that tells the story of the international financial system over the past 150 years. Globalizing Capital is intended not only for economists but also for a general audience of historians, political scientists, professionals in government and business, and anyone with a broad interest in international economic and political relations. Eichengreen's work demonstrates that insights into the international monetary system and effective principles for governing it can result only if it is seen a historical phenomenon extending from the gold standard period to interwar instability, then to Bretton Woods, and finally to the post-1973 period of fluctuating currencies.Eichengreen analyzes the shift from pegged to floating exchange rates in the 1970s and ascribes that change to the growing capital mobility that has made pegged rates difficult to maintain. However, he shows that capital mobility was also high prior to World War I, yet this did not prevent the maintenance of fixed exchange rates. What was critical for the successful maintenance of fixed exchange rates during that period was the fact that governmentswere relatively insulated from democratic politics and thus from pressure to trade off exchange rate stability for other goals, such as the reduction of unemployment. Today pegging exchange rates would require very radical reforms of a sort that governments are understandably reluctant to embrace. The implication seems undeniable: floating rates are here to stay.

    But the left and right can usually agree on one thing: that the Nordic system is impossible to replicate here at home. The US is too big, or too individualistic, or too puritan, or too . . . something. Whatever the reason, it's impossible, and we shouldn't bother to try.Enter George Lakey. A longtime activist and academic, Lakey has spent decades studying the economies of Denmark, Sweden, Norway, Finland, and Iceland, and in Viking Economics, he reveals that Scandinavia's deep commitment to the welfare state is much more recent than we think. Not long ago, Scandinavia was a far more unequal place, with a much weaker commitment to the social welfare of its citizens. There's nothing inherently Scandinavian about greater equality . . . so why not try it here?Viking Economics is more fun and entertaining than any economics book you've ever read. And, very possibly, more convincing! As he ranges from twentieth-century Norwegian history to the details of Swedish childcare policies, Lakey never loses his sense of humor or his expansive, generous vision of a better, more equal future. By explaining that even Scandinavia's grandest experiments in social equality are rooted in recent political struggles, Lakey explains shows how we can do it, too—conventional wisdom be damned.From the Hardcover edition.

    Porter's Competitive Advantage explores the underpinnings of competitive advantage in the individual firm.Competitive Advantage introduces a whole new way of understanding what a firm does. Porter's groundbreaking concept of the value chain disaggregates a company into "activities," or the discrete functions or processes that represent the elemental building blocks of competitive advantage. Now an essential part of international business thinking, Competitive Advantage takes strategy from broad vision to an internally consistent configuration of activities. Its powerful framework provides the tools to understand the drivers of cost and a company's relative cost position. Porter's value chain enables managers to isolate the underlying sources of buyer value that will command a premium price, and the reasons why one product or service substitutes for another. He shows how competitive advantage lies not only in activities themselves but in the way activities relate to each other, to supplier activities, and to customer activities. Competitive Advantage also provides for the first time the tools to strategically segment an industry and rigorously assess the competitive logic of diversification. That the phrases "competitive advantage" and "sustainable competitive advantage" have become commonplace is testimony to the power of Porter's ideas. Competitive Advantage has guided countless companies, business school students, and scholars in understanding the roots of competition. Porter's work captures the extraordinary complexity of competition in a way that makes strategy both concrete and actionable.

    Offering time-tested problems, conceptual and visual pedagogy, and a state-of-the-art media package, this 11th edition looks to the future of university physics, in terms of both content and approach.

    The new edition, fully updated with the most recent data and research possible, includes new coverage of the Medicare drug benefit, changes in the tax code, Hurricane Katrina, and the ongoing debate over privatization.

    Detailing the technical indicators and money management strategies that have worked best for him, T. Livingston breaks down what every savvy trader needs to profit in today’s stock market. Topics discussed include how to analyze the general market, which stocks to trade, when to buy, position sizing, profit targets, and selling rules. Swing Into It provides a variety of different examples so that the reader will be prepared for various market scenarios. Detailed sample trades are included so that the reader can see how Livingston thinks throughout each phase of his trades. If you’re looking to get started in swing trading or seeking to refine your trading system, Swing Into It belongs in your library.

    The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation.

    More than four million homes were lost to foreclosures. Is it a coincidence that the United States witnessed a dramatic rise in household debt in the years before the recession—that the total amount of debt for American households doubled between 2000 and 2007 to $14 trillion? Definitely not. Armed with clear and powerful evidence, Atif Mian and Amir Sufi reveal in House of Debt how the Great Recession and Great Depression, as well as the current economic malaise in Europe, were caused by a large run-up in household debt followed by a significantly large drop in household spending. Though the banking crisis captured the public’s attention, Mian and Sufi argue strongly with actual data that current policy is too heavily biased toward protecting banks and creditors. Increasing the flow of credit, they show, is disastrously counterproductive when the fundamental problem is too much debt. As their research shows, excessive household debt leads to foreclosures, causing individuals to spend less and save more. Less spending means less demand for goods, followed by declines in production and huge job losses. How do we end such a cycle? With a direct attack on debt, say Mian and Sufi.  More aggressive debt forgiveness after the crash helps, but as they illustrate, we can be rid of painful bubble-and-bust episodes only if the financial system moves away from its reliance on inflexible debt contracts. As an example, they propose new mortgage contracts that are built on the principle of risk-sharing, a concept that would have prevented the housing bubble from emerging in the first place. Thoroughly grounded in compelling economic evidence, House of Debt offers convincing answers to some of the most important questions facing the modern economy today: Why do severe recessions happen? Could we have prevented the Great Recession and its consequences? And what actions are needed to prevent such crises going forward?

    Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.

    With an accessible, straightforward approach. He guides traders through the basics of option pricing, volatility measurement, hedging, money management, and trade evaluation. In addition, Sinclair explains the often-overlooked psychological aspects of trading, revealing both how behavioral psychology can create market conditions traders can take advantage of-and how it can lead them astray. Psychological biases, he asserts, are probably the drivers behind most sources of edge available to a volatility trader. Your goal, Sinclair explains, must be clearly defined and easily expressed-if you cannot explain it in one sentence, you probably aren't completely clear about what it is. The same applies to your statistical edge. If you do not know exactly what your edge is, you shouldn't trade. He shows how, in addition to the numerical evaluation of a potential trade, you should be able to identify and evaluate the reason why implied volatility is priced where it is, that is, why an edge exists. This means it is also necessary to be on top of recent news stories, sector trends, and behavioral psychology. Finally, Sinclair underscores why trades need to be sized correctly, which means that each trade is evaluated according to its projected return and risk in the overall context of your goals. As the author concludes, while we also need to pay attention to seemingly mundane things like having good execution software, a comfortable office, and getting enough sleep, it is knowledge that is the ultimate source of edge. So, all else being equal, the trader with the greater knowledge will be the more successful. This book, and its companion CD-ROM, will provide that knowledge. The CD-ROM includes spreadsheets designed to help you forecast volatility and evaluate trades together with simulation engines.

    'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

    Updates to this edition include a more user-friendly approach, new or updated cases that illustrate top companies addressing real world situations, topical articles written by scholars and practitioners, and more.

    Edited by the Sustainability Institute’s Diana Wright, this essential primer brings systems thinking out of the realm of computers and equations and into the tangible world, showing readers how to develop the systems-thinking skills that thought leaders across the globe consider critical for 21st-century life.Some of the biggest problems facing the world—war, hunger, poverty, and environmental degradation—are essentially system failures. They cannot be solved by fixing one piece in isolation from the others, because even seemingly minor details have enormous power to undermine the best efforts of too-narrow thinking.While readers will learn the conceptual tools and methods of systems thinking, the heart of the book is grander than methodology. Donella Meadows was known as much for nurturing positive outcomes as she was for delving into the science behind global dilemmas. She reminds readers to pay attention to what is important, not just what is quantifiable, to stay humble, and to stay a learner.In a world growing ever more complicated, crowded, and interdependent, Thinking in Systems helps readers avoid confusion and helplessness, the first step toward finding proactive and effective solutions.

    Non- mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms. Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance-all of which are problems that occur frequently in practice. The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code f

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.