Financialization over the past three decades has created a structure that lacks resilience and supports absurd volumes of trading. The finance sector devotes too little attention to the search for new investment opportunities and the stewardship of existing ones, and far too much to secondary-market dealing in existing assets. Regulation has contributed more to the problems than the solutions.Why? What is finance for? John Kay, with wide practical and academic experience in the world of finance, understands the operation of the financial sector better than most. He believes in good banks and effective asset managers, but good banks and effective asset managers are not what he sees.In a dazzling and revelatory tour of the financial world as it has emerged from the wreckage of the 2008 crisis, Kay does not flinch in his criticism: we do need some of the things that Citigroup and Goldman Sachs do, but we do not need Citigroup and Goldman to do them. And many of the things done by Citigroup and Goldman do not need to be done at all. The finance sector needs to be reminded of its primary purpose: to manage other people's money for the benefit of businesses and households. It is an aberration when the some of the finest mathematical and scientific minds are tasked with devising algorithms for the sole purpose of exploiting the weakness of other algorithms for computerized trading in securities. To travel further down that road leads to ruin.

    Pettis combines the insights of economic history, economic theory, and finance theory into a comprehensive model for understanding sovereign liability management and the causes of financial crises. He examines recent financial crises in emerging market countries along with the history of international lending since the 1820s to argue that the process of international lending is driven primarily by external events and not by local politics and/or economic policies. He draws out the corporate finance implications of this approach to argue that most of the current analyses of the recent financial crises suffered by Latin America, Asia, and Russia have largely missed the point. He then develops a sovereign finance model, analogous to corporate finance, to understand the capital structure needs of emerging market countries. Using this model, he finally puts into perspective the recent crises, a new sovereign liability management theory, the implications of the model for sovereign debt restructurings, and the new financial architecture.Bridging the gap between finance specialists and traders, on the one hand, and economists and policy-makers on the other, The Volatility Machine is critical reading for anyone interested in where the international economy is going over the next several years.

    Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught?   In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters."   In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    The Fourth Edition builds on this strength with new examples, additional applications and increased cryptology coverage. Up-to-date information on the latest discoveries is included.Elementary Number Theory and Its Applications provides a diverse group of exercises, including basic exercises designed to help students develop skills, challenging exercises and computer projects. In addition to years of use and professor feedback, the fourth edition of this text has been thoroughly accuracy checked to ensure the quality of the mathematical content and the exercises.

    Get a new and powerful understanding of the world around you. Save yourself from the nonsense spouted by politicians, TV pundits, right-wingers, left-wingers, shamans, uncles, and best friends.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    The book also provides a balanced presentation of time-varying and static fields, preparingstudents for employment in today's industrial and manufacturing sectors. Streamlined to facilitate student understanding, this edition features worked examples in every chapter that explain how to use the theory presented in the text to solve different kinds of problems. Numerical methods, including MATLAB and vector analysis, are also included to help students analyzesituations that they are likely to encounter in industry practice. Elements of Electromagnetics, Fifth Edition, is designed for introductory undergraduate courses in electromagnetics.

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    The book offers sound, practical advice, no matter what your age or net worth. Bottomline, become a Boglehead and prosper! Originally just the chat-line ruminations of Boglehead founder Taylor Larimore, and Morningstar forum leading cohorts Mel Lindauer and Michael LeBoeuf, their trusted advice has been brewed and distilled into an easy-to-use, need-to-know, no frills guide to building up your own financial well-being - so you can worry less and profit more from the investments you make. Invest like a Boglehead, and let their grassroots investment wisdom guide you down the path of long-term wealth creation and happiness, without all the worries and fuss of stock pickers and day traders. If you face a financial crisis or problem, or simply want to know what is prudent to do with the money you save, the Bogleheads will have the answers you need to help you gain your financial footing and keep it.

    Drawing on his experience as a professional trader, author Sheldon Natenberg examines both the theory and reality of option trading. He presents the foundations of option theory explaining how this theory can be used to identify and exploit trading opportunities. "Option Volatility & Pricing" teaches you to use a wide variety of trading strategies and shows you how to select the strategy that best fits your view of market conditions and individual risk tolerance.New sections include: Expanded coverage of stock option Strategies for stock index futures and options A broader, more in-depth discussion volatility Analysis of volatility skews Intermarket spreading with options

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    Objects are introduced early, right after control structures and before arrays and pointers. The STL string class is used throughout. As with all Gaddis books, there is a strong emphasis on problem solving and program design, a careful step-by-step introduction of each new topic, clear and easy to read code listings, concise and practical real world examples, and an abundance of exercises in each chapter.

    From inside the corner office at Lehman Brothers to secret meetings in South Korea, and the corridors of Washington, Too Big to Fail is the definitive story of the most powerful men and women in finance and politics grappling with success and failure, ego and greed, and, ultimately, the fate of the world’s economy. “We’ve got to get some foam down on the runway!” a sleepless Timothy Geithner, the then-president of the Federal Reserve of New York, would tell Henry M. Paulson, the Treasury secretary, about the catastrophic crash the world’s financial system would experience. Through unprecedented access to the players involved, Too Big to Fail re-creates all the drama and turmoil, revealing neverdisclosed details and elucidating how decisions made on Wall Street over the past decade sowed the seeds of the debacle. This true story is not just a look at banks that were “too big to fail,” it is a real-life thriller with a cast of bold-faced names who themselves thought they were too big to fail.

    The exposition is simple and leads to the most complete direct means of solving problems in mechanics. The final sections on adiabatic invariants have been revised and augmented. In addition a short biography of L D Landau has been inserted.