Throughout the book the authors show how managers use financial theory to solve practical problems and as a way of learning how to respond to change by showing not just how but why companies and management act as they do. The text is comprehensive, authoritative, and modern and yet the material is presented at a common sense level. The discussions and illustrations are unique due to the depth of detail blended with a distinct sense of humor for which the book is well known and highly regarded. This text is a valued reference for thousands of practicing financial managers.

    In fact it was a dramatic caesura of global significance that spiraled around the world, from the financial markets of the UK and Europe to the factories and dockyards of Asia, the Middle East, and Latin America, forcing a rearrangement of global governance. In the United States and Europe, it caused a fundamental reconsideration of capitalist democracy, eventually leading to the war in the Ukraine, the chaos of Greece, Brexit, and Trump.It was the greatest crisis to have struck Western societies since the end of the Cold War, but was it inevitable? And is it over? Crashed is a dramatic new narrative resting on original themes: the haphazard nature of economic development and the erratic path of debt around the world; the unseen way individual countries and regions are linked together in deeply unequal relationships through financial interdependence, investment, politics, and force; the ways the financial crisis interacted with the spectacular rise of social media, the crisis of middle-class America, the rise of China, and global struggles over fossil fuels.Finally, Tooze asks, given this history, what now are the prospects for a liberal, stable, and coherent world order?

    We need to remember that sustained economic success is a rare phenomenon.As an era of easy money and easy growth comes to a close, China in particular will cool down. Other major players including Brazil, Russia, and India face their own daunting challenges and inflated expectations. The new "breakout nations" will probably spring from the margins, even from the shadows. Ruchir Sharma, one of the world’s largest investors in emerging markets for Morgan Stanley, here identifies which are most likely to leap ahead and why.After two decades spent traveling the globe tracking the progress of developing countries, Sharma has produced a book full of surprises: why the overpriced cocktails in Rio are a sign of revival in Detroit; how the threat of the "population bomb" came to be seen as a competitive advantage; how an industrial revolution in Asia is redefining what manufacturing can do for a modern economy; and how the coming shakeout in the big emerging markets could shift the spotlight back to the West, especially American technology and German manufacturing.What emerges is a clear picture of the shifting balance of global economic power and how it plays out for emerging nations and for the West. In a captivating exploration studded with vignettes, Sharma reveals his rules on how to spot economic success stories. Breakout Nations is a rollicking education for anyone looking to understand where the future will happen.

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    With the stock market sinking and soaring from day to day, retirement plans becoming less certain, and a longer life expectancy in retirement, more people are looking for some control over their investments. If you're one of them, Investing Online For Dummies, 6th Edition might be just what you're looking for. The Internet brings a world of investment resources to your desktop, but how do you find your way through the dizzying array of investment possibilities? The Dummies Way, of course! This book helps you set reasonable expectations, assess your risk tolerance, choose an asset allocation, analyze and select investments, and maximize your financial success. You'll discover how toDetermine how much you can afford to invest Choose an online broker Research, trade, and track investments online Measure the potential return of a stock Maximize your investment knowledge and build a profitable portfolio Buy bonds online Understand options, commodities, and IPOs If you've decided to take control of your investments but don't want to make it your full-time job, Investing Online For Dummies, 6th Edition gives you the important information that will also give you confidence. Completely updated to cover all the new online tools and resources, it even provides some bonus assistance on the companion Web site.

     They were preparing to compete in a poker tournament with million-dollar stakes, but those numbers meant nothing to them.  They were accustomed to risking billions.     At the card table that night was Peter Muller, an eccentric, whip-smart whiz kid who’d studied theoretical mathematics at Princeton and now managed a fabulously successful hedge fund called PDT…when he wasn’t playing his keyboard for morning commuters on the New York subway.  With him was Ken Griffin, who as an undergraduate trading convertible bonds out of his Harvard dorm room had outsmarted the Wall Street pros and made money in one of the worst bear markets of all time.  Now he was the tough-as-nails head of Citadel Investment Group, one of the most powerful money machines on earth. There too were Cliff Asness, the sharp-tongued, mercurial founder of the hedge fund AQR, a man as famous for his computer-smashing rages as for his brilliance, and Boaz Weinstein, chess life-master and king of the credit default swap, who while juggling $30 billion worth of positions for Deutsche Bank found time for frequent visits to Las Vegas with the famed MIT card-counting team.     On that night in 2006, these four men and their cohorts were the new kings of Wall Street.  Muller, Griffin, Asness, and Weinstein were among the best and brightest of a  new breed, the quants.  Over the prior twenty years, this species of math whiz --technocrats who make billions not with gut calls or fundamental analysis but with formulas and high-speed computers-- had usurped the testosterone-fueled, kill-or-be-killed risk-takers who’d long been the alpha males the world’s largest casino.  The quants believed that a dizzying, indecipherable-to-mere-mortals cocktail of differential calculus, quantum physics, and advanced geometry held the key to reaping riches from the financial markets.  And they helped create a digitized money-trading machine that could shift billions around the globe with the click of a mouse.     Few realized that night, though, that in creating this unprecedented machine, men like Muller, Griffin, Asness and Weinstein had sowed the seeds for history’s greatest financial disaster.     Drawing on unprecedented access to these four number-crunching titans, The Quants tells the inside story of what they thought and felt in the days and weeks when they helplessly watched much of their net worth vaporize – and wondered just how their mind-bending formulas and genius-level IQ’s had led them so wrong, so fast.  Had their years of success been dumb luck, fool’s gold, a good run that could come to an end on any given day?  What if The Truth they sought -- the secret of the markets -- wasn’t knowable? Worse, what if there wasn’t any Truth?   In The Quants, Scott Patterson tells the story not just of these men, but of Jim Simons, the reclusive founder of the most successful hedge fund in history; Aaron Brown, the quant who used his math skills to humiliate Wall Street’s old guard at their trademark game of Liar’s Poker, and years later found himself with a front-row seat to the rapid emergence of mortgage-backed securities; and gadflies and dissenters such as Paul Wilmott, Nassim Taleb, and Benoit Mandelbrot.     With the immediacy of today’s NASDAQ close and the timeless power of a Greek tragedy, The Quants is at once a masterpiece of explanatory journalism, a gripping tale of ambition and hubris…and an ominous warning about Wall Street’s future.

    The economic narratives that underpinned these eras—the gold standard, the Bretton Woods regime, the "Washington Consensus"—brought great success and great failure. In this eloquent challenge to the reigning wisdom on globalization, Dani Rodrik offers a new narrative, one that embraces an ineluctable tension: we cannot simultaneously pursue democracy, national self-determination, and economic globalization. When the social arrangements of democracies inevitably clash with the international demands of globalization, national priorities should take precedence. Combining history with insight, humor with good-natured critique, Rodrik's case for a customizable globalization supported by a light frame of international rules shows the way to a balanced prosperity as we confront today's global challenges in trade, finance, and labor markets.

    This connectedness is found in many incarnations: in the rapid growth of the Internet, in the ease with which global communication takes place, and in the ability of news and information as well as epidemics and financial crises to spread with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which our decisions can have subtle consequences for others. This introductory undergraduate textbook takes an interdisciplinary look at economics, sociology, computing and information science, and applied mathematics to understand networks and behavior. It describes the emerging field of study that is growing at the interface of these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

    In this unconventional introduction, physicist Leonard Susskind and hacker-scientist George Hrabovsky offer a first course in physics and associated math for the ardent amateur. Unlike most popular physics books—which give readers a taste of what physicists know but shy away from equations or math—Susskind and Hrabovsky actually teach the skills you need to do physics, beginning with classical mechanics, yourself. Based on Susskind's enormously popular Stanford University-based (and YouTube-featured) continuing-education course, the authors cover the minimum—the theoretical minimum of the title—that readers need to master to study more advanced topics.An alternative to the conventional go-to-college method, The Theoretical Minimum provides a tool kit for amateur scientists to learn physics at their own pace.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    For the first time, the major developed economies began to invest more in intangible assets, like design, branding, R&D, and software, than in tangible assets, like machinery, buildings, and computers. For all sorts of businesses, from tech firms and pharma companies to coffee shops and gyms, the ability to deploy assets that one can neither see nor touch is increasingly the main source of long-term success.But this is not just a familiar story of the so-called new economy. Capitalism without Capital shows that the growing importance of intangible assets has also played a role in some of the big economic changes of the last decade. The rise of intangible investment is, Jonathan Haskel and Stian Westlake argue, an underappreciated cause of phenomena from economic inequality to stagnating productivity.Haskel and Westlake bring together a decade of research on how to measure intangible investment and its impact on national accounts, showing the amount different countries invest in intangibles, how this has changed over time, and the latest thinking on how to assess this. They explore the unusual economic characteristics of intangible investment, and discuss how these features make an intangible-rich economy fundamentally different from one based on tangibles.Capitalism without Capital concludes by presenting three possible scenarios for what the future of an intangible world might be like, and by outlining how managers, investors, and policymakers can exploit the characteristics of an intangible age to grow their businesses, portfolios, and economies.

    This overview has enabled students to make sense more easily of what instructors are doing when they produce proofs, theorems and formulas.

    Peter Bernstein has written a comprehensive history of man's efforts to understand risk and probability, beginning with early gamblers in ancient Greece, continuing through the 17th-century French mathematicians Pascal and Fermat and up to modern chaos theory. Along the way he demonstrates that understanding risk underlies everything from game theory to bridge-building to winemaking.

    When it comes to markets, the first deadly sin is greed. In this New York Times bestseller, Michael Lewis is our jungle guide through five of the most violent and costly upheavals in recent financial history. With his trademark humor and brilliant anecdotes, Lewis paints the mood and market factors leading up to each event, weaves contemporary accounts to show what people thought was happening at the time, and, with the luxury of hindsight, analyzes what actually happened and what we should have learned from experience. .