This is one of the biggest debates in economics and the value or futility of investment management and financial regulation hang on the outcome. In this groundbreaking book, Andrew Lo cuts through this debate with a new framework, the Adaptive Markets Hypothesis, in which rationality and irrationality coexist.Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency isn't wrong but merely incomplete. When markets are unstable, investors react instinctively, creating inefficiencies for others to exploit. Lo's new paradigm explains how financial evolution shapes behavior and markets at the speed of thought--a fact revealed by swings between stability and crisis, profit and loss, and innovation and regulation.A fascinating intellectual journey filled with compelling stories, Adaptive Markets starts with the origins of market efficiency and its failures, turns to the foundations of investor behavior, and concludes with practical implications--including how hedge funds have become the Galapagos Islands of finance, what really happened in the 2008 meltdown, and how we might avoid future crises.An ambitious new answer to fundamental questions in economics, Adaptive Markets is essential reading for anyone who wants to know how markets really work.

    Is it possible for investors to identify emerging bubbles and then profit from their inflation? Likewise, can investors avoid the bursting of these bubbles, and the extreme volatility and losses found in their aftermath to survive to invest another day? Over 70 years ago, Benjamin Graham and David Dodd proposed valuing stocks with earnings smoothed across multiple years. Robert Shiller later popularized this method with his version of the cyclically adjusted price-to-earnings (CAPE) ratio in the late 1990s and correctly issued a timely warning of poor stock returns to follow in the coming years. We apply this valuation metric across more than 40 foreign markets and find it both practical and useful. Indeed, we witness even greater examples of bubbles and busts abroad than in the United States. We then create a trading system to build global stock portfolios, and find significant outperformance by selecting markets based on relative and absolute valuation.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    Carlota Perez draws upon Schumpeter's theories of the clustering of innovations to explain why each technological revolution gives rise to a paradigm shift and a "New Economy" and how these "opportunity explosions", focused on specific industries, also lead to the recurrence of financial bubbles and crises. These findings are illustrated with examples from the past two centuries: the industrial revolution, the age of steam and railways, the age of steel and electricity, the emergence of mass production and automobiles, and the current information revolution/knowledge society. By analyzing the changing relationship between finance capital and production capital during the emergence, diffusion and assimilation of new technologies throughout the global economic system, this book sheds light on some of the most pressing economic problems of today.

    Porter). We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you catalyze your organization's strategy development and execution.HBR's 10 Must Reads on Strategy will inspire you to:• Distinguish your company from rivals• Clarify what your company will and won't do• Craft a vision for an uncertain future• Create blue oceans of uncontested market space• Use the Balanced Scorecard to measure your strategy• Capture your strategy in a memorable phrase• Make priorities explicit• Allocate resources early• Clarify decision rights for faster decision making"This collection of best-selling articles includes: featured article "What Is Strategy?" by Michael E. Porter, "The Five Competitive Forces That Shape Strategy," "Building Your Company's Vision," "Reinventing Your Business Model," "Blue Ocean Strategy," "The Secrets to Successful Strategy Execution," "Using the Balanced Scorecard as a Strategic Management System," "Transforming Corner-Office Strategy into Frontline Action," "Turning Great Strategy into Great Performance," and "Who Has the D? How Clear Decision Roles Enhance Organizational Performance."

    Thorp invented card counting, proving the seemingly impossible: that you could beat the dealer at the blackjack table. As a result he launched a gambling renaissance. His remarkable success--and mathematically unassailable method--caused such an uproar that casinos altered the rules of the game to thwart him and the legions he inspired. They barred him from their premises, even put his life in jeopardy. Nonetheless, gambling was forever changed.Thereafter, Thorp shifted his sights to "the biggest casino in the world" Wall Street. Devising and then deploying mathematical formulas to beat the market, Thorp ushered in the era of quantitative finance we live in today. Along the way, the so-called godfather of the quants played bridge with Warren Buffett, crossed swords with a young Rudy Giuliani, detected the Bernie Madoff scheme, and, to beat the game of roulette, invented, with Claude Shannon, the world's first wearable computer.Here, for the first time, Thorp tells the story of what he did, how he did it, his passions and motivations, and the curiosity that has always driven him to disregard conventional wisdom and devise game-changing solutions to seemingly insoluble problems. An intellectual thrill ride, replete with practical wisdom that can guide us all in uncertain financial waters, A Man for All Markets is an instant classic--a book that challenges its readers to think logically about a seemingly irrational world.Praise for A Man for All Markets"In A Man for All Markets, [Thorp] delightfully recounts his progress (if that is the word) from college teacher to gambler to hedge-fund manager. Along the way we learn important lessons about the functioning of markets and the logic of investment."--The Wall Street Journal"[Thorp] gives a biological summation (think Richard Feynman's Surely You're Joking, Mr. Feynman!) of his quest to prove the aphorism 'the house always wins' is flawed. . . . Illuminating for the mathematically inclined, and cautionary for would-be gamblers and day traders"-- Library Journal

    Klein and Michael Pettis show in this book, they are often the unexpected result of domestic political choices to serve the interests of the rich at the expense of workers and ordinary retirees.   Klein and Pettis trace the origins of today’s trade wars to decisions made by politicians and business leaders in China, Europe, and the United States over the past thirty years. Across the world, the rich have prospered while workers can no longer afford to buy what they produce, have lost their jobs, or have been forced into higher levels of debt. In this thought-provoking challenge to mainstream views, the authors provide a cohesive narrative that shows how the class wars of rising inequality are a threat to the global economy and international peace—and what we can do about it.

    The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for shastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.This book is being published in two volumes. This second volume develops shastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time.Masters level students and researchers in mathematical finance and financial engineering will find this book useful.Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education.

    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!

    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. .

    The 17th Edition builds upon the tradition of leadership with three main goals: help the beginning student master the principles essential for understanding the economizing problem, specific economic issues, and the policy alternatives; help the student understand and apply the economic perspective and reason accurately and objectively about economic matters; and promote a lasting student interest in economics and the economy."

    This book takes you beyond the currency ("Blockchain 1.0") and smart contracts ("Blockchain 2.0") to demonstrate how the blockchain is in position to become the fifth disruptive computing paradigm after mainframes, PCs, the Internet, and mobile/social networking. Author Melanie Swan, Founder of the Institute for Blockchain Studies, explains that the blockchain is essentially a public ledger with potential as a worldwide, decentralized record for the registration, inventory, and transfer of all assets—not just finances, but property and intangible assets such as votes, software, health data, and ideas. Topics include: Concepts, features, and functionality of Bitcoin and the blockchain Using the blockchain for automated tracking of all digital endeavors Enabling censorship?resistant organizational models Creating a decentralized digital repository to verify identity Possibility of cheaper, more efficient services traditionally provided by nations Blockchain for science: making better use of the data-mining network Personal health record storage, including access to one’s own genomic data Open access academic publishing on the blockchain This book is part of an ongoing O’Reilly series. Mastering Bitcoin: Unlocking Digital Crypto-Currencies introduces Bitcoin and describes the technology behind Bitcoin and the blockchain. Blockchain: Blueprint for a New Economy considers theoretical, philosophical, and societal impact of cryptocurrencies and blockchain technologies.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

     -Byte, September 1995 I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up. -Charles Long If you think you're a really good programmer... read [Knuth's] Art of Computer Programming... You should definitely send me a resume if you can read the whole thing. -Bill Gates It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers. -Jonathan Laventhol This first volume in the series begins with basic programming concepts and techniques, then focuses more particularly on information structures-the representation of information inside a computer, the structural relationships between data elements and how to deal with them efficiently. Elementary applications are given to simulation, numerical methods, symbolic computing, software and system design. Dozens of simple and important algorithms and techniques have been added to those of the previous edition. The section on mathematical preliminaries has been extensively revised to match present trends in research. Ebook (PDF version) produced by Mathematical Sciences Publishers (MSP), http: //msp.org