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"Half of all Americans have money in the stock market, yet economists can’t agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe. The debate is one of the biggest in economics, and the value or futility of investment management and financial regulation hangs on the answer. In this groundbreaking book, Andrew Lo transforms the debate with a powerful new framework in which rationality and irrationality coexist—the Adaptive Markets Hypothesis. Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency is 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. An ambitious new answer to fundamental questions about economics and investing, Adaptive Markets is essential reading for anyone who wants to understand how markets really work." -- Publisher's description.
Investments --- Stock exchanges. --- Efficient market theory. --- Psychological aspects. --- Market theory, Efficient --- Capital market --- Stock exchanges --- Bulls and bears --- Commercial corners --- Corners, Commercial --- Equity markets --- Exchanges, Securities --- Exchanges, Stock --- Securities exchanges --- Stock-exchange --- Stock markets --- Efficient market theory --- Speculation --- Adaptive market hypothesis. --- Arbitrage. --- Asset. --- Bank run. --- Bank. --- Behavior. --- Behavioral economics. --- Biology. --- Broker-dealer. --- Calculation. --- Career. --- Central bank. --- Competition. --- Cryptocurrency. --- Currency. --- Customer. --- Debt. --- Decision-making. --- Economics. --- Economist. --- Ecosystem. --- Efficient-market hypothesis. --- Employment. --- Entrepreneurship. --- Equity Market. --- Evolution. --- Finance. --- Financial crisis of 2007–08. --- Financial crisis. --- Financial economics. --- Financial innovation. --- Financial institution. --- Financial services. --- Financial technology. --- Forecasting. --- Fraud. --- Funding. --- Hedge Fund Manager. --- Hedge fund. --- Heuristic. --- Homo economicus. --- Human behavior. --- Incentive. --- Income. --- Insider. --- Insurance. --- Interest rate. --- Investment strategy. --- Investment. --- Investor. --- Leverage (finance). --- Macroeconomics. --- Margin (finance). --- Market (economics). --- Market Dynamics. --- Market liquidity. --- Market maker. --- Market price. --- Market trend. --- Myron Scholes. --- Narrative. --- Paul Samuelson. --- Ponzi scheme. --- Portfolio manager. --- Prediction. --- Prefrontal cortex. --- Probability matching. --- Probability. --- Psychology. --- Random walk hypothesis. --- Rational expectations. --- Rationality. --- Result. --- Risk aversion. --- Risk management. --- S&P 500 Index. --- Salary. --- Saving. --- Scientist. --- Share price. --- Sociobiology. --- Speculation. --- Stock market crash. --- Stock market. --- Supply (economics). --- Systemic risk. --- Technology. --- The Wisdom of Crowds. --- Theory. --- Thought experiment. --- Thought. --- Time series. --- Trade-off. --- Trader (finance). --- Trading strategy. --- Uncertainty. --- Venture capital. --- Warren Buffett. --- Wealth. --- Year.
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An essential guide to recognizing bogus numbers and misleading dataNumbers are often intimidating, confusing, and even deliberately deceptive-especially when they are really big. The media loves to report on millions, billions, and trillions, but frequently makes basic mistakes or presents such numbers in misleading ways. And misunderstanding numbers can have serious consequences, since they can deceive us in many of our most important decisions, including how to vote, what to buy, and whether to make a financial investment. In this short, accessible, enlightening, and entertaining book, leading computer scientist Brian Kernighan teaches anyone-even diehard math-phobes-how to demystify the numbers that assault us every day.With examples drawn from a rich variety of sources, including journalism, advertising, and politics, Kernighan demonstrates how numbers can mislead and misrepresent. In chapters covering big numbers, units, dimensions, and more, he lays bare everything from deceptive graphs to speciously precise numbers. And he shows how anyone-using a few basic ideas and lots of shortcuts-can easily learn to recognize common mistakes, determine whether numbers are credible, and make their own sensible estimates when needed.Giving you the simple tools you need to avoid being fooled by dubious numbers, Millions, Billions, Zillions is an essential survival guide for a world drowning in big-and often bad-data.
Numbers, Complex. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Complex numbers --- Imaginary quantities --- Quantities, Imaginary --- Algebra, Universal --- Quaternions --- Vector analysis --- A picture is worth a thousand words. --- AARP. --- American Medical Association. --- Approximation. --- Arithmetic mean. --- Arithmetic. --- Associated Press. --- Baby boomers. --- Back-of-the-envelope calculation. --- Barrel (unit). --- Birth rate. --- Blogger (service). --- Body surface area. --- Breast cancer. --- Calculation. --- Celsius. --- Centenarian. --- Computation. --- Consumer Reports. --- Corporate tax. --- Correlation does not imply causation. --- Daniel Kahneman. --- Darrell Huff. --- Dilbert. --- Dot-com bubble. --- Economics. --- Edward Tufte. --- Error. --- Estimation. --- Exabyte. --- Exponential growth. --- FLOPS. --- Factoid. --- Fermi problem. --- Gigabyte. --- Half Gone. --- Headline. --- Hectare. --- Home computer. --- How to Lie with Statistics. --- Hulu. --- Identity theft. --- Inception. --- Inflation. --- Innumeracy (book). --- Jeff Bezos. --- John Maynard Keynes. --- Just in case. --- Kilobit. --- Kilogram. --- Life expectancy. --- Little's law. --- Millionth. --- Mortality rate. --- My Local. --- Naomi Wolf. --- National Rifle Association. --- Net worth. --- Newspaper. --- Newsweek. --- Nobel Prize. --- Order of magnitude. --- Outright. --- Percentage point. --- Percentage. --- Petabit. --- Petabyte. --- Population growth. --- Pound sterling. --- Power of 10. --- Quadrillion. --- Quantity. --- Ranking (information retrieval). --- Result. --- Round number. --- Rule of 72. --- Sampling bias. --- School bus. --- Scientific notation. --- Square foot. --- Square yard. --- Strategic Petroleum Reserve (United States). --- Tax cut. --- Tax. --- Technology. --- Terabit. --- The Beauty Myth. --- The Colbert Report. --- The New York Times. --- The Wisdom of Crowds. --- The World's Billionaires. --- U.S. News & World Report. --- Ultra-high-definition television. --- Unemployment. --- W. E. B. Du Bois. --- Warren Buffett. --- With high probability. --- Year. --- Your Computer (British magazine). --- Zettabyte. --- Mathematics --- Mathematics in mass media --- Critical thinking --- Statistics --- Big data --- Million (The number) --- Billion (The number) --- Evaluation --- Methodology
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