The hedge fund industry has grown dramatically over the last two decades, with more than eight thousand funds now controlling close to two trillion dollars. Originally intended for the wealthy, these private investments have now attracted a much broader following that includes pension funds and retail investors. Because hedge funds are largely unregulated and shrouded in secrecy, they have developed a mystique and allure that can beguile even the most experienced investor. In Hedge Funds, Andrew Lo--one of the world's most respected financial economists--addresses the pressing need for a systematic framework for managing hedge fund investments. Arguing that hedge funds have very different risk and return characteristics than traditional investments, Lo constructs new tools for analyzing their dynamics, including measures of illiquidity exposure and performance smoothing, linear and nonlinear risk models that capture alternative betas, econometric models of hedge fund failure rates, and integrated investment processes for alternative investments. In a new chapter, he looks at how the strategies for and regulation of hedge funds have changed in the aftermath of the financial crisis.
The Adaptive Markets Hypothesis is a formal and systematic exposition. Lo and Zhang develop the mathematical foundations of the simple yet powerful evolutionary model and show that the most fundamental economic behaviours that we take for granted emerge solely through natural selection.
The hedge fund industry has grown dramatically over the last two decades, with more than eight thousand funds now controlling close to two trillion dollars. Originally intended for the wealthy, these private investments have now attracted a much broader following that includes pension funds and retail investors. Because hedge funds are largely unregulated and shrouded in secrecy, they have developed a mystique and allure that can beguile even the most experienced investor. In Hedge Funds, Andrew Lo--one of the world's most respected financial economists--addresses the pressing need for a systematic framework for managing hedge fund investments. Arguing that hedge funds have very different risk and return characteristics than traditional investments, Lo constructs new tools for analyzing their dynamics, including measures of illiquidity exposure and performance smoothing, linear and nonlinear risk models that capture alternative betas, econometric models of hedge fund failure rates, and integrated investment processes for alternative investments. In a new chapter, he looks at how the strategies for and regulation of hedge funds have changed in the aftermath of the financial crisis.
A new, evolutionary explanation of markets and investor behavior 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.
An introductory finance textbook for the healthcare industry We are living in a golden age of biomedical innovation, yet entrepreneurs still struggle with the so-called Valley of Death when seeking funding for their biotech start-ups. In Healthcare Finance, Andrew Lo and Shomesh Chaudhuri show that there are better ways to finance breakthrough therapies, and they provide the essential financial tools and concepts for creating the next generation of healthcare technologies. Geared for MBA and life sciences students, as well as biopharma executives and healthcare investment professionals, this textbook covers the theory and application of financial techniques such as diversification, discounted cash flow analysis, real options, Monte Carlo simulation, and securitization, all within the context of managing biomedical assets. The book demonstrates that more efficient funding structures can reduce financial risks, lower the cost of capital, and bring more lifesaving therapies to patients faster. Readers will gain the background, framework, and techniques needed to reshape the healthcare industry in positive ways. Finance doesn’t have to be a zero-sum game, and Healthcare Finance proves that it is possible to do well by doing good. Explores new financing methods for the biopharma industry Provides accessible explanations for making good business decisions in the life sciences Analyzes real-world examples, case studies, and practical applications Includes access to videos of lectures and recitations, interactive figures, self-graded problem sets, and other online content
How the greatest thinkers in finance changed the field and how their wisdom can help investors today Is there an ideal portfolio of investment assets, one that perfectly balances risk and reward? In Pursuit of the Perfect Portfolio examines this question by profiling and interviewing ten of the most prominent figures in the finance world—Jack Bogle, Charley Ellis, Gene Fama, Marty Leibowitz, Harry Markowitz, Bob Merton, Myron Scholes, Bill Sharpe, Bob Shiller, and Jeremy Siegel. We learn about the personal and intellectual journeys of these luminaries—which include six Nobel Laureates and a trailblazer in mutual funds—and their most innovative contributions. In the process, we come to understand how the science of modern investing came to be. Each of these finance greats discusses their idea of a perfect portfolio, offering invaluable insights to today’s investors. Inspiring such monikers as the Bond Guru, Wall Street’s Wisest Man, and the Wizard of Wharton, these pioneers of investment management provide candid perspectives, both expected and surprising, on a vast array of investment topics—effective diversification, passive versus active investment, security selection and market timing, foreign versus domestic investments, derivative securities, nontraditional assets, irrational investing, and so much more. While the perfect portfolio is ultimately a moving target based on individual age and stage in life, market conditions, and short- and long-term goals, the fundamental principles for success remain constant. Aimed at novice and professional investors alike, In Pursuit of the Perfect Portfolio is a compendium of financial wisdom that no market enthusiast will want to be without.
A comprehensive history of the evolution of technical analysis from ancient times to the Internet age Whether driven by mass psychology, fear or greed of investors, the forces of supply and demand, or a combination, technical analysis has flourished for thousands of years on the outskirts of the financial establishment. In The Evolution of Technical Analysis: Financial Prediction from Babylonian Tablets to Bloomberg Terminals, MIT's Andrew W. Lo details how the charting of past stock prices for the purpose of identifying trends, patterns, strength, and cycles within market data has allowed traders to make informed investment decisions based in logic, rather than on luck. The book Reveals the origins of technical analysis Compares and contrasts the Eastern practices of China and Japan to Western methods Details the contributions of pioneers such as Charles Dow, Munehisa Homma, Humphrey B. Neill, and William D. Gann The Evolution of Technical Analysis explores the fascinating history of technical analysis, tracing where technical analysts failed, how they succeeded, and what it all means for today's traders and investors.
The Heretics of Finance provides extraordinary insight into both the art of technical analysis and the character of the successful trader. Distinguished MIT professor Andrew W. Lo and researcher Jasmina Hasahodzic interviewed thirteen highly successful, award-winning market professionals who credit their substantial achievements to technical analysis. The result is the story of technical analysis in the words of the people who know it best; the lively and candid interviews with these gurus of technical analysis. The first half of the book focuses on the technicians' careers: How and why they learned technical analysis What market conditions increase their chances of making mistakes What their average workday is like To what extent trading controls their lives Whether they work on their own or with a team How their style of technical analysis is unique The second half concentrates on technical analysis and addresses questions such as these: Did the lack of validation by academics ever cause you to doubt technical analysis? Can technical analysis be applied to other disciplines? How do you prove the validity of the method? How has computer software influenced the craft? What is the role of luck in technical analysis? Are there laws that underlie market action? What traits characterize a highly successful trader? How do you test patterns before you start using them with real money? Interviewees include: Ralph J. Acampora, Laszlo Birinyi, Walter Deemer, Paul Desmond, Gail Dudack, Robert J. Farrell, Ian McAvity, John Murphy, Robert Prechter, Linda Raschke, Alan R. Shaw, Anthony Tabell, Stan Weinstein.
For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a state-of-the-art account of the techniques for detecting predictabilities and evaluating their statistical and economic significance, and offers a tantalizing glimpse into the financial technologies of the future. The articles track the exciting course of Lo and MacKinlay's research on the predictability of stock prices from their early work on rejecting random walks in short-horizon returns to their analysis of long-term memory in stock market prices. A particular highlight is their now-famous inquiry into the pitfalls of "data-snooping biases" that have arisen from the widespread use of the same historical databases for discovering anomalies and developing seemingly profitable investment strategies. This book invites scholars to reconsider the Random Walk Hypothesis, and, by carefully documenting the presence of predictable components in the stock market, also directs investment professionals toward superior long-term investment returns through disciplined active investment management.
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). The book examines and presents, in a systematic manner, computational probability methods that encompass data structures and algorithms. The developed techniques address problems that require exact probability calculations, many of which have been considered intractable in the past. The book addresses the plight of the probabilist by providing algorithms to perform calculations associated with random variables. Computational Probability: Algorithms and Applications in the Mathematical Sciences, 2nd Edition begins with an introductory chapter that contains short examples involving the elementary use of APPL. Chapter 2 reviews the Maple data structures and functions necessary to implement APPL. This is followed by a discussion of the development of the data structures and algorithms (Chapters 3–6 for continuous random variables and Chapters 7–9 for discrete random variables) used in APPL. The book concludes with Chapters 10–15 introducing a sampling of various applications in the mathematical sciences. This book should appeal to researchers in the mathematical sciences with an interest in applied probability and instructors using the book for a special topics course in computational probability taught in a mathematics, statistics, operations research, management science, or industrial engineering department.
Half of all Americans have money in the stock market, yet economists can't agree on whether investors and markets are ration and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe - and as financial bubbles, crashes, and crises suggest. 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 marked 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."--Inside flap.
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