- Princeton University Press
Hedge Funds: An Analytic Perspective - Updated Edition
Key Metrics
- Andrew W Lo
- Princeton University Press
- Paperback
- 9780691145983
- 9.1 X 6.1 X 1 inches
- 1.3 pounds
- Business & Economics > Investments & Securities - General
- English
Book Description
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.
Author Bio
Andrew W. Lo is the Charles E. and Susan T. Harris Professor, a Professor of Finance, and the Director of the Laboratory for Financial Engineering at the MIT Sloan School of Management.
His current research spans five areas: evolutionary models of investor behavior and adaptive markets, systemic risk and financial regulation, quantitative models of financial markets, financial applications of machine-learning techniques and secure multi-party computation, and healthcare finance.
Recent projects include: deriving risk aversion, loss aversion, probability matching, and other behaviors as emergent properties of evolution in stochastic environments; constructing new measures of systemic risk and comparing them across time and systemic events; applying spectral analysis to investment strategies to decompose returns into fundamental frequencies; and developing new statistical tools for predicting clinical trial outcomes, incorporating patient preferences into the drug approval process, and accelerating biomedical innovation via novel financing structures.
Lo has published extensively in academic journals (see http://alo.mit.edu) and his most recent book is Adaptive Markets: Financial Evolution at the Speed of Thought. His awards include Batterymarch, Guggenheim, and Sloan Fellowships; the Paul A. Samuelson Award; the Eugene Fama Prize; the IAFE-SunGard Financial Engineer of the Year; the Global Association of Risk Professionals Risk Manager of the Year; the Harry M. Markowitz Award; the Managed Futures Pinnacle Achievement Award; one of TIME’s “100 most influential people in the world”; and awards for teaching excellence from both Wharton and MIT.
His book Adaptive Markets has also received a number of awards, listed here. He is a Fellow of Academia Sinica; the American Academy of Arts and Sciences; the Econometric Society; and the Society of Financial Econometrics.
Lo is also a principal investigator at the MIT Computer Science and Artificial Intelligence Laboratory, an affiliated faculty member of the MIT Department of Electrical Engineering and Computer Science, an external faculty member of the Santa Fe Institute, and a research associate of the National Bureau of Economic Research.
He is a member of the New York Federal Reserve Board’s Financial Advisory Roundtable, FINRA’s Economic Advisory Committee, the National Academy of Sciences Board on Mathematical Sciences and Their Applications, Beth Israel Deaconess Medical Center’s Board of Overseers, and the boards of Roivant Sciences and the Whitehead Institute for Biomedical Research.
Lo holds a BA in economics from Yale University and an AM and PhD in economics from Harvard University.
Source: MIT Sloan School of Management
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