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Maximizing Predictability in the Stock and Bond Markets

Maximizing Predictability in the Stock and Bond Markets

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  • Andrew W Lo
  • Sagwan Press
  • Hardcover
  • 9781340082222
  • 9.21 X 6.14 X 0.25 inches
  • 0.6 pounds
  • History > General
  • English
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Book Description

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Maximizing Predictability in the Stock and Bond Markets

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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