Warning: Physics Envy May be Hazardous to Your Wealth
06/05/2010 1:00 PM Wong AuditoriumAndrew W. Lo, Harris & Harris Group Professor, Director, MIT Laboratory for Financial EngineeringDescription: In this talk Andrew Lo addresses the problem of finding the right level of abstraction with which to think about economic phenomena. He compares economics to physics, with some surprising results.
For at least several decades economics theorists have assumed that the
highest level of abstraction is the best. Lo argues that this
assumption has stemmed from what he calls "physics envy": the enviable
ability to explain a huge range of phenomena with a small number of
rules or laws.
Admittedly physics envy has led to the development of many useful ideas,
including utility theory, game theory, and general equilibrium theory,
among others. These have been real successes; however Lo
takes up the argument recently made by some observers that the recent
fiscal crisis is evidence that economics is by the nature of its subject
matter not reducible to a small number of general laws.
The possibility that a certain level of abstraction can be inappropriate
for a given material raises the question of how to know what level is
right where. Lo addresses this issue with a distinction originally made
in the 1920's between risk and uncertainty which has been further developed into the Ellsberg Paradox. Both terms refer to
unknowns, but in this formulation, "risk" refers to the category of
unknown that is governed by defined probabilities. You do not know
whether a flipped coin will land heads or tails, but you do know, with certainty, that the odds of either outcome is 50" 50. "Uncertainty" refers to unknowns in which the odds of a given outcome are not known and even can not be known, such as the odds of running into an old friend you have not seen for years on the street tomorrow.
Recently Lo and physicist Mark T. Mueller developed this polarity into
a spectrum of types or kinds of unknowns. These run from well" defined
cases like the coin toss, through types in which, while the odds of a
given outcome are unknown now, it is pretty clear how to go about making
them known, to unknowns that are so complex that there is no way to even
begin to get a handle on them, to cases that are a confusing mixture of
all three. Lo demonstrates an instrument developed by researchers that allows managers and analysts to assess what kind of unknowns they are dealing with at any given time, and therefore to get a sense of what level of abstraction might reasonably be expected to be useful for that particular material.
In response to a question, Lo observed that the highest rewards seem to
flow to people who deal successfully with the most profound levels of
unknowns. He concluded by speculating that people with a very high level
of self"confidence might be able to use his instrument to pick the most
intractable unknowns facing society. If they pick right, and then
manage those unknowns successfully, they should do well.
About the Speaker(s): Andrew Lo's research interests include the empirical validation and implementation of financial asset pricing models; the pricing of options and other derivative securities; financial engineering and risk management; trading technology and market microstructure; statistics, econometrics, and stochastic processes; computer algorithms and numerical methods; financial visualization; nonlinear models of stock and bond returns; hedge"fund risk and return dynamics and risk transparency; and, most recently, evolutionary and neurobiological models of individual risk preferences and financial markets.
He has published numerous articles in finance and economics journals, and is a co"author of The Econometrics of Financial Markets and A Non"Random Walk Down Wall Street, and author of Hedge Funds: An Analytic Perspective. He is currently an associate editor of the Financial Analysts Journal, the Journal of Portfolio Management, the Journal of Computational Finance, and Statistica Sinica.
Lo is a former governor of the Boston Stock Exchange, and currently a research associate of the National Bureau of Economic Research, a member of the NASD's Economic Advisory Board, and founder and chief scientific officer of AlphaSimplex Group, LLC, a quantitative investment management company based in Cambridge, Massachusetts.
Lo received his Ph.D. in economics from Harvard University in 1984, and taught at the University of Pennsylvania's Wharton School 1984 to 1988.
Harris & Harris Group Professor of Finance, MIT Sloan School of Management
Director, MIT Laboratory for Financial Engineering
Host(s): Sloan School of Management, MIT Sloan School of Management
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