By
Haim Levy, The Hebrew University of Jerusalem, Mt. Scopus, Israel
Moshe Levy, The Hebrew University of Jerusalem, Mt. Scopus, Israel
Sorin Solomon, The Hebrew University of Jerusalem, Mt. Scopus, Israel
Description
Microscopic Simulation (MS) uses a computer to represent and keep track of individual ("microscopic") elements in order to investigate
complex systems which are analytically intractable. A methodology that was developed to solve physics problems, MS has been used to study
the relation between microscopic behavior and macroscopic phenomena in systems ranging from those of atomic particles, to cars, animals,
and even humans. In finance, MS can help explain, among other things, the effects of various elements of investor behavior on market
dynamics and asset pricing. It is these issues in particular, and the value of an MS approach to finance in general, that are the subjects
of this book. The authors not only put their work in perspective by surveying traditional economic analyses of investor behavior, but
they also briefly examine the use of MS in fields other than finance.
Most models in economics and finance assume that investors are
rational. However, experimental studies reveal systematic deviations from rational behavior. How can we determine the effect of investors'
deviations from rational behavior on asset prices and market dynamics? By using Microscopic Simulation, a methodology originally developed
by physicists for the investigation of complex systems, the authors are able to relax classical assumptions about investor behavior and
to model it as empirically and experimentally observed. This rounded and judicious introduction to the application of MS in finance and
economics reveals that many of the empirically-observed "puzzles" in finance can be explained by investors' quasi-rationality.
Researchers
use the book because it models heterogeneous investors, a group that has proven difficult to model. Being able to predict how people
will invest and setting asset prices accordingly is inherently appealing, and the combination of computing power and statistical mechanics
in this book makes such modeling possible. Because many finance researchers have backgrounds in physics, the material here is accessible.
Audience:
University and commercial finance researchers, and graduate students.
