Agent-based simulations of financial markets: zero- and positive-intelligence models
Authored by James R Thompson, James R Wilson
Date Published: 2015
DOI: 10.1177/0037549715582252
Sponsors:
No sponsors listed
Platforms:
MASON
Model Documentation:
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Model Code URLs:
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Abstract
To analyze the impact of intelligent traders with differing fundamental
motivations on agent-based simulations of financial markets, we
construct both zero-intelligence and positive-intelligence models of
those markets using the MASON agent-based modeling framework. We exploit
our software implementation of multifractal detrended fluctuation
analysis (MF-DFA) to analyze the price paths generated by both
simulation models as well as the price paths of selected stocks traded
on the New York Stock Exchange. We study the changes in the models'
macrolevel price paths when altering some of the microlevel agent
behaviors; and we compare and contrast the multifractal properties of
the zero- and positive-intelligence price paths with those properties of
the selected real price paths. For the positive-intelligence and real
price paths, we generally observed long-range dependence in the
small-magnitude fluctuations and short-range dependence in the
large-magnitude fluctuations. On the other hand, the zero-intelligence
price paths failed to exhibit the multifractal properties seen in the
selected real price paths.
Tags
Detrended fluctuation analysis