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From: McClelland_R <McClelland_R(a)dcgate.bls.gov>
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Subject: SNDE_L FW: Artificial Stock Market working paper available
Date: Tue, 7 Jan 1997 10:03:29 -0500
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<bigger>
Asset Pricing Under Endogenous Expectations in an Artificial Stock
Market
by
W. B. Arthur, J. H. Holland, , B. LeBaron, R. G. Palmer, and P. Tayler
ABSTRACT:
We propose a theory of asset pricing based on heterogeneous agents
who continually adapt their expectations to the market that these
expectations aggregatively create. And we explore the implications of
this theory computationally using our Santa Fe artificial stock market.
Asset markets, we argue, have a recursive nature in that agents'
expectations are formed on the basis of their anticipations of
other agents' expectations, which precludes expectations being
formed by deductive means. Instead, traders continually
hypothesize (continually explore) expectational models, buy or sell
on the basis of those that perform best, and confirm or discard these
according to their performance. Thus, individual beliefs or expectations
become endogenous to the market, and constantly compete within an
ecology of others' beliefs or expectations. The ecology of beliefs
co-evolves over time.
Computer experiments with this endogenous-expectations market explain
one of the more striking puzzles in finance: that market traders often
believe in such concepts as technical trading, "market psychology,"
and bandwagon effects, while academic theorists believe in market
efficiency
and a lack of speculative opportunities. Both views, we show, are
correct, but within different regimes. Within a regime where investors
explore alternative expectational models at a low rate, the market
settles into the rational-expectations equilibrium of the
efficient-market
literature. Within a regime where the rate of exploration of
alternative
expectations is higher, the market self-organizes into a complex pattern.
It acquires a rich psychology, technical trading emerges, temporary
bubbles
and crashes occur, and asset prices and trading volume show statistical
features (in particular, GARCH behavior) characteristic of actual market
data.
Postscript is available at:
http://www.santafe.edu/sfi/publications/96wplist.html
Paper copies can be requested from:
wp(a)santafe.edu
(All authors are affiliated with the Santa Fe Institute where Arthur is
the
Citibank Professor. In addition, Holland is Professor of Computer
Science
and Engineering, University of Michigan, Ann Arbor; LeBaron is Associate
Professor of Economics, University of Wisconsin, Madison; Palmer is
Professor of Physics, Duke University; and Tayler is with the Dept. of
Computer Science, Brunel University, London.)
</bigger>
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