| Authors: |
Chia-Hsuan Yeh
and Shu-Heng Chen
|
| URL: |
http://fmwww.bc.edu/cef00/papers/paper338.pdf |
| Tags: |
Agent-Based
Annealing
Artificial
Computation,
Evolutionary
Market,
Modelling,
Simulated
Stock
algorithms,
genetic
programming,
|
| Abstract: |
Artificial stock market is a growing field in the past
few years. The essence of this issue is the interaction
between many heterogeneous agents. In order to model
this complex adaptive system, the techniques of
evolutionary computation have been employed. Chen and
Yeh (2000) proposed a new architecture to construct the
artificial stock market. This framework is composed of
a single-population genetic programming (SGP) based
adaptive agent with a SA (Simulated Annealing) learning
process and a business school.
However, one of the drawbacks of SGP-based framework is
that the traders can't work out new ideas by
themselves. The only way is to consult researchers in
the business school. In order to make the traders more
intelligent, we employ multi-population GP (MGP) based
framework with the mechanism of school. This extension
is not only reasonable, but also has the economic
implications. How do the more intelligent agents
influence the economy? Are the econometric properties
of the simulation results based on MGP more like the
phenomena found in the real stock market? In this
paper, the comparison between SGP and MGP is studied
from two sides. One is related to the micro-structure,
traders? behaviour and believe. The other is
macro-properties, the properties of time series. The
line of research is helpful in understanding the
foundation of economics and finance, and constructing
more realistic economic models. |
@inproceedings{Shu-HengChen2:2000:CEF,
title = {Toward an integration of social learning and
individual learning in agent-based computational stock
markets:the approach based on population genetic
programming},
address = {Universitat Pompeu Fabra, Barcelona, Spain},
author = {Chia-Hsuan Yeh and Shu-Heng Chen},
booktitle = {Computing in Economics and Finance},
month = {6-8 July},
url = {http://fmwww.bc.edu/cef00/papers/paper338.pdf},
year = {2000},
abstract = {Artificial stock market is a growing field in the past
few years. The essence of this issue is the interaction
between many heterogeneous agents. In order to model
this complex adaptive system, the techniques of
evolutionary computation have been employed. Chen and
Yeh (2000) proposed a new architecture to construct the
artificial stock market. This framework is composed of
a single-population genetic programming (SGP) based
adaptive agent with a SA (Simulated Annealing) learning
process and a business school.
However, one of the drawbacks of SGP-based framework is
that the traders can't work out new ideas by
themselves. The only way is to consult researchers in
the business school. In order to make the traders more
intelligent, we employ multi-population GP (MGP) based
framework with the mechanism of school. This extension
is not only reasonable, but also has the economic
implications. How do the more intelligent agents
influence the economy? Are the econometric properties
of the simulation results based on MGP more like the
phenomena found in the real stock market? In this
paper, the comparison between SGP and MGP is studied
from two sides. One is related to the micro-structure,
traders? behaviour and believe. The other is
macro-properties, the properties of time series. The
line of research is helpful in understanding the
foundation of economics and finance, and constructing
more realistic economic models.},
notes = {http://enginy.upf.es/SCE/index2.html
22 Aug 2004 updated from
http://econpapers.hhs.se/paper/scescecf0/338.htm
Chung-Chi Liao was listed as co-author due to confusion
with \cite{RePEc:sce:scecf0:328} also in CEF 2001}, size = {31 pages},
keywords = {Agent-Based Annealing Artificial Computation, Evolutionary Market, Modelling, Simulated Stock algorithms, genetic programming, }
}
::