Summary
This paper presents the results from an agent-based stock market with a Walrasian auctioneer (Walrasian adaptive simulation market, abbrev.: WASIM) based on the Santa Fe artificial stock market (SF-ASM, see e.g. [1], [2],[3],[4],[5]). The model is purposely simple in order to show that a parsimonious nonlinear framework with an equilibrium model can replicate typical stock market phenomena including phases of speculative bubbles and market crashes. As in the original SF-ASM, agents invest in a risky stock (with price p t and stochastic dividend d t ) or in a risk-free asset. One of the properties of SF-ASM is that the microscopic wealth of the agents has no influence on the macroscopic price of the risky asset (see [5]). Moreover, SF-ASM uses trading restrictions which can lead to a deviation from the underlying equilibrium model. Our simulation market uses a Walrasian auctioneer to overcome these shortcomings, i.e. the auctioneer builds a causality between wealth of each agent and the arising price function of the risky asset, and the auctioneer iterates toward the equilibrium. The Santa Fe artificial stock market has been criticized because the mutation operator for producing new trading rules is not bit-neutral (see [6]). That means with the original SF-ASM mutation operator the trading rules are generalized, which also could be interpreted as a special market design. However, using the original non bit-neutral mutation operator with fast learning agents there is a causality between the used technical trading rules and a deviation from an intrinsic value of the risky asset in SF-ASM. This causality gets lost when using a bit-neutral mutation operator. WASIM uses this bit-neutral mutation operator and presents a model in which high fluctuations and deviations occur due to extreme wealth concentrations. We introduce a Herfindahl index measuring these wealth concentrations and show reasons for arising of market monopolies. Instabilities diminish with introducing a Tobin tax which avoids that rich and influential agents emerge.
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References
LeBaron B, Arthur WB, Palmer R, Holland JH, Tayler P (1997) Asset pricing under endogenous expectations in an artificial stock market. In: Arthur WB, Durlauf S, Lane D (eds) The economy as an evolving complex system II. Addison-Wesley
LeBaron B, Arthur WB, Palmer R (1999) Time series properties of an artificial stock market. Journal of Economic Dynamics and Control 23:1487–1516
Tesfatsion L (2002) Notes on the Santa Fe artificial stock market model. Econ 308x: Agent-based Computational Economics
Seese D, Stumpert T (2003) Influence of heterogeneous agents on market structure in an artificial stock market. Proceedings of Annual Workshop on Economics with Heterogeneous Interacting Agents, WEHIA 2003, Kiel
LeBaron B (2002) Building the Santa Fe Artificial Stock Market. Working Paper, Brandeis University
Ehrentreich N (2003) A corrected version of the Santa Fe institute artificial stock market model. Complexity 2003: Second Workshop of the Society for Computational Economics.
Cont R (2001). Emperical properties of asset returns: Stylized facts and statistical issues. Quantitative Finance Volume 1:223–236
Walras L (1874) Eléments d’économie politique pure. [English Translation: Elements of Pure Economics of the Theory of Social Wealth. Irwin RD, Homewood, 1926] Corbaz L (eds) Lausanne
Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley
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© 2006 Springer-Verlag Berlin Heidelberg
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Stümpert, T., Seese, D., Sunderkötter, M. (2006). Time Series Properties from an Artificial Stock Market with a Walrasian Auctioneer. In: Beckmann, M., et al. Artificial Economics. Lecture Notes in Economics and Mathematical Systems, vol 564. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28547-4_1
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DOI: https://doi.org/10.1007/3-540-28547-4_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28578-6
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