Abstract
This paper examines the behavior of price discovery within a context of an agent-based artificial stock market. In this model, traders stochastically update their forecasts by searching the business school whose evolution is driven by genetic programming. We observe how well the market can track the “true price” i.e., the homogeneous rational expectations equilibrium price (HREEP). It is found that market prices are statistically significantly biased. Furthermore, the pricing error is negatively correlated to market size. Excess volatility is also noticeable in these markets.
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Chen, SH., Liao, CC. (2002). Price Discovery in Agent-Based Computational Modeling of the Artificial Stock Market. In: Chen, SH. (eds) Genetic Algorithms and Genetic Programming in Computational Finance. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0835-9_16
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DOI: https://doi.org/10.1007/978-1-4615-0835-9_16
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5262-4
Online ISBN: 978-1-4615-0835-9
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