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Numerical Modeling, Noise Traders, and the Swarm Simulation System

  • Timothy E. Jares
Part of the Advances in Computational Economics book series (AICE, volume 14)

Abstract

This paper investigates the long-run effects of noise traders in an ar-tificial financial market in which risky asset returns are endogenously determined. “Noise traders” are agents irrationally trading on noise as if it were information. Some researchers have argued that traders following seemingly irrational strategies can have little influence on financial markets because they will tend to buy high and sell low on average. Eventually, their wealth and market influence will be lost.

However, complete noise trader elimination as traditionally hypothesized is not found. Model analysis strongly suggests that noise traders can affect prices in the long run. The effects of market configuration changes on various market characteristics (e.g., trading volume and risky asset returns) are also assessed. A curious result from our simulations is that increased volume is observed in our base (homogeneous) market when traders can buy/sell on margin.

Keywords

Cash Flow Risky Asset Market Maker Trading Period Noise Trader 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Timothy E. Jares
    • 1
  1. 1.University of North FloridaUSA

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