Evolution and anti-evolution in a minimal stock market model

✍ Scribed by R Rothenstein; K Pawelzik

• Publisher: Elsevier Science
• Year: 2003
• Tongue: English
• Weight: 577 KB
• Volume: 326
• Category: Article
• ISSN: 0378-4371
• DOI: 10.1016/s0378-4371(03)00396-0

✦ Synopsis

We present a novel microscopic stock market model consisting of a large number of random agents modeling traders in a market. Each agent is characterized by a set of parameters that serve to make iterated predictions of two successive returns. The future price is determined according to the o er and the demand of all agents. The system evolves by redistributing the capital among the agents in each trading cycle. Without noise the dynamics of this system is nearly regular and thereby fails to reproduce the stochastic return uctuations observed in real markets. However, when in each cycle a small amount of noise is introduced we ÿnd the typical features of real ÿnancial time series like fat-tails of the return distribution and large temporal correlations in the volatility without signiÿcant correlations in the price returns. Introducing the noise by an evolutionary process leads to di erent scalings of the return distributions that depend on the deÿnition of ÿtness. Because our realistic model has only very few parameters, and the results appear to be robust with respect to the noise level and the number of agents we expect that our framework may serve as new paradigm for modeling self-generated return uctuations in markets.