ON THE EMERGENT PROPERTIES OF ARTIFICIAL STOCK MARKETS: SOME INITIAL EVIDENCES
Shu-Heng Chen (),
Chung-Chi Liao and
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Chung-Chi Liao: National Taiwan University, Graduate Institute of International Business
Chi-Hsuan Yeh: I-Shou University
No 328, Computing in Economics and Finance 2000 from Society for Computational Economics
Using the framework of agent-based artificial stock markets, this paper addresses the two well-known properties frequently observed in financial markets, namely, price-volume relation and sunspots, from a bottom-up perspective. In spirit of ``bottom-up'', these two phenomena are pursued in a more fundamental level, i.e., we are asking: is it possible to observed the emergence of these phenomena without explicit references to the assumptions frequently used by the studies in a ``top-down'' style? Posing it slightly different, would it be enough to generate these phenomena once we model the market as an evolving decentralized system of autonomous interacting agents? Or, can these two phenomenon be coined as ``emergent phenomena'', a terminology from complex adaptive systems.To do so, simulation based on AIE-ASM Version 3 (Chen and Yeh, 2000) are conducted for multiple runs. Within the genetic programming framework, we include trading volume and some irrelevant exogenous variables into the terminal sets. This make it possible that trader can choose to believe that trading volume or sunspots can help forecast the future movement of stock returns if they are convinced so from the market behaviour endogenously generated by themselves. To have a further examination on the emergence of sunspot effects, sunspots are generated by deterministic cyclic processes, such as sin curve, and the purely iid random processes. We then test the emergent of these two phenomena by using a new version of the Granger causality test, which does not require an ad-hoc procedure of filtering.
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