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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shu-Heng Chen Chia-Hsuan Yeh |
| Copyright Year | 1999 |
| Description | Author affiliation: Nat. Chengchi Univ., Taipei, Taiwan (Shu-Heng Chen) |
| Abstract | In this paper, we propose a new architecture to study artificial stock markets. This architecture rests on a mechanism called "school" which is a procedure to map the phenotype to the genotype or, in plain English, to uncover the secret of success. We propose an agent-based model of "school", and consider school as an evolving population driven by single-population GP (SGP). The architecture also takes into consideration traders' search behavior. By simulated annealing, traders' search density can be connected to psychological factors, such as peer pressure or economic factors such as the standard of living. This market architecture was then implemented in a standard artificial stock market. Our econometric study of the resultant artificial time series evidences that the return series is independently and identically distributed (iid), and hence supports the efficient market hypothesis (EMH). What is interesting though is that this lid series was generated by "traders" who do not believe in the EMH at all. In fact, our study indicates that many of our traders were able to find useful signals quite often from business school, even though these signals were short-lived. |
| Starting Page | 834 |
| Ending Page | 841 |
| File Size | 761164 |
| Page Count | 8 |
| File Format | |
| ISBN | 0780355369 |
| DOI | 10.1109/CEC.1999.782509 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1999-07-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Genetic programming Stock markets Econometrics Economics Educational institutions Peer to peer computing Biological cells Simulated annealing Psychology Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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