Issue |
EPL
Volume 123, Number 1, July 2018
|
|
---|---|---|
Article Number | 18001 | |
Number of page(s) | 7 | |
Section | Interdisciplinary Physics and Related Areas of Science and Technology | |
DOI | https://doi.org/10.1209/0295-5075/123/18001 | |
Published online | 03 August 2018 |
A minority game with expected returns for modeling stock correlations
1 School of Business, East China University of Science and Technology - Shanghai 200237, China
2 Institute of Physics, Academia Sinica - Taipei 115 Taiwan
3 School of Finance, Zhejiang University of Finance and Economics - Hangzhou 310018, China
4 School of Science, East China University of Science and Technology - Shanghai 200237, China
5 Research Center for Econophysics, East China University of Science and Technology - Shanghai 200237, China
Received: 25 March 2018
Accepted: 13 July 2018
Financial systems are complex systems which have been widely studied in recent years. We here propose a model to study stock correlations in financial markets, in which an agent's expected return for one stock is influenced by the historical return of the other stock. Each agent makes a decision based on his expected return with reference to information dissemination and the historical return of the stock. We find that the returns of the stocks are positively (negatively) correlated when agents' expected returns for one stock are positively (negatively) correlated with the historical return of the other. We provide both numerical and analytical studies and give explanations to stock correlations for cases with agents having either homogeneous or heterogeneous expected returns. The result still holds when other factors such as holding decisions and external events are included which broadens the practicability of the model.
PACS: 89.65.Gh – Economics; econophysics, financial markets, business and management / 07.05.Tp – Computer modeling and simulation / 05.45.Tp – Time series analysis
© EPLA, 2018
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.