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Mathematical Problems in Engineering
Volume 2014, Article ID 563912, 10 pages
http://dx.doi.org/10.1155/2014/563912
Research Article

An Agent-Based Computational Model for China’s Stock Market and Stock Index Futures Market

1College of Management and Economics, Tianjin University, Tianjin 300072, China
2China Center for Social Computing and Analytics, Tianjin University, Tianjin 300072, China
3School of Business, East China University of Science and Technology, Shanghai 200237, China
4Department of Mathematics, East China University of Science and Technology, Shanghai 200237, China
5Research Center for Econophysics, East China University of Science and Technology, Shanghai 200237, China

Received 17 February 2014; Revised 25 March 2014; Accepted 6 April 2014; Published 17 April 2014

Academic Editor: Pankaj Gupta

Copyright © 2014 Hai-Chuan Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. C. Bae, T. H. Kwon, and J. W. Park, “Futures trading, spot market volatility, and market efficiency: the case of the Korean index futures markets,” Journal of Futures Markets, vol. 24, no. 12, pp. 1195–1228, 2004. View at Publisher · View at Google Scholar · View at Scopus
  2. S. S. Wang, W. Li, and L. T. W. Cheng, “The impact of H-share derivatives on the underlying equity market,” Review of Quantitative Finance and Accounting, vol. 32, no. 3, pp. 235–267, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. X. Xiong, Y. Zhang, W. Zhang, and Y.-J. Zhang, “The effect on volatility of stock market and stock index futures market after launching stock index options: a case of KOSPI200 index options,” System Engineering Theory & Practice, vol. 31, no. 5, pp. 785–791, 2011 (Chinese). View at Google Scholar · View at Scopus
  4. E. Drimbetas, N. Sariannidis, and N. Porfiris, “The effect of derivatives trading on volatility of the underlying asset: evidence from the Greek stock market,” Applied Financial Economics, vol. 17, no. 2, pp. 139–148, 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. D. Cumming, S. Johan, and D. Li, “Exchange trading rules and stock market liquidity,” Journal of Financial Economics, vol. 99, no. 3, pp. 651–671, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. D. Rittler, “Price discovery and volatility spillovers in the European Union emissions trading scheme: a high-frequency analysis,” Journal of Banking & Finance, vol. 36, no. 3, pp. 774–785, 2012. View at Publisher · View at Google Scholar · View at Scopus
  7. A. N. Cappellini, “SumWEB: stock market experiment environment for natural and artificial agents,” Swarm Fest, 2004.
  8. S. Kobayashi and T. Hashimoto, “Analysis of circuit breakers using artificial stock market,” in Proceedings of the 12th International Symposium on Artificial Life and Robotics (AROB '07), pp. 260–263, January 2007. View at Scopus
  9. S. Ecca, M. Marchesi, and A. Setzu, “Modeling and simulation of an artificial stock option market,” Computational Economics, vol. 32, no. 1-2, pp. 37–53, 2008. View at Publisher · View at Google Scholar · View at Scopus
  10. F. H. Westerhoff, “The use of agent-based financial market models to test the effectiveness of regulatory policies,” Jahrbucher fur Nationalokonomie und Statistik, vol. 228, no. 2-3, pp. 195–227, 2008. View at Google Scholar · View at Scopus
  11. C. Chiarella, G. Iori, and J. Perelló, “The impact of heterogeneous trading rules on the limit order book and order flows,” Journal of Economic Dynamics and Control, vol. 33, no. 3, pp. 525–537, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  12. M. D. Gould, M. A. Porter, S. Williams, M. McDonald, D. J. Fenn, and S. D. Howison, “Limit order books,” Quantitative Finance, vol. 13, no. 11, pp. 1709–1742, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  13. M. Martens, “Measuring and forecasting S&P 500 index-futures volatility using high-frequency data,” Journal of Futures Markets, vol. 22, no. 6, pp. 497–518, 2002. View at Publisher · View at Google Scholar · View at Scopus