JACIII Vol.15 No.2 pp. 204-211
doi: 10.20965/jaciii.2011.p0204


Simulation of Futures and Spot Markets by Using an Agent-Based Multi-Market Model

Tomoko Ohi, Yasuhiro Hashimoto, Yu Chen, and Hirotada Ohashi

Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

August 1, 2010
December 31, 2010
March 20, 2011
multi-agent model, multi-market model, futures market, fat-tail
The agent-based multi-market model we propose simulates futures and spot markets. On the basis of trading strategies in real markets, four kinds of agents - arbitragers, hedgers, speculators, and noise traders - are included in our model. Interactions of the two markets are generated through various agent trading behavior. We also statistically analyzed futures and spot prices of the Nikkei 225 index, where we found a large positive correlation between the two prices and a fat-tail distribution of the basis. Simulations results show that, instead of the conventional single-market model, only the two-market model reproduces both statistical properties of futures prices.
Cite this article as:
T. Ohi, Y. Hashimoto, Y. Chen, and H. Ohashi, “Simulation of Futures and Spot Markets by Using an Agent-Based Multi-Market Model,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.2, pp. 204-211, 2011.
Data files:
  1. [1] M. Niizeki and D. Maki, “A Further Analysis of the Cointegration Relationship Between the Cash Stock Market and the Derivatives Markets: Cointegration Tests with Threshold Autoregressive Models in the Japanese Markets,” Doshisha University World Wide Business Review Vol.6, No.2, 2005.
  2. [2] H. R. Stoll and R. E. Whaley, “The Dynamics of Stock Index and Stock Index Futures Returns,” J. of Financial and Quantitative Analysis, Vol.25, No.4, 1990.
  3. [3] K. N. Mukherjee, “Information Flow and Price Comovements Empirical Evidence from Indian Spot and Futures Market,” First Annual Conf. on Finance and Economics (ICFAI Business School, Bangalore), 2004.
  4. [4] U-Mart Project, “U-Mart.”
  5. [5] J. Duke and C. D. Clack, “Evolutionary Simulation of Hedging Pressure in Futures Markets,” GECCO ’07, ACM, 2007.
  6. [6] L. Tan, Q. Zhong-ying, S. Xue-shen, and L. Ying, “Heterogeneous Agent Beliefs and Clustered Volatility in Commodity Futures Market,” Proc. of the 2007 Int. Conf. on Intelligent Pervasive Computing, 2007.
  7. [7] J. Hull, “Introduction to Futures and Options Markets,” Prentice Hall, 1997.
  8. [8] C. Brooks, I. Garrett, and M. Hinich, “An Alternative Approach to Investigating Lead-Lag Relationships between Stock and Stock Index Futures Markets,” Applied Financial Economics, Vol.9, No.6, 1999.
  9. [9] Y. K. Tse, “Lead-Lag Relationship Between Spot Index and Futures Price of the Nikkei Stock Average,” J. of Forecasting, Vol.14, No.7, 1995.
  10. [10] S. Figlewski, “Hedging Performance and Basis Risk in Stock Index Futures,” J. of Finance, Vol.39, No.3, 1984.
  11. [11] T. Bollerslev, “Generalized Autoregressive Conditional Heteroskedasticity,” J. of Econometrics, Vol.31, No.3, 1986.
  12. [12] Tokyo Stock Exchange, Inc., “What is the ‘itayose’ method?”
  13. [13] E. Fama, “Efficient Capital Markets: A Review of Theory and Empirical Work,” The J. of Finance, Vol.25, No.2, Papers and Proc. of the 28th annual meeting of the American Finance, Association of New York, 1969.

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