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Position-Limit Design for the CSI 300 Futures Markets




The aim of this paper is to find the optimal level of position limit for the Chinese Stock Index (CSI) 300 futures market. A small position limit helps to prevent price manipulations in the spot market, thus able to keep the magnitude of instantaneous price changes within policy makers' tolerance range. However, setting the position limit too small may also have negative effects on market quality. We propose an artificial limit order market with heterogeneous and interacting agents to examine the impact of different levels of position limit on market quality, which is measured by liquidity, return volatility, efficiency of information dissemination and trading welfare. The simulation model is based on realistic trading mechanism, investor structure and order submission behavior observed in the CSI 300 futures market. Our results show that based on the liquidity condition in September 2010, raising the position limit from 100 to 300 can significantly improve market quality and at the same time keep maximum absolute price change per 5 seconds under the 2% tolerance level. However, the improvement becomes only marginal when further increasing the position limit beyond 300. Therefore, we believe that raising the position limit a moderate level can enhance the functionality of the CSI 300 futures market, which benefits the development of the Chinese financial system.

Suggested Citation

  • Lijian Wei & Wei Zhang & Xiong Xiong & Lei Shi, 2014. "Position-Limit Design for the CSI 300 Futures Markets," Research Paper Series 349, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:349

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    References listed on IDEAS

    1. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    2. Chiarella, Carl & Iori, Giulia, 2009. "The impact of heterogeneous trading rules on the limit order book and order flows," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 525-537.
    3. Menkhoff, Lukas & Osler, Carol L. & Schmeling, Maik, 2010. "Limit-order submission strategies under asymmetric information," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2665-2677, November.
    4. Kumar, Praveen & Seppi, Duane J, 1992. " Futures Manipulation with "Cash Settlement."," Journal of Finance, American Finance Association, vol. 47(4), pages 1485-1502, September.
    5. Theissen, Erik, 2000. "Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets," Journal of Financial Markets, Elsevier, vol. 3(4), pages 333-363, November.
    6. Goettler, Ronald L. & Parlour, Christine A. & Rajan, Uday, 2009. "Informed traders and limit order markets," Journal of Financial Economics, Elsevier, vol. 93(1), pages 67-87, July.
    7. repec:wsi:ijitdm:v:10:y:2011:i:03:n:s0219622011004464 is not listed on IDEAS
    8. Gil Bazo, Javier & Tapia Torres, Miguel Ángel & Moreno Muñoz, Jesús David, 2005. "Price dynamics, informational efficiency and wealth distribution in continuous double auction markets," DEE - Working Papers. Business Economics. WB wb057819, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
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    More about this item


    position limit; stock index futures; agent-based modeling; market quality;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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