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The investor behavior and futures market volatility: A theory and empirical study based on the OLG model and high-frequency data

  • Yun Wang
  • Renhai Hua
  • Zongcheng Zhang
Registered author(s):

    Purpose–The purpose of this paper is to examine whether the futures volatility could affect the investor behavior and what trading strategy different investors could adopt when they meet different information conditions. Design/methodology/approach–This study introduces a two-period overlapping generation model (OLG) model into the future market and set the investor behavior model based on the future contract price, which can also be extended to complete and incomplete information. It provides the equilibrium solution and uses cuprum tick data in SHFE to conduct the empirical analysis. Findings–The two-period OLG model based on the future market is consistent with the practical situation; second, the sufficient information investors such as institutional adopt reversal trading patterns generally; last, the insufficient information investors such as individual investors adopt momentum trading patterns in general. Research limitations/implications–Investor trading behavior is always an important issue in the behavioral finance and market supervision, but the related research is scarce. Practical implications–The conclusion shows that the investors' behavior in Chinese future market is different from the Chinese stock market. Originality/value–This study empirically analyzes and verifies the different types of trading strategies investors could; investors such as institutional ones adopt reversal trading patterns generally; while investors such as individual investors adopt momentum trading patterns in general.

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    File URL: http://www.emeraldinsight.com/journals.htm?issn=2044-1398&volume=1&issue=4&articleid=1950964&show=abstract
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    Article provided by Emerald Group Publishing in its journal China Finance Review International.

    Volume (Year): 1 (2011)
    Issue (Month): 4 (August)
    Pages: 388-407

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    Handle: RePEc:eme:cfripp:v:1:y:2011:i:4:p:388-407
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    1. Nicholas Barberis & Ming Huang & Tano Santos, . "Prospect Theory and Asset Prices," CRSP working papers 494, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    2. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
    4. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-68, February.
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    6. Wang, Jiang, 1993. "A Model of Intertemporal Asset Prices under Asymmetric Information," Review of Economic Studies, Wiley Blackwell, vol. 60(2), pages 249-82, April.
    7. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    8. Spiegel, Matthew, 1998. "Stock Price Volatility in a Multiple Security Overlapping Generations Model," Review of Financial Studies, Society for Financial Studies, vol. 11(2), pages 419-47.
    9. J. Bradford De Long & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1989. "The Size and Incidence of the Losses from Noise Trading," NBER Working Papers 2875, National Bureau of Economic Research, Inc.
    10. De Long, J Bradford, et al, 1990. " Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-95, June.
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