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Impact of information cost and switching of trading strategies in an artificial stock market

  • Yi-Fang Liu

    (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University, CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS)

  • Wei Zhang

    (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University)

  • Chao Xu


    (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University)

  • Jørgen Vitting Andersen


    (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS)

  • Hai-Chuan Xu

    (College of Management and Economics - Tianjin University, China Center for Social Computing and Analytics - Tianjin University)

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    This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First, we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.

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    Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00983051.

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    Date of creation: Apr 2014
    Date of revision:
    Publication status: Published in Documents de travail du Centre d'Economie de la Sorbonne 2014.31 - ISSN : 1955-611X. 2014
    Handle: RePEc:hal:cesptp:halshs-00983051
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    1. repec:att:wimass:9530 is not listed on IDEAS
    2. Cochrane, John H. & Campbell, John, 1999. "By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Scholarly Articles 3119444, Harvard University Department of Economics.
    3. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-96, July.
    4. Robert J. Shiller, 1980. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," NBER Working Papers 0456, National Bureau of Economic Research, Inc.
    5. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    6. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Society for Computational Economics, vol. 19(1), pages 95-132, February.
    7. Grundy, Bruce D. & Kim, Youngsoo, 2002. "Stock Market Volatility in a Heterogeneous Information Economy," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(01), pages 1-27, March.
    8. Allan Timmermann, 1996. "Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning," Review of Economic Studies, Oxford University Press, vol. 63(4), pages 523-557.
    9. Sanford J Grossman & Joseph E Stiglitz, 1997. "On the Impossibility of Informationally Efficient Markets," Levine's Working Paper Archive 1908, David K. Levine.
    10. Franke, Reiner & Westerhoff, Frank, 2011. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," BERG Working Paper Series 78, Bamberg University, Bamberg Economic Research Group.
    11. Weinbaum, David, 2009. "Investor heterogeneity, asset pricing and volatility dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 33(7), pages 1379-1397, July.
    12. Javier Gil-Bazo & David Moreno & Mikel Tapia, 2005. "Price Dynamics, Informational Efficiency And Wealth Distribution In Continuous Double Auction Markets," Business Economics Working Papers wb057819, Universidad Carlos III, Departamento de Economía de la Empresa.
    13. Youssefmir, Michael & Huberman, Bernardo A., 1997. "Clustered volatility in multiagent dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 32(1), pages 101-118, January.
    14. Bulkley, George & Tonks, Ian, 1989. "Are U.K. Stock Prices Excessively Volatile? Trading Rules and Variance Bounds Tests," Economic Journal, Royal Economic Society, vol. 99(398), pages 1083-98, December.
    15. Kirchler, Michael & Huber, Jurgen, 2007. "Fat tails and volatility clustering in experimental asset markets," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1844-1874, June.
    16. Lux, Thomas & Schornstein, Sascha, 2002. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Discussion Paper Series 1: Economic Studies 2002,29, Deutsche Bundesbank, Research Centre.
    17. Brock, W.A. & Hommes, C.H., 1996. "A Rational Route to Randomness," Working papers 9530r, Wisconsin Madison - Social Systems.
    18. James Bullard & John Duffy, 1999. "Learning and Excess Volatility," Computing in Economics and Finance 1999 224, Society for Computational Economics.
    19. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Society for Computational Economics, vol. 26(1), pages 19-49, August.
    20. LeRoy, Stephen F & Porter, Richard D, 1981. "The Present-Value Relation: Tests Based on Implied Variance Bounds," Econometrica, Econometric Society, vol. 49(3), pages 555-74, May.
    21. Luisa Corrado & Marcus Miller & Lei Zhang, 2007. "Bulls, bears and excess volatility: can currency intervention help?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 261-272.
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