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Trading volume and market efficiency: an Agent Based Model with heterogenous knowledge about fundamentals

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  • Vivien Lespagnol

    (Aix-Marseille University (Aix-Marseille School of Economics), CNRS & EHESS)

  • Juliette Rouchier

    (Aix-Marseille University (Aix-Marseille School of Economics), CNRS & EHESS)

Abstract

This paper studies the effect of investor’s bounded rationality on market dynamics. In an order driven market, we consider a few-types model where two risky assets are exchanged. Agents differ by their behavior, knowledge, risk aversion and investment horizon. The investor’s demand is defined by a utility maximization under constant absolute risk aversion. Relaxing the assumption of perfect knowledge of the fundamentals enables to identify two components in a bubble. The first one comes from the unperceived fundamental changes due to trader’s belief perseverance. The second one is generated by chartist behavior. In all simulations, speculators make the market less efficient and more volatile. They also increase the maximum amount of assets exchanged in the most liquid time step. However, our model is not showing raising average volatility on long term. Concerning the fundamentalists, the unknown fundamental has a stabilization impact on the trading price. The closer the anchor is to the true fundamental value, the more efficient the market is, because the prices change smoothly.

Suggested Citation

  • Vivien Lespagnol & Juliette Rouchier, 2014. "Trading volume and market efficiency: an Agent Based Model with heterogenous knowledge about fundamentals," AMSE Working Papers 1419, Aix-Marseille School of Economics, France, revised May 2014.
  • Handle: RePEc:aim:wpaimx:1419
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    1. Amihud, Yakov & Mendelson, Haim & Pedersen, Lasse Heje, 2006. "Liquidity and Asset Prices," Foundations and Trends(R) in Finance, now publishers, vol. 1(4), pages 269-364, February.
    2. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2005. "Limit Order Book as a Market for Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1171-1217.
    3. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    4. Cohen, Kalman J, et al, 1980. "Implications of Microstructure Theory for Empirical Research on Stock Price Behavior," Journal of Finance, American Finance Association, vol. 35(2), pages 249-257, May.
    5. 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.
    6. Sanford J. Grossman & Merton H. Miller, 1988. "Liquidity and Market Structure," NBER Working Papers 2641, National Bureau of Economic Research, Inc.
    7. Iori, Giulia, 2002. "A microsimulation of traders activity in the stock market: the role of heterogeneity, agents' interactions and trade frictions," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 269-285, October.
    8. Westerhoff, Frank H., 2004. "Multiasset Market Dynamics," Macroeconomic Dynamics, Cambridge University Press, vol. 8(5), pages 596-616, November.
    9. Harras, Georges & Sornette, Didier, 2011. "How to grow a bubble: A model of myopic adapting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 137-152.
    10. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    11. Hawawini, Gabriel & Cohen, Kalman & Maier, Steven & Schwartz, Robert & Whitcomb, David, 1980. "Implications of microstructure theory for empirical research in stock price behavior," MPRA Paper 33976, University Library of Munich, Germany.
    12. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    13. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    14. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    15. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    16. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    17. Orlean, Andre, 1995. "Bayesian interactions and collective dynamics of opinion: Herd behavior and mimetic contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 28(2), pages 257-274, October.
    18. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    19. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    20. Karolyi, G. Andrew & Lee, Kuan-Hui & van Dijk, Mathijs A., 2012. "Understanding commonality in liquidity around the world," Journal of Financial Economics, Elsevier, vol. 105(1), pages 82-112.
    21. Grossman, Sanford J & Miller, Merton H, 1988. " Liquidity and Market Structure," Journal of Finance, American Finance Association, vol. 43(3), pages 617-637, July.
    22. Bao, Te & Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan, 2012. "Individual expectations, limited rationality and aggregate outcomes," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1101-1120.
    23. Chenghuan Sean Chu & Andreas Lehnert & Wayne Passmore, 2009. "Strategic Trading in Multiple Assets and the Effects on Market Volatiliy," International Journal of Central Banking, International Journal of Central Banking, vol. 5(4), pages 143-172, December.
    24. Parlour, Christine A, 1998. "Price Dynamics in Limit Order Markets," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 789-816.
    25. Chiarella, Carl & Dieci, Roberto & He, Xue-Zhong, 2007. "Heterogeneous expectations and speculative behavior in a dynamic multi-asset framework," Journal of Economic Behavior & Organization, Elsevier, vol. 62(3), pages 408-427, March.
    26. Tedeschi, Gabriele & Iori, Giulia & Gallegati, Mauro, 2012. "Herding effects in order driven markets: The rise and fall of gurus," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 82-96.
    27. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    28. Handa, Puneet & Schwartz, Robert & Tiwari, Ashish, 2003. "Quote setting and price formation in an order driven market," Journal of Financial Markets, Elsevier, vol. 6(4), pages 461-489, August.
    29. Beja, Avraham & Goldman, M Barry, 1980. "On the Dynamic Behavior of Prices in Disequilibrium," Journal of Finance, American Finance Association, vol. 35(2), pages 235-248, May.
    30. Carl Chiarella & Xue-Zhong He & Lijian Wei, 2013. "Learning and Evolution of Trading Strategies in Limit Order Markets," Research Paper Series 335, Quantitative Finance Research Centre, University of Technology, Sydney.
    31. Hommes, Cars & Huang, Hai & Wang, Duo, 2005. "A robust rational route to randomness in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 29(6), pages 1043-1072, June.
    32. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.
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    More about this item

    Keywords

    Agent-based modeling; market microstructure; fundamental value; trading volume; _efficient market;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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