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What Is the Impact of Heterogeneous Knowledge About Fundamentals on Market Liquidity and Efficiency: An ABM Approach

In: Advances in Artificial Economics

Author

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  • Vivien Lespagnol

    (Aix-Marseille University, CNRS & EHESS)

  • Juliette Rouchier

    (Aix-Marseille University, 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 traded. 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 belief perseverance 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, 2015. "What Is the Impact of Heterogeneous Knowledge About Fundamentals on Market Liquidity and Efficiency: An ABM Approach," Lecture Notes in Economics and Mathematical Systems, in: Frédéric Amblard & Francisco J. Miguel & Adrien Blanchet & Benoit Gaudou (ed.), Advances in Artificial Economics, edition 127, pages 105-117, Springer.
  • Handle: RePEc:spr:lnechp:978-3-319-09578-3_9
    DOI: 10.1007/978-3-319-09578-3_9
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. Jack Ochs & John Duffy, 1999. "Emergence of Money as a Medium of Exchange: An Experimental Study," American Economic Review, American Economic Association, vol. 89(4), pages 847-877, September.
    5. Westerhoff, Frank H., 2004. "Multiasset Market Dynamics," Macroeconomic Dynamics, Cambridge University Press, vol. 8(5), pages 596-616, November.
    6. repec:bla:jfinan:v:43:y:1988:i:3:p:617-37 is not listed on IDEAS
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Grossman, S.J. & Miller, M.H., 1988. "Liquidity And Market Structure," Papers 88, Princeton, Department of Economics - Financial Research Center.
    18. 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.
    19. 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.
    20. 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..
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    30. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    31. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    32. 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.
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