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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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    2. Yukio Ohsawa & Teruaki Hayashi & Takaaki Yoshino, 2019. "Tangled String for Multi-Scale Explanation of Contextual Shifts in Stock Market," Papers 1901.09469, arXiv.org.

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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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