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Computational Economics

, Volume 51, Issue 4, pp 991–1020 | Cite as

Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals

  • Vivien Lespagnol
  • Juliette Rouchier
Article
  • 167 Downloads

Abstract

This paper investigates whether trading volume and price distortion can be explained by the investor’s bounded rationality. Assuming that agents are bounded by their information access and processing, what are the consequences on market dynamics? We expose the result of simulations in an ABM that considers the liquidity as an endogenous characteristic of the market and allows to design investors as bounded rational. In a call auction market, where two risky assets are exchanged, traders are defined as a mix between fundamentalist and trend-follower outlook. Each one differs as to behaviour, order-placement strategy, mood, knowledge, risk-aversion and investment horizon. We place agents in a context of evolving fundamental values and order placement strategy; they perceive the fundamental but they also have some heterogeneous belief perseverance; and they adapt their orders to the market depth so as to maximise their execution probability and their profit. By adding bounded rationality in their information processing, we show that (1) usual features as trend-follower outlook and heterogeneous investment horizon are important features to generate excess volatility of asset prices and market inefficiency; (2) the learning fundamental value stabilises the market price and the trading volume; (3) the order-placement strategy increases trading volume, but reduces market efficiency and stability; (4) the agent’s mood prevents illiquid market and weakly increases the market volatility as classical noise trader agents; (5) the impatience to sell of traders is always present in the market: the market sell orders are always more numerous than the market buy orders.

Keywords

Agent-based modelling Market microstructure Fundamental value Trading volume Efficient market 

JEL Classification

C63 D44 G12 G14 

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Aix-Marseille University (Aix-Marseille School of Economics)CNRS, EHESS and Centrale MarseilleMarseilleFrance
  2. 2.Université Paris-DauphinePSL Research University, CNRS and LAMSADEParisFrance

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