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Who wins? Study of long-run trader survival in an artificial stock market

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Author Info

  • Cincotti, Silvano
  • M. Focardi, Sergio
  • Marchesi, Michele
  • Raberto, Marco

Abstract

We introduce a multi-asset artificial financial market with finite amount of cash and number of stocks. The background trading is characterized by a random trading strategy constrained by the finiteness of resources and by market volatility. Stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Three active trading strategies have been introduced and studied in two different market conditions: steady market and growing market with asset inflation. We show that the profitability of each strategy depends both on the periodicity of portfolio reallocation and on the market condition. The best performing strategy is the one that exploits the mean reversion characteristic of asset price processes.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 324 (2003)
Issue (Month): 1 ()
Pages: 227-233

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Handle: RePEc:eee:phsmap:v:324:y:2003:i:1:p:227-233

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Artificial financial markets; Heterogeneous agents; Econophysics;

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Cited by:
  1. Marco Raberto & Andrea Teglio & Silvano Cincotti, 2005. "Multi-agent modeling and simulation of a sequential monetary production economy," Computational Economics 0503002, EconWPA.
  2. Erika Corona & Sabrina Ecca & Michele Marchesi & Alessio Setzu, 2008. "The Interplay Between Two Stock Markets and a Related Foreign Exchange Market: A Simulation Approach," Computational Economics, Society for Computational Economics, vol. 32(1), pages 99-119, September.
  3. Derveeuw, Julien & Beaufils, Bruno & Mathieu, Philippe & Brandouy, Olivier, 2007. "Testing double auction as a component within a generic market model architecture," MPRA Paper 4918, University Library of Munich, Germany.
  4. Liu, Xinghua & Gregor, Shirley & Yang, Jianmei, 2008. "The effects of behavioral and structural assumptions in artificial stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2535-2546.
  5. Raberto, Marco & Cincotti, Silvano, 2005. "Modeling and simulation of a double auction artificial financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 34-45.

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