Using agent-based artificial financial market to analyse market manipulation
Resumo
Este trabalho visa estudar a manipulação de preços por grandes investidores e seu efeito geral no mercado de ações.. Para isto, criou-se um mercado financeiro artificial utilizando NetLogo. Foram efetuados experimentos em um ambiente fechado, com especuladores que utilizam análise técnica e outros três diferentes perfis de agentes com estratégias de investimento únicas. Este trabalho provê insumos para a criação de um mercado financeiro artificial, no qual poderiam ser adicionadas outras diversas estratégias para seus agentes, e evidências de uma manipulação de mercado causada por excesso de demanda.Referências
Angel, J. and Mccabe, D. (2013). “Fairness in financial markets: The case of high frequency trading”, Journal of Business Ethics, v. 112, n. 4, p. 585-595, 2013.
Asparouhova, E., Bossaerts, P. and Plott, C. (2003) “Excess demand and equilibration in multi-security financial markets: the empirical evidence”, Journal of Financial Markets, vol. 6, Elsevier Science B.V., p. 1-21.
Buss, A., Dumas, B., Uppal, R. and Vilkov, G. (2016) “The intended and unintended consequences of financial-market regulations: A general-equilibrium analysis”, Journal of Monetary Economics, vol. 81, Elsevier B.V., p. 25-43.
Castro, P. A. and Sichman, J. S. (2009) “Agex: a financial market simulation tool for software agents”, In: Aalst W., Mylopoulos J., Sadeh N. M., Shaw M. J., Szyperski C., Filipe J., Cordeiro J. (eds) LNBIP, vol 24, Springer, Berlin, p. 704–715.
Castro, P. A. and Sichman, J. S. (2013) “Automated asset management based on partially cooperative agents for a world of risks”, Appl Intell, vol 38, Springer, Berlin, p. 210-225.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L. F., Nobrega, J. P. and Oliveira, A. L. I. (2016) “Computational Intelligence and Financial Markets: A Survey and Future Directions”, Expert Systems With Applications, vol. 55, Elsevier Ltd., p. 194-211.
CVM, C. d. V. M. (2013) “Mercado de valores mobiliários brasileiro.” [S.l.]: Comissão de valores mobiliários, 1 st ed., ISBN 978-85-67896-00-7.
Immonen, E. (2017) “Simple agent-based dynamical system models for efficient financial markets: Theory and examples”, Journal of Mathematical Economics, vol. 69, Elsevier B. V., p. 38-53.
Kirkpatrick II, C. D. and Dahlquist, J. A. (2010) “Technical analysis: the complete resource for financial market technicians”. FT press.
LeBaron, B. (2000) “Agent-based computational finance: Suggested readings and early research”, Journal of Economic Dynamics & Control, vol. 24, Elsevier Science B.V., p. 679-702.
Marchesi, M., Mannaro, K. and Setzu, A. (2008) “Using an artificial financial market for assessing the impact of Tobin-like transaction taxes”, Journal of Economic Behavior & Organization, vol. 67, Elsevier B.V., p. 445-462.
Moore, T., Gandal, N., Hamrick, J. T. and Oberman, T. (2018) “Price Manipulation in the Bitcoin Ecosystem”, Journal of Monetary Economics, DOI: 10.1016/j.jmoneco.2017.12.004.
Raberto, M., Cincotti, S., Focardi, S. M. and Marchesi, M. (2001) “Agent-based simulation of a financial market”, Physica A, vol. 299, Elsevier Science B.V., p. 319-327.
Reilly, F. K. and Brown, K. C. (2011) “Investment analysis and portfolio management”. Cengage Learning.
Reis, E. R., Castro, P. A. and Sichman, J. S. (2016) “Enhancing Classification Accuracy Through Feature Selection Methods”, XIII Encontro Nacional de Inteligência Artificial e Computacional, SBC ENIAC, Recife – PE, Brazil.
Vishwanath, R and Krishnamurti, C. (2009) “Investment Management: A Modern Guide to Security Analysis and Stock Selection”. Springer-Verlag Berlin Heidelberg, 1st ed., p. 13-29.
Westerhoff, F. H., and Dieci, R. (2006) “The effectiveness of Keynes–Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach”, Journal of Economic Dynamics & Control, vol. 30, Elsevier B. V., p. 293-322.
Wurman, P. R., Walsh, W. E and Wellman, M. P. (1998) “Flexible double auctions for electronic commerce: theory and implementation”, Decision Support Systems, vol. 24, Elsevier Science B.V., p. 17-27.
Asparouhova, E., Bossaerts, P. and Plott, C. (2003) “Excess demand and equilibration in multi-security financial markets: the empirical evidence”, Journal of Financial Markets, vol. 6, Elsevier Science B.V., p. 1-21.
Buss, A., Dumas, B., Uppal, R. and Vilkov, G. (2016) “The intended and unintended consequences of financial-market regulations: A general-equilibrium analysis”, Journal of Monetary Economics, vol. 81, Elsevier B.V., p. 25-43.
Castro, P. A. and Sichman, J. S. (2009) “Agex: a financial market simulation tool for software agents”, In: Aalst W., Mylopoulos J., Sadeh N. M., Shaw M. J., Szyperski C., Filipe J., Cordeiro J. (eds) LNBIP, vol 24, Springer, Berlin, p. 704–715.
Castro, P. A. and Sichman, J. S. (2013) “Automated asset management based on partially cooperative agents for a world of risks”, Appl Intell, vol 38, Springer, Berlin, p. 210-225.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L. F., Nobrega, J. P. and Oliveira, A. L. I. (2016) “Computational Intelligence and Financial Markets: A Survey and Future Directions”, Expert Systems With Applications, vol. 55, Elsevier Ltd., p. 194-211.
CVM, C. d. V. M. (2013) “Mercado de valores mobiliários brasileiro.” [S.l.]: Comissão de valores mobiliários, 1 st ed., ISBN 978-85-67896-00-7.
Immonen, E. (2017) “Simple agent-based dynamical system models for efficient financial markets: Theory and examples”, Journal of Mathematical Economics, vol. 69, Elsevier B. V., p. 38-53.
Kirkpatrick II, C. D. and Dahlquist, J. A. (2010) “Technical analysis: the complete resource for financial market technicians”. FT press.
LeBaron, B. (2000) “Agent-based computational finance: Suggested readings and early research”, Journal of Economic Dynamics & Control, vol. 24, Elsevier Science B.V., p. 679-702.
Marchesi, M., Mannaro, K. and Setzu, A. (2008) “Using an artificial financial market for assessing the impact of Tobin-like transaction taxes”, Journal of Economic Behavior & Organization, vol. 67, Elsevier B.V., p. 445-462.
Moore, T., Gandal, N., Hamrick, J. T. and Oberman, T. (2018) “Price Manipulation in the Bitcoin Ecosystem”, Journal of Monetary Economics, DOI: 10.1016/j.jmoneco.2017.12.004.
Raberto, M., Cincotti, S., Focardi, S. M. and Marchesi, M. (2001) “Agent-based simulation of a financial market”, Physica A, vol. 299, Elsevier Science B.V., p. 319-327.
Reilly, F. K. and Brown, K. C. (2011) “Investment analysis and portfolio management”. Cengage Learning.
Reis, E. R., Castro, P. A. and Sichman, J. S. (2016) “Enhancing Classification Accuracy Through Feature Selection Methods”, XIII Encontro Nacional de Inteligência Artificial e Computacional, SBC ENIAC, Recife – PE, Brazil.
Vishwanath, R and Krishnamurti, C. (2009) “Investment Management: A Modern Guide to Security Analysis and Stock Selection”. Springer-Verlag Berlin Heidelberg, 1st ed., p. 13-29.
Westerhoff, F. H., and Dieci, R. (2006) “The effectiveness of Keynes–Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach”, Journal of Economic Dynamics & Control, vol. 30, Elsevier B. V., p. 293-322.
Wurman, P. R., Walsh, W. E and Wellman, M. P. (1998) “Flexible double auctions for electronic commerce: theory and implementation”, Decision Support Systems, vol. 24, Elsevier Science B.V., p. 17-27.
Publicado
02/05/2018
Como Citar
BIASOTO, Luiza P.; REIS, Everton R.; SICHMAN, Jaime S..
Using agent-based artificial financial market to analyse market manipulation. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 12. , 2018, Fortaleza/CE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 154-166.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2018.33263.
