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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

Fundamental analysis in the multi-agent trading system

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DOI: http://dx.doi.org/10.15439/2016F238

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 1169–1174 ()

Full text

Abstract. The paper presents issues related to developing methods for fundamental analysis used to expand capabilities of A-Trader, to better predict the financial market. The fundamental analysis indicators can be used as confirmation of decisions generated by other strategies of the system. The first part of the article discusses briefly the fundamental analysis issues in relation to the FOREX market. Next, the statistical analysis of correlations of the different time series indicators and algorithms of fundamental analysis agents are examined. The final part discusses the results of the performance evaluation of selected investment strategies, including fundamental--based strategies.

References

  1. B. LeBaron, “Active and Passive Learning in Agent-based Financial Markets”, Eastern Economic Journal, vol. 37, pp. 35-43, 2011.
  2. L. Mendes, P. Godinho and J. Dias, “A Forex trading system based on a genetic algorithm”, Journal of Heuristics 18 (4), pp. 627-656, 2012.
  3. J.R. Thompson, J.R. Wilson and E. P. Fitts, “Analysis of market returns using multifractal time series and agent-based simulation”, in Proceedings of the Winter Simulation Conference (WSC '12). Winter Simulation Conference, Article 323, 2012.
  4. C. D. Kirkpatric and J. Dahlquist, Technical Analysis: The Complete Resource for Financial Market Technicians, Financial Times Press, 2006.
  5. C. Lento, “A Combined Signal Approach to Technical Analysis on the S&P 500”, Journal of Business & Economics Research, 6 (8), pp. 41–51, 2008.
  6. H. C. Aladag, U. Yolco and E. Egrioglu, “A new time invariant fuzzy time series forecasting model based on particle swarm optimization”, Applied Soft Computing, 12 (10), pp. 3291-3299, 2012.
  7. P. Singh and B. Borah, “Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization”, International Journal of Approximate Reasoning, 55 (3), pp. 812-833, 2014.
  8. O. Badawy and A. Almotwaly, "Combining neural network knowledge in a mobile collaborating multi-agent system", Electrical, Electronic and Computer Engineering, ICEEC '04, pp. 325, 328, 2004, http://dx.doi.org/10.1109/ICEEC.2004.1374457.
  9. M. Aloud, E.P.K. Tsang and R. Olsen, “Modelling the FX Market Traders' Behaviour: An Agent-based Approach”, in Simulation in Computational Finance and Economics: Tools and Emerging Applications, B. Alexandrova-Kabadjova, S. Martinez-Jaramillo, A. L. Garcia-Almanza and E. Tsang (eds.), IGI Global, 2012, pp. 202-228.
  10. P. R. Kaltwasser, “Uncertainty about fundamentals and herding behavior in the FOREX market”, Physica A: Statistical Mechanics and its Applications, 389 (6), pp. 1215-1222, March 2010.
  11. J. B. Glattfelder, A. Dupuis and R. Olsen, “Patterns in high-frequency FX data: Discovery of 12 empirical scaling laws”, Quantitative Finance, 11 (4), pp. 599-614, 2011.
  12. R.P. Barbosa and O. Belo, “Multi-Agent Forex Trading System”, in Agent and Multi-agent Technology for Internet and Enterprise Systems, Studies in Computational Intelligence, vol. 289, 2010, pp. 91-118.
  13. F. H. Westerhoff, “Multi-Asset Market Dynamics”, Macroeconomic Dynamics, 8/2011, pp. 596—616, 2011.
  14. S. Johnson, "Push to tap into EM currency returns”, Financial Times, February 2011.
  15. A. Kritzer, “Forex For Beginners. A Comprehensive Guide to Profiting from the Global Currency Markets”, Apress, 2012.
  16. J. Kumar, T. Rao and S. Srivastava, “Economics of Gold Price Movement-Forecasting Analysis Using Macro-economic, Investor Fear and Investor Behavior Features”, in S. Srinivasa, V. Bhatnagar (eds.), Big Data Analytics, Lecture Notes in Computer Science, Volume 7678, Springer-Verlag, Berlin, Heidelberg 2012, pp. 111-121, http://dx.doi.org/10.1007/978-3-642-35542-4_10.
  17. J. Korczak, M. Hernes and M. Bac, “Fuzzy Logic as Agents’ Knowledge Representation in A-Trader System”, in E. Ziemba (ed.), Information Technology for Management, Lecture Notes in Business Information Processing, vol. 243, Springer International Publishing, 2016, pp. 109-124.
  18. J. Korczak, M. Hernes and M. Bac, “Performance evaluation of decision- making agents’ in the multi-agent system”, in Proceedings of Federated Conference Computer Science and Information Systems (FedCSIS), Warszawa, 2014, pp. 1171 – 1180. http://dx.doi.org/10.15439/2014F188.
  19. M. Hernes and N.T. Nguyen, “Deriving Consensus for Hierarchical Incomplete Ordered Partitions and Coverings”, Journal of Universal Computer Science 13 (2) , pp. 317-328, 2007.
  20. M. Hernes and J. Sobieska-Karpińska , “Application of the consensus method in a multi-agent financial decision support system”, Information Systems and e-Business Management 14 (1), Springer Berlin Heidelberg, 2016, http://dx.doi.org/10.1007/s10257-015-0280-9.
  21. P. D. McNelis, “Neural Networks in Finance: Gaining Predictive Edge in the Market” (Academic Press Advanced Finance Series). Academic Press, Inc., Orlando, FL, USA, 2004.
  22. F. Ahrens, "U.S. Trade Imbalance Widens Slightly: So What?" Washington Post, May 2009.
  23. S. Johnson, "Push to tap into EM currency returns”, Financial Times, February 2011.
  24. J. Beckmann, A. Belke and M. Kühl, “The dollar-euro exchange rate and macroeconomic fundamentals: a time-varying coefficient approach”, Review of World Economics 147 (1), pp 11-40, 2011.
  25. P. Singh and B. Borah, “Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization”, International Journal of Approximate Reasoning, 55 (3), pp. 812-833, 2014.
  26. P. van Foreest and C. G. de Vries, “The Forex Regime and EMU Expansion”, Open Economies Review, 14 (3), pp. 285-298, 2003.
  27. http://forexmarketexplained.com/