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Fuzzy trading system on the forex market for deriving the portfolio of instruments

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Decision support and trading systems for the forex market mostly derive a single signal for the decision-maker. This is so, because instruments are evaluated based on a single criterion, which creates a ranking of instruments, from which the best one is selected. At the same time, one can observe a lack of tools al- lowing one to derive the set of non-dominated trading opportunities considered in the multicriteria space. This article focuses on multicriteria analysis, in which several different market indicators describe a single instrument on the forex market (currency pair), leading to definite criteria. Thus, for a given time horizon, we consider a set of currency pairs described by a group of technical market indicators in every trading session. However, instead of deriving crisp information, based on the buy-no buy binary logic, we use concepts from the fuzzy sets theory, in which each criterion for a single variant takes a value from the h0, 1i interval. We select only the non-dominated variants from such a set, which will be used as elements of the portfolio of currency pairs on the forex market. We test our idea on the real-world data covering more than ten years, several technical market indicators, and over twenty different currency pairs. The preliminary results show that the proposed idea can be treated as a promising concept for deriving a portfolio of currency pairs instead of focusing on only a single currency pair.
Rocznik
Strony
467--486
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
  • Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland
autor
  • Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland
Bibliografia
  • Angelelli, E., Mansini, R. and Grazia Speranza, M. (2012) Kernel Search: a new heuristic framework for portfolio selection. Computational Optimization and Applications, 51(1), 345–361.
  • Anyfantaki, S., Arvanitis, S. and Topaloglou, N. (2021) Diversification benefits in the cryptocurrency market under mild explosivity. European Journal of Operational Research, 295, 1, 378–393.
  • Arévalo, R., Garcia, J., Guijarro, F. and Peris, A. (2017) A dynamic trading rule based on filtered flag pattern recognition for stock market price forecasting. Expert Systems with Applications, 81, 177–192.
  • Bagheri, A., Peyhani, H. M. and Akbari, M. (2014) Financial forecasting using ANFIS networks with Quantum-behaved Particle Swarm Optimization. Expert Systems with Applications, 41, 14, 6235–6250.
  • Banik, S., Sharma, N., Mangla, M., Mohanty, S. and Shitharth, S. (2022) LSTM based decision support system for swing trading in stock market. Knowledge-Based Systems, 239, 107944.
  • Briec, W., Kerstens, K. and de Woestyne, I.V. (2013) Portfolio selection with skewness: a comparison of methods and a generalized one fund result. European Journal of Operational Research, 230, 2, 412–421.
  • Brzeszczyński, J. and Ibrahim, B. M. (2019) A stock market trading system based on foreign and domestic information. Expert Systems with Applications, 118, 381–399.
  • Chmielewski, L., Janowicz, M. and Kaleta, J. (2015) Pattern recognition in the Japanese candlesticks. Soft Computing Computer Information Sciences, 342, 227–234.
  • Dymova, L., Sevastjanov, P. and Kaczmarek, K. (2016) A forex trading expert system based on a new approach to the rule-base evidential reasoning. Expert Systems with Applications, 51, 1–13.
  • Juszczuk, P. and Kruś, L. (2020) Soft multicriteria computing supporting decisions on the Forex market. Applied Soft Computing, 96, 106654.
  • Kaoa, C and Steuer, R. E. (2016) Value of information in portfolio selection, with a Taiwan stock market application illustration. European Journal of Operational Research, 253(2), 418–427.
  • Lee, S. M. (1972) Goal Programming for Decision Analysis. Auerbach Publishers, Philadelphia.
  • Markowitz, H. (1952) Portfolio selection. Journal of Finance. 7, 1, 77–91.
  • Merton, R. C. (1974) On the Pricing of Corporate Debt: The Risk Structure of Interest Rates. Journal of Finance, 29, 2, 449–470.
  • Naranjo, R. and Santos, M. (2019) A fuzzy decision system for money investment in stock markets based on fuzzy candlesticks pattern recognition. Expert Systems with Applications, 133, 34–48.
  • Ozturk, M., Toroslu, I. H. and Fidan, G. (2016) Heuristic based trading system on forex data using technical indicator rules. Applied Soft Computing, 43, 170–186.
  • Petropoulos, A., Chatzis, S.P., Siakoulis, V. and Vlachogiannakis, N. (2017) A stacked generalization system for automated FOREX portfolio trading. Expert Systems with Applications, 90, 290–302.
  • Steuer, R. E. and Na, P. (2003) Multiple criteria decision making combined with finance: A categorized bibliography. European Journal of Operational Research, 150(3):496–515.
  • Steuer, R. E., Qi, Yue and Hirschberger, M. (2007) Suitable-portfolio investors, nondominated frontier sensitivity, and the effect of multiple objectives on standard portfolio selection. Annals of Operations Research, 152(1):297–317.
  • Thawornwong, S., Enke, D. and Dagli, C. (2010) Neural Pattern recognition with self-organizing maps for efficient processing of forex market data streams. Artificial Intelligence and Soft Computing, LNCS, 6113, 307–314.
  • Utz, S., Wimmer, M. and Steuer, R.E. (2015) Tri-criterion modeling for constructing more-sustainable mutual funds. European Journal of Operational Research, 246, 1, 331–338.
  • Yaoa, H., Lib, Z. and Lai, Y. (2013) Mean–CVaR portfolio selection: A nonparametric estimation framework. Computers & Operations Research, 40(4),1014–1022.
  • Vetschera, R. and de Almeida, A. T. (2012) A PROMETHEE-based approach to portfolio selection problems. Computers & Operations Research, 39, 1010–1020.
  • Zopounidis, C. and Doumpos, M. (2013) Multicriteria decision systems for financial problems. TOP, 21(2), 241–261.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c0047153-6ca4-4e42-b904-7bb0fbe5f0fa
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