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

Juszczuk Przemysław, Kruś Lech

Control and Cybernetics

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2022

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Vol. 51, No. 4

467--486

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.

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Supporting decisions on the Forex market using fuzzy approach

Juszczuk Przemysław, Kruś Lech

Journal of Automation Mobile Robotics and Intelligent Systems

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2020

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Vol. 14, No. 2

50--62

EN

A new concept of the multicriteria fuzzy trading system using the technical analysis is proposed. The existing trading systems use different indicators of the technical analysis and generate buy or sell signal only when assumed conditions for a given indicator are satisfied. The information presented to the trader – decision maker is binary. The decision maker obtains a signal or no. In comparison to the existing traditional systems called as crisp, the proposed system treats all considered indicators jointly using the multicriteria approach and the binary information is extended with the use of the fuzzy approach. Currency pairs are considered as variants in the multicriteria space in which criteria refer to different technical indicators. The introduced domination relation allows generating the most efficient, non‐dominated (Pareto optimal) variants in the space. An algorithm generated these non-dominated variants is proposed. It is implemented in a computer‐based system assuring the sovereignty of the decision maker. We compare the proposed system with the traditional crisp trading system. It is made experimentally on different sets of real‐world data for three different types of trading: short‐term, medium and long‐term trading. The achieved results show the computational efficiency of the proposed system. The proposed approach is more robust and flexible than the traditional crisp approach. The set of variants derived for the decision maker in the case of the proposed approach includes only non‐dominated variants, what is not possible in the case of the traditional crisp approach. The reservation point and its impact on the overall results are measured with the use of the sensitivity analysis.

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A condition for asset redundancy in the mean-variance model of portfolio investment

Juszczuk Przemysław, Kaliszewski Ignacy, Miroforidis Janusz, Podkopaev Dmitry

Control and Cybernetics

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2020

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Vol. 49, No. 2

179--191

EN

The mean-variance approach to portfolio investment exploits the fact that the diversification of investments by combination of different assets in one portfolio allows for reducing the financial risks significantly. The mean-variance model is formulated as a bi-objective optimization problem with linear (expected return) and quadratic (variance) objective functions. Given a set of available assets, the investor searches for a portfolio yielding the most preferred combination of these objectives. Naturally, the search is limited to the set of non-dominated combinations, referred to as the Pareto front. Due to the globalization of financial markets, investors nowadays have access to large numbers of assets. We examine the possibility of reducing the problem size by identifying those assets, whose removal does not affect the resulting Pareto front, thereby not deteriorating the quality of the solution from the investor’s perspective. We found a sufficient condition for asset redundancy, which can be verified before solving the problem. This condition is based on the possibility of reallocating the share of one asset in a portfolio to another asset without deteriorating the objective function values. We also proposed a parametric relaxation of this condition, making it possible to removemore assets for a price of a negligible deterioration of the Pareto front. Computational experiments conducted on five real-world problems have demonstrated that the problem size can be reduced significantly using the proposed approach.