The Forex Trading System for Speculation with Constant Magnitude of Unit Return

Krzysztof Piasecki , Michał Stasiak


The main purpose of this article is to investigate a speculative trading system with a constant magnitude of return rate. We consider speculative operations related to the exchange rate given as the quotient of the base exchange medium by the quoted currency. An exchange medium is understood as any currency or any precious metal. The unit return is defined as the return expressed in the quoted currency by the amount of base exchange medium. All possible states of the exchange market form a finite elemental space. All knowledge about the dynamics of this market is presented as a prediction table describing the conditional probability distributions of incoming exchange rate changes. On the other hand, in the proposed trading system each speculative operation is concluded in such a way that the gross payment is determined by the given magnitude of unit return. The paper contains an analysis of the following evaluation criteria: annual number of transaction, success probability, expected unit payment, expected unit profit, risk index, unit risk premium, return rate, interest rate, and interest risk premium. Both of these indices can be used to select the effective trading systems. Effectiveness is considered in the local sense and in the global sense
Author Krzysztof Piasecki (WZ / KIiN)
Krzysztof Piasecki,,
- Department of Investment and Real Estate
, Michał Stasiak (WZ / KIiN)
Michał Stasiak,,
- Department of Investment and Real Estate
Journal seriesMathematics, ISSN 2227-7390, (N/A 20 pkt)
Issue year2019
Publication size in sheets1.1
Article number623
Keywords in Polishsystem spekulacyjny, tablica predykcyjna, efektywność finansowa
Keywords in Englishpeculative trading system; prediction table; financial effectiveness
Languageen angielski
Score (nominal)20
Score sourcejournalList
ScoreMinisterial score = 20.0, 09-04-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; WoS Impact Factor: 2018 = 1.105 (2)
Citation count*3 (2020-10-26)
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