Collective Intelligence Supporting Trading Decisions on FOREX Market

Korczak, Jerzy; Hernes, Marcin; Bac, Maciej

doi:10.1007/978-3-319-67074-4_12

Cited by 12 publications

(6 citation statements)

References 10 publications

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“…As a consequence, this enables the trader to compose an evaluation function according to their preferences and to apply to the strategies of the best Supervisor Agents. The results presented in our previous research [13,14,21,22,24,25] allow us to come to the conclusions that there is no universally accepted evaluation function nor universal measures. The choice of measures and the composition of the evaluation function is highly dependent on trader preferences and trading market.…”

Section: Discussionmentioning

confidence: 85%

“…It allows for High Frequency Trading (HFT). It is realized in near real time (the notion of "near real time" can be understood as a very short delay between the last quote and the time of generated trading decision; usually 10-250 ms) and characterized by high speed, short-term positions, it concentrates attention on price formation process using sophisticated algorithms based on efficient and robust indicators and modern IT [14]. High frequency traders take decisions on the basis of real-time quotes changes in order to achieve satisfactory rate of return.…”

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confidence: 99%

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Performance evaluation of trading strategies in multi-agent systems – Case of A-Trader

Korczak

Hernes

2018

Annals of Computer Science and Information Systems

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The article presents the problem related to evaluation of Forex trading strategies in multi-agent systems. The ratios based on financial measures cannot be assumed to be only evaluation criteria because other aspects determining effectiveness of the strategies, such as, for instance, investment risk, statistics on winning, and lost transactions, transaction costs, should also be taken into consideration. The aim of this paper is to review the general financial investments performance measures in relation to the performance analysis of trading strategies. The characteristics of the commonly used performance measures are outlined. The discussion will be illustrated by solutions developed in the trading support system, called A-Trader system. The performance analysis in A-Trader is detailed on real FOREX quotations.

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Section: Discussionmentioning

confidence: 85%

mentioning

confidence: 99%

Performance evaluation of trading strategies in multi-agent systems – Case of A-Trader

Korczak

Hernes

2018

Annals of Computer Science and Information Systems

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“…In the literature, we can find many examples of its application in many various domains [33]- [36]. FIGURE 5: General overview of a multi-agent system [37] As an inspiration for our researches, we have found A-Trader system [27], [28]. It's a multi-agent system, that uses the power of the collective intelligence, dedicated to support decision-making on financial markets.…”

Section: A Simulation System Designmentioning

confidence: 99%

The Impact of the Collective Members’ Independence on the Prediction Accuracy

Sitarczyk

Nguyen

2021

IEEE Access

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Decision making is one of the most frequently performed processes nowadays. Our future or other people's future may depend on the decision we make, therefore we try to take it as good as possible. The rapid development of technology facilitates it for us, as we are able to store, process and analyse more and more data. However, the power of human knowledge extended by experience and intuition still overperforms computer systems in solving such problems. The power of the combined knowledge of a group of people is known as a collective intelligence. In this paper, we present an analysis of one of the properties describing the consensus, id est the influence between its members. We base our work on graph theory and a multi-agent system approach and provide an experimental evaluation and a statistical analysis of obtained results. As a result, we observed four relationships between the considered measures describing the collective and the accuracy of collective prediction.

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“…Due to the volatility of the Forex market, there are three types of portfolios: high-frequency traders, long-term investors, and corporations. This paper proposes a trading for high-frequency traders who speculate small intraweek price fluctuations [37,58].…”

Section: Investment Strategy the Portfolio Theory Appeared In 1952 Bmentioning

confidence: 99%

Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression

Chihab

Bousbaa

Chihab

et al. 2019

Applied Computational Intelligence and Soft Computing

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In the Forex market, the price of the currencies increases and decreases rapidly based on many economic and political factors such as commercial balance, the growth index, the inflation rate, and the employment indicators. Having a good strategy to buy and sell can make a profit from the above changes. A successful strategy in Forex should take into consideration the relation between benefits and risks. In this work, we propose an intraweek foreign exchange speculation strategy for currency markets based on a combination of technical indicators. This system has a two-level decision and is composed of the Probit regression model and rules discovery using Random Forest. There are two minimum requirements for a trading strategy: a rule to enter the market and a rule to exit it. Our proposed system, to enter the currency market, should validate two conditions. First, it should validate Random Forest access rules over the following week while in the second one the predicted value of the next day using Probit should be positive. To exit the currency market just one negative warning from Probit or Random Forest is enough. This system was used to develop dynamic portfolio trading systems. The profitability of the model was examined for USD/(EUR, JYN, BRP) variation within the period from January 2014 to January 2016. The proposed system allows improving the prediction accuracy. This indicates a good prediction of the behavior market and it helps to identify the good times to enter it or to leave it.

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Collective Intelligence Supporting Trading Decisions on FOREX Market

Cited by 12 publications

References 10 publications

Performance evaluation of trading strategies in multi-agent systems – Case of A-Trader

Performance evaluation of trading strategies in multi-agent systems – Case of A-Trader

The Impact of the Collective Members’ Independence on the Prediction Accuracy

Algo-Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression

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