International Scientific Conference „Business and Management“, 11th International Scientific Conference „Business and Management 2020“

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Investigation of decision making support in digital trading
Ilona Stalovinaitė, Nijolė Maknickienė, Raimonda Martinkutė-Kaulienė

Last modified: 2020-06-16

Abstract


In order to trade successfully investors are looking for the best method to determine possible di-rections of the price changes of financial means. The main objective of this paper is to evaluate the results of digital trading using different decision-making techniques. The paper examines deep learning technique known as Long Short – Term Memory (LSTM) neural network and parabolic stop and reverse (SAR) technical indicator as possible means for decision-making support. Based on an investigation of theoretical and practical aspects of digital trading and its support possibilities, investment portfolios in real-time “IQ Option” digital trading platform were created. Short-term results show that investment portfolios created using LSTM neural network performed better compared to the ones that were created using technical analysis. The study contributes to the development of new decision-making algorithms that can be used for forecasting of the results in the financial markets.

DOI: https://doi.org/10.3846/bm.2020.510


Keywords


deep learning, neural network, technical analysis, digital trading, investment portfolio

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