Investment Strategies Support Using Deep Learning: Towards Theoretical Framework
Klaudia Kaczmarczyk , Marcin Hernes , Anna Chojnacka-Komorowska , Adam Zawadzki , Artur Rot
AbstractInvestment decision-supporting computer systems operate mainly on the basis of technical analysis. Fundamental and behavioral analysis is also aided with computer tools, but the integration of data remains at the discretion of the user since the market lacks a holistic system that automatically integrates the results of technical, fundamental, and behavioral analysis. The main aim of the paper is to develop a conceptual framework of investment decision support systems using cognitive technologies, including deep learning. The study of subject literature by authors has revealed a lack of both papers with a comprehensive presentation of methods to build an automated investment strategy building system and a lack of works about automated systems used in the Polish stock market. The main contribution is to develop a holistic approach based on integration by using collective intelligence methods. The article also fills the gap in using deep learning methods in the Polish stock market.
|Publication size in sheets||0.5|
|Book||Soliman Khalid S. (eds.): Education Excellence and Innovation Management: A 2025 Vision to Sustain Economic Development during Global Challenges, 2020, International Business Information Management Association (IBIMA), ISBN 9780999855141|
|Keywords in English||Deep Learning, Artificial Intelligence, Investment Strategies, Financial Decisions|
|Uwaga||'The project is financed by the Ministry of Science and Higher Education in Poland under the program 'Regional Initiative of Excellence' 2019 - 2022 project number 015/RID/2018/19 total funding amount 10 721 040,00 PLN.'|
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