Financial Trading Technological Advancements: Systematic Review

Introduction. Transformations have drastically reshaped the landscape of financial markets, making it necessaryto reassess current knowledge and future trends of financial trading technologies (FTT).Problem Statement. The use of a variety of FTT requires to structure them depending on the level of machinetechnology and the level of trading strategy.Purpose. To investigate the technological advancements in financial trading to assess the quality of scientificresearch and outline promising areas for further development.Materials and Methods. By following the PRISMA 2020 standard, this systematic review covers 130 researcharticles (for 2013—2023) on FTT, focusing on technologies used. An innovative Four-Quadrant Theory was usedto analyze the synergy between machine technology and trading strategy, which is based on 2 dimensions’ total of8 factors.Results. Key financial technologies include algorithmic trading, machine learning, and deep learning, eachwith unique traits: speed, automation, adaptability, and complex pattern recognition. These technologies haveimproved market efficiency, risk management, and personalized trading strategies. The Four-Quadrant Theoryoffers a structured approach to understanding the interaction between machine technology and trading strategies and divides interactions into four quadrants.Conclusions. The transformative impact of technological advancements in financial trading is evident. The maintechnologies have substantially improved market liquidity, trading efficiency, and risk management practices. TheFour-Quadrant Theory lets to suggests that further exploration could lead to more intelligent, diversifi ed trading systems, with data-driven decision-making and artificial intelligence playing pivotal roles. The importance of hybrid technology, scientific assessment of performance and the cutting-edge development of autonomous intelligent trading systems for the further study of financial trading technology were underscored.

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Journal
Science and innovation
Published
2025-06-12
DOI
https://doi.org/10.15407/scine21.03.016
Primary Topic
Stock Market Forecasting Methods
Type
article
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article

Financial Trading Technological Advancements: Systematic Review

Антоніна Шолойко, Hou PENGYUE
Science and innovation
Stock Market Forecasting Methods
article

Financial Trading Technological Advancements: Systematic Review

Антоніна Шолойко, Hou PENGYUE
article en

Abstract

Introduction. Transformations have drastically reshaped the landscape of financial markets, making it necessaryto reassess current knowledge and future trends of financial trading technologies (FTT).Problem Statement. The use of a variety of FTT requires to structure them depending on the level of machinetechnology and the level of trading strategy.Purpose. To investigate the technological advancements in financial trading to assess the quality of scientificresearch and outline promising areas for further development.Materials and Methods. By following the PRISMA 2020 standard, this systematic review covers 130 researcharticles (for 2013—2023) on FTT, focusing on technologies used. An innovative Four-Quadrant Theory was usedto analyze the synergy between machine technology and trading strategy, which is based on 2 dimensions’ total of8 factors.Results. Key financial technologies include algorithmic trading, machine learning, and deep learning, eachwith unique traits: speed, automation, adaptability, and complex pattern recognition. These technologies haveimproved market efficiency, risk management, and personalized trading strategies. The Four-Quadrant Theoryoffers a structured approach to understanding the interaction between machine technology and trading strategies and divides interactions into four quadrants.Conclusions. The transformative impact of technological advancements in financial trading is evident. The maintechnologies have substantially improved market liquidity, trading efficiency, and risk management practices. TheFour-Quadrant Theory lets to suggests that further exploration could lead to more intelligent, diversifi ed trading systems, with data-driven decision-making and artificial intelligence playing pivotal roles. The importance of hybrid technology, scientific assessment of performance and the cutting-edge development of autonomous intelligent trading systems for the further study of financial trading technology were underscored.

Science and innovationVol. 21(3)
Taras Shevchenko National University of Kyiv (UA)
Openalex Percentile: Top 83%
Stock Market Forecasting Methods
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