Designing a Comprehensive Reference Architecture for AI-Enabled Trading Systems in Financial Market

Designing a Comprehensive Reference Architecture for AI-Enabled Trading Systems in Financial Market | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 28 January 2025 V1 Latest version Share on Designing a Comprehensive Reference Architecture for AI-Enabled Trading Systems in Financial Market Authors : Seyed Amir Agah , Ali Yazdian Varjani 0000-0001-8561-6389 [email protected] , Farsad Zamani Boroujeni , and Samaneh Yazdani Authors Info & Affiliations https://doi.org/10.22541/au.173809225.54632726/v1 368 views 97 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Today, integrating AI-enabled algorithmic trading and market prediction services into different financial ecosystems is a high-priority requirement. The design of a reference architecture for these systems is important. Although research exists in this domain, a reliable and comprehensive reference architecture for financial market is needed. This paper proposes a new comprehensive reference architecture for trading systems (RATS) which considers all compulsive components in an auto trading system. The inclusion of AI has been considered as the main component of the RATS. The proposed architecture is described using a combination of a 4+1 View and UML diagrams. By evaluating the proposed reference architecture, the abstraction level has been kept as high as possible. The Architecture Tradeoff Analysis Method (ATAM) has been used to evaluate RATS’s quality attributes, including availability and operational consistency. The results confirm that the RATS effectively covered system attributes such as performance, interoperability, and modifiability for the auto trading systems in the financial market. Supplementary Material File (a_reference_software_architecture_journal_of_software.docx) Download 1.69 MB File (figures_tif.rar) Download 901.24 KB Information & Authors Information Version history V1 Version 1 28 January 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence auto trading system financial market machine learning quality attribute reference architecture Authors Affiliations Seyed Amir Agah Islamic Azad University View all articles by this author Ali Yazdian Varjani 0000-0001-8561-6389 [email protected] Tarbiat Modares University Faculty of Electrical and Computer Engineering View all articles by this author Farsad Zamani Boroujeni Islamic Azad University View all articles by this author Samaneh Yazdani Islamic Azad University Tehran North Branch Department of Computer Engineering View all articles by this author Metrics & Citations Metrics Article Usage 368 views 97 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Seyed Amir Agah, Ali Yazdian Varjani, Farsad Zamani Boroujeni, et al. Designing a Comprehensive Reference Architecture for AI-Enabled Trading Systems in Financial Market. Authorea . 28 January 2025. 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