<doi_batch xmlns="http://www.crossref.org/schema/4.4.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" version="4.4.0"><head><doi_batch_id>327965f8-f9ff-4706-a804-982041f7efe9</doi_batch_id><timestamp>20230214090251510</timestamp><depositor><depositor_name>wseas:wseas</depositor_name><email_address>mdt@crossref.org</email_address></depositor><registrant>MDT Deposit</registrant></head><body><journal><journal_metadata language="en"><full_title>WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL</full_title><issn media_type="electronic">2224-2856</issn><issn media_type="print">1991-8763</issn><archive_locations><archive name="Portico"/></archive_locations><doi_data><doi>10.37394/23203</doi><resource>http://wseas.org/wseas/cms.action?id=4073</resource></doi_data></journal_metadata><journal_issue><publication_date media_type="online"><month>1</month><day>2</day><year>2023</year></publication_date><publication_date media_type="print"><month>1</month><day>2</day><year>2023</year></publication_date><journal_volume><volume>18</volume><doi_data><doi>10.37394/23203.2023.18</doi><resource>https://wseas.com/journals/sac/2023.php</resource></doi_data></journal_volume></journal_issue><journal_article language="en"><titles><title>Software Solution for the Implementation of a Predictive Analytics System for Investment Instruments</title></titles><contributors><person_name sequence="first" contributor_role="author"><given_name>Natalia</given_name><surname>Mamedova</surname><affiliation>Basic Department of digital economy, Higher School of Cyber Technologies, Mathematics and Statistics, Plekhanov Russian University of Economics, RUSSIA</affiliation></person_name><person_name sequence="additional" contributor_role="author"><given_name>Olga</given_name><surname>Staroverova</surname><affiliation>Basic Department of digital economy, Higher School of Cyber Technologies, Mathematics and Statistics, Plekhanov Russian University of Economics, RUSSIA</affiliation></person_name><person_name sequence="additional" contributor_role="author"><given_name>Alexey</given_name><surname>Epifanov</surname><affiliation>Basic Department of digital economy, Higher School of Cyber Technologies, Mathematics and Statistics, Plekhanov Russian University of Economics, RUSSIA</affiliation></person_name><person_name sequence="additional" contributor_role="author"><given_name>Huaming</given_name><surname>Zhang</surname><affiliation>Deputy Dean, School of Economics, Shanxi University of Finance and Economics, CHINA</affiliation></person_name><person_name sequence="additional" contributor_role="author"><given_name>Arkadiy</given_name><surname>Urintsov</surname><affiliation>Basic Department of digital economy, Higher School of Cyber Technologies, Mathematics and Statistics, Plekhanov Russian University of Economics, RUSSIA</affiliation></person_name></contributors><jats:abstract xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1"><jats:p>This article raises the issues of research investment support tools and the study of existing IT solutions in the field of predictive analytics investment solutions. The research request is based on the lack of accuracy, and objectivity of existing methods of investment analysis and means of its automation. A review of existing technical solutions and technologies is carried out. The process of analyzing investment instruments has been studied, and bottlenecks in existing approaches to analysis have been identified. A solution for implementing a system of predictive analytics of investment instruments has been developed. The solution is based on the business requirements and functional requirements of the software development company.</jats:p></jats:abstract><publication_date media_type="online"><month>12</month><day>31</day><year>2022</year></publication_date><publication_date media_type="print"><month>12</month><day>31</day><year>2022</year></publication_date><pages><first_page>18</first_page><last_page>25</last_page></pages><publisher_item><item_number item_number_type="article_number">2</item_number></publisher_item><ai:program xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" name="AccessIndicators"><ai:free_to_read start_date="2022-12-31"/><ai:license_ref applies_to="am" start_date="2022-12-31">https://wseas.com/journals/sac/2023/a045103-1226.pdf</ai:license_ref></ai:program><archive_locations><archive name="Portico"/></archive_locations><doi_data><doi>10.37394/23203.2023.18.2</doi><resource>https://wseas.com/journals/sac/2023/a045103-1226.pdf</resource></doi_data><citation_list><citation key="ref0"><doi>10.1016/j.nic.2020.08.008</doi><unstructured_citation>Letourneau-Guillon L, Camirand D, Guilbert F and Forghani R, Artificial Intelligence Applications for Workflow, Process Optimization and Predictive Analytics, Neuroimaging Clin. 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