Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Designing a Decision Support System for Capital Markets. / Voronova, Natalia S.; Vinogradov, Andrei N.; Sharich, Ermin E.; Iakovleva, Daria D.
System Analysis in Engineering and Control. ed. / Yuriy S. Vasiliev; Nataliya D. Pankratova; Violetta N. Volkova; Olga D. Shipunova; Nikolay N. Lyabakh. Springer Nature, 2022. p. 473-486 (Lecture Notes in Networks and Systems; Vol. 442 LNNS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
}
TY - GEN
T1 - Designing a Decision Support System for Capital Markets
AU - Voronova, Natalia S.
AU - Vinogradov, Andrei N.
AU - Sharich, Ermin E.
AU - Iakovleva, Daria D.
N1 - Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022/8/1
Y1 - 2022/8/1
N2 - The article deals with the weakly formalized problem of decision-making under conditions of rapid development of analysis tools and intelligent technologies in the financial market. These circumstances determine the necessity of systematic analysis, monitoring, and considering the signs of changes of poorly-structured phenomena that affect the process of decision-making on the capital market, both in the governance structure of hedge fund (interests, incentives, motives) and in the governance subsystem (project changes, investments, transactions, portfolio). System diagnostics of strategic problem situations requires the study of properties, relations, and structure of elementary objects in the system and connections between separate elementary objects of the financial system. This, therefore, makes it necessary to create a support system of investment decision-making in hedge funds using neural technologies of data collection and processing of information about the movement of the capital market, systematic approach, and logical–linguistic modeling of the consequences of management decisions (results, damage). Institutional nature of hedge funds allows the application of tools of artificial neural networks, developed on methods of fuzzy logic, logic-linguistic modeling and rules, and determines their competitive advantages over other investment intermediaries in the emerging financial markets, especially over banks, when placing the raised resources to design new products and modern technology management. The research will result in designing a decision support system for investment decisions based on neural network technology, systematic analysis of risks that can lead to problematic situations, and dynamic management of hedge fund Bridgewater LLC’s investment strategies.
AB - The article deals with the weakly formalized problem of decision-making under conditions of rapid development of analysis tools and intelligent technologies in the financial market. These circumstances determine the necessity of systematic analysis, monitoring, and considering the signs of changes of poorly-structured phenomena that affect the process of decision-making on the capital market, both in the governance structure of hedge fund (interests, incentives, motives) and in the governance subsystem (project changes, investments, transactions, portfolio). System diagnostics of strategic problem situations requires the study of properties, relations, and structure of elementary objects in the system and connections between separate elementary objects of the financial system. This, therefore, makes it necessary to create a support system of investment decision-making in hedge funds using neural technologies of data collection and processing of information about the movement of the capital market, systematic approach, and logical–linguistic modeling of the consequences of management decisions (results, damage). Institutional nature of hedge funds allows the application of tools of artificial neural networks, developed on methods of fuzzy logic, logic-linguistic modeling and rules, and determines their competitive advantages over other investment intermediaries in the emerging financial markets, especially over banks, when placing the raised resources to design new products and modern technology management. The research will result in designing a decision support system for investment decisions based on neural network technology, systematic analysis of risks that can lead to problematic situations, and dynamic management of hedge fund Bridgewater LLC’s investment strategies.
KW - Decision support system
KW - Design
KW - Investment
KW - Management
KW - Network technology
KW - Neural network
KW - System analysis
UR - http://www.scopus.com/inward/record.url?scp=85128980775&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/db9317af-6dd2-3b70-845b-0aaf1d9f958d/
U2 - 10.1007/978-3-030-98832-6_42
DO - 10.1007/978-3-030-98832-6_42
M3 - Conference contribution
AN - SCOPUS:85128980775
SN - 9783030988319
T3 - Lecture Notes in Networks and Systems
SP - 473
EP - 486
BT - System Analysis in Engineering and Control
A2 - Vasiliev, Yuriy S.
A2 - Pankratova, Nataliya D.
A2 - Volkova, Violetta N.
A2 - Shipunova, Olga D.
A2 - Lyabakh, Nikolay N.
PB - Springer Nature
T2 - 25th International Conference on System Analysis in Engineering and Control, SAEC 2021 and 12th International Scientific and Theoretical Conference on Communicative Strategies of the Information Society, CSIS 2021
Y2 - 22 October 2021 through 23 October 2021
ER -
ID: 98139154