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 -