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Contextual Analysis of Financial Time Series

Author

Listed:
  • Nadezhda Yarushkina

    (Department of Information Systems, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, Russia)

  • Aleksey Filippov

    (Department of Information Systems, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, Russia)

  • Anton Romanov

    (Department of Information Systems, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, Russia)

Abstract

The evaluation of the financial state of small and medium-sized companies is a pressing issue today. This article introduces a novel method to evaluate a company’s financial state, implemented as a module within a decision support system. This component uses fuzzy logic and knowledge engineering methods. The article describes an ontological model that provides the framework for data analysis and financial time-series modeling. The ontological framework simplifies the representation of the trends in the financial indicators under analysis. Integrating an ontology and a set of fuzzy rules makes it possible to develop control systems based on fuzzy inference. This approach provides the analysis and interpretation of results. The experimental results validate the accuracy and effectiveness of the proposed method.

Suggested Citation

  • Nadezhda Yarushkina & Aleksey Filippov & Anton Romanov, 2024. "Contextual Analysis of Financial Time Series," Mathematics, MDPI, vol. 13(1), pages 1-17, December.
    • Handle: RePEc:gam:jmathe:v:13:y:2024:i:1:p:57-:d:1554695
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