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Parameter Estimation for Dynamic Model of the Financial System

Author

Listed:
  • Veronika Novotná

    (Department of Informatics, Faculty of Business and Management, Brno University of Technology, Antonínská 548/1, 601 90 Brno, Czech Republic)

  • Vladěna Štěpánková

    (Department of Informatics, Faculty of Business and Management, Brno University of Technology, Antonínská 548/1, 601 90 Brno, Czech Republic)

Abstract

Economy can be considered a large, open system which is influenced by fluctuations, both internal and external. Based on non-linear dynamics theory, the dynamic models of a financial system try to provide a new perspective by explaining the complicated behaviour of the system not as a result of external influences or random behaviour, but as a result of the behaviour and trends of the system's internal structures. The present article analyses a chaotic financial system from the point of view of determining the time delay of the model variables - the interest rate, investment demand, and price index. The theory is briefly explained in the first chapters of the paper and serves as a basis for formulating the relations. This article aims to determine the appropriate length of time delay variables in a dynamic model of the financial system in order to express the real economic situation and respect the effect of the history of factors under consideration. The determination of the delay length is carried out for the time series representing Euro area. The methodology for the determination of the time delay is illustrated by a concrete example.

Suggested Citation

  • Veronika Novotná & Vladěna Štěpánková, 2015. "Parameter Estimation for Dynamic Model of the Financial System," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(6), pages 2051-2055.
    • Handle: RePEc:mup:actaun:actaun_2015063062051
    DOI: 10.11118/actaun201563062051
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    References listed on IDEAS

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    1. Hołyst, Janusz A & Urbanowicz, Krzysztof, 2000. "Chaos control in economical model by time-delayed feedback method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 587-598.
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