Adaptive short-term forecasting of selected financial processes

Authors

  • Петро Іванович Бідюк Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”, Ukraine
  • Максим Михайлович Коновалюк Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”, Ukraine
  • Наталія Володимирівна Кузнєцова Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”, Ukraine
  • Ілля Віталійович Пудло Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”, Ukraine

DOI:

https://doi.org/10.20535/1810-0546.2014.1.26531

Keywords:

Adaptive forecasting, System approach, Nonlinear nonstationary processes, Model structure and parameters estimation, Complex criterion

Abstract

A computer based system is proposed for adaptive modeling and forecasting of financial and economic processes, that is constructed with application of system analysis principles. A hierarchical structure of decision making process during forecasts estimation was taken into consideration and the methods were used for describing uncertainties of structural, parametric and statistical nature. To estimate model structure and parameters several mutually supporting estimation techniques were used as well as optimal state estimation procedure for dynamic systems that allowed take into consideration some types of structural and statistical uncertainties. Probabilistic modeling methods make it possible to consider uncertainties of probabilistic type. The problem of short term forecasting for gold price is considered as an example using a set of constructed regression models and Kalman filter for generating optimal estimates of states. The best forecasting results were achieved with optimal filter and autoregression models with trends. Also the models were constructed for conditional variance that provided acceptable quality forecasts for variance (volatility) that could be used for constructing decision making rules in trading operations.

Author Biographies

Петро Іванович Бідюк, Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”

Petro Ivanovych Bidyuk,

doc. of eng. sci., professor

Максим Михайлович Коновалюк, Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”

Maxym Mykhailovych Konovalyuk,

PhD, senior instructor

Наталія Володимирівна Кузнєцова, Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”

Natalia Volodymyrivna Kuznetsova,

­PhD, senior instructor

Ілля Віталійович Пудло, Institute for Applied System Analysis of the National Technical University of Ukraine “KPI”

Illya Vitaliyovych Pudlo,

student

References

R.H. Shumway and D.S. Stoffer, Time Series Analysis and its Applications.New York: Springer Verlag, 2006, 588 p.

P.I. Bidyuk et al., Time Series Analysis.Ukraine, Kyiv: Polytechnika, NTUU KPI, 2013, 607 p. (in Ukrainian).

R. Harris and R. Sollis, Applied Time Series Modelling and Forecasting.West Sussex: Jоhn Wiley & Sons Ltd., 2005, 313 p.

M.Z. Zgurovsky and N.D. Pankratova, The System Analysis: Problems, Methodology, Applications.Ukraine, Kyiv: Naukova Dumka, 2011, 726 p. (in Ukrainian).

F.V. Jensen and Th. Nielsen, Bayesian Networks and Decision Graphs.New York: Spinger-Verlag, 2009, 457 p.

M.Z. Zgurovsky and Yu.P. Zaichenko, An Introduction to Computing Intelligence.Ukraine, Kyiv: Naukova Dumka, 2013, 406 p. (in Ukrainian).

A. Dobson, An Introduction to Generalized Linear Models.New York: CRC Press Company, 2013, 407 p.

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Published

2014-02-24

Issue

Section

Art