Prediction of EUR/AZN exchange rate dynamics on the basis of spectral characterıstıcs
Vol. 13, No 2, 2020
Elshar Orudzhev
Department of Mathematical Economy, Baku State University (BSU), Azerbaijan elsharorucov63@mail.ru ORCID 0000-0002-6985-1407 |
Prediction of EUR/AZN exchange rate dynamics on the basis of spectral characterıstıcs |
Leyla Mammadova
Department of Mathematical Economy, Baku State University (BSU), Azerbaijan l.mamedova2807@gmail.com ORCID 0000-0003-0512-2958
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Abstract. Herein, we establish the most appropriate model of exchange rate dynamics using computer modeling, mean-error indicators of approximation, and the average quadratic divergence with the Fourier series approach and time-dependent behavior in a time series. This study was based on 360 daily observations of EUR/AZN currency exchanges covering the time period 03.02.2017–03.08.2018. Our main assumptions were: (1) the ability to describe the global dynamics of exchange rates by approximating the combinations of the linear trend and harmonic oscillations of various frequencies relative to this line; and (2) the possibility of developing a high-precision algorithm for short-term forecasting of changes in exchange rates. Harmonious oscillations were separated by using methods for the harmonic analysis of the table error in MS EXCEL. Eviews was used to calculate statistical estimates of the coefficients of factor variables with the types of sines and cosines that are suitable for all possible frequencies. Dynamic forecasting of exchange rates was enabled by setting up harmonious oscillatory models with straight-line trends. The necessary statistical procedures were implemented for authentication of the established models, evaluation of parameters, and verification of the algorithm’s adequacy. |
Received: September, 2019 1st Revision: February, 2020 Accepted: May, 2020 |
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DOI: 10.14254/2071-8330.2020/13-2/17
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JEL Classification: C10, C14, C15, C53, F31 |
Keywords: Fourier series, regressive analysis, correlation analysis, t-Student criterion, F-test, Darbin–Watson test, determination factor, Spearman rank correlation factor, prediction |