Forecasting Time Series in the Stock Exchange Quotations Using the Fourier Series

The paper describes an actual task of forecasting the quotation time series in a stock market. It defines peculiarities in working with the time series, analyzes the process of dividing the time series into components and methods of the series consolidation in a stationary form. The paper presents theoretical basis for using the Fourier series in forecasting the series. It provides a technique in the Fourier series algorithm finetuning the one-step and long-term forecast. Comparing the forecast results, it analyzes the delay value influence on the algorithm accuracy.

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Published
2025-04-08
DOI
https://doi.org/10.1109/reepe63962.2025.10970907
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
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article

Forecasting Time Series in the Stock Exchange Quotations Using the Fourier Series

Vladimir V. Gurenko, Mark E. Khabarov
Neural Networks and Applications
article

Forecasting Time Series in the Stock Exchange Quotations Using the Fourier Series

Vladimir V. Gurenko, Mark E. Khabarov
article en

Abstract

The paper describes an actual task of forecasting the quotation time series in a stock market. It defines peculiarities in working with the time series, analyzes the process of dividing the time series into components and methods of the series consolidation in a stationary form. The paper presents theoretical basis for using the Fourier series in forecasting the series. It provides a technique in the Fourier series algorithm finetuning the one-step and long-term forecast. Comparing the forecast results, it analyzes the delay value influence on the algorithm accuracy.

Bauman Moscow State Technical University (RU)
Openalex Percentile: Top 95%
Neural Networks and Applications
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