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.
Authors
- Vladimir V. Gurenko (ORCID: https://orcid.org/0000-0002-6421-0467)
- Mark E. Khabarov
Institutions
- Bauman Moscow State Technical University (RU)
Publication Details
- 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
- 0.00