Abstract
Abstract
The problem of economic time series analysis and forecasting using amplitude-frequency analysis of STL decomposition is considered. An amplitude-phase operator was chosen as an apparatus for extraction the series harmonic components, the advantages of which (compared to the Fourier transform) are: calculations speed, result accuracy, simplicity and interpretability of software implementation. The forecast quality was carried out using the MAPE metric. Significantly higher prediction quality was achieved compared to Facebook Prophet forecasting package.
Subject
General Physics and Astronomy
Reference20 articles.
1. Forecasting foreign exchange rate by using ARIMA model: A case of VND/USD exchange rate;Ngan;Methodology,2016
2. Forecasting exchange rate between the Ghana cedi and the US dollar using time series analysis;Appiah;Current research journal of economic theory,2011
3. A combined independent component analysis - neural network model for forecasting exchange rate variation;Henriquez;Appl. Soft Comput.,2019
4. A hybrid artificial neural network-GJR modeling approach to forecasting currency exchange rate volatility;Baffour;Neurocomputing,2019
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Research on Short-Term and Medium-Term Power Load Forecasting Based on STL-LightGBM;2022 2nd International Conference on Electrical Engineering and Control Science (IC2ECS);2022-12-16