Exchange Rate Forecasting Based on Combined Fuzzification Strategy and Advanced Optimization Algorithm

Exchange rate forecasting is a crucial but challenging task due to the uncertainty and fuzziness of the associated data caused by complex influence factors. However, most traditional forecasting methods ignore the ambiguity of the data itself. Thus, in this paper, a novel fuzzy time series forecasti...

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Veröffentlicht in:Processes Jg. 9; H. 12; S. 2204
Hauptverfasser: Yin, Jie, Zhang, He, Zahra, Aqeela, Tayyab, Muhammad, Dong, Xiaohua, Ahmad, Ijaz, Ahmad, Nisar
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.12.2021
Schlagworte:
Accuracy
Algorithms
Artificial intelligence
Decision making
Digital currencies
Electromagnetism
Forecasting
Foreign exchange markets
Foreign exchange rates
Fuzzy sets
International finance
Mathematical models
Neural networks
Noise
Optimization
Optimization algorithms
Securities markets
Statistical methods
Stochastic models
Stock exchanges
Time series
Uncertainty
Volatility
ISSN:2227-9717, 2227-9717
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Zusammenfassung:Exchange rate forecasting is a crucial but challenging task due to the uncertainty and fuzziness of the associated data caused by complex influence factors. However, most traditional forecasting methods ignore the ambiguity of the data itself. Thus, in this paper, a novel fuzzy time series forecasting system based on a combined fuzzification strategy and an advanced optimization algorithm was proposed for use in exchange rate forecasting, and was proven to have an excellent ability to deal with the uncertainties and ambiguities in data. Concretely, the data “decomposition and ensemble” strategy was applied to carry out the data preprocessing process. The combined fuzzification strategy was used in the fuzzification of the observed data, and the advanced optimization algorithm was developed to determine the optimal parameters in the models. The analysis of this experiment verified the effectiveness of the proposed forecasting system, which will benefit future research and decision-making related to investments.
Bibliographie:ObjectType-Article-1
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ISSN:2227-9717
2227-9717
DOI:10.3390/pr9122204