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Exchange Rate Forecasting Based on Deep Learning and NSGA-II Models
- Source :
- Computational Intelligence and Neuroscience, Computational Intelligence and Neuroscience, Vol 2021 (2021)
- Publication Year :
- 2021
- Publisher :
- Hindawi Limited, 2021.
-
Abstract
- Today, the global exchange market has been the world’s largest trading market, whose volume could reach nearly 5.345 trillion US dollars, attracting a large number of investors. Based on the perspective of investors and investment institutions, this paper combines theory with practice and creatively puts forward an innovative model of double objective optimization measurement of exchange forecast analysis portfolio. To be more specific, this paper proposes two algorithms to predict the volatility of exchange, which are deep learning and NSGA-II-based dual-objective measurement optimization algorithms for the exchange investment portfolio. Compared with typical traditional exchange rate prediction algorithms, the deep learning model has more accurate results and the NSGA-II-based model further optimizes the selection of investment portfolios and finally gives investors a more reasonable investment portfolio plan. In summary, the proposal of this article can effectively help investors make better investments and decision-making in the exchange market.
- Subjects :
- Article Subject
General Computer Science
Computer science
General Mathematics
Computer applications to medicine. Medical informatics
R858-859.7
Neurosciences. Biological psychiatry. Neuropsychiatry
Deep Learning
Exchange rate
Econometrics
Investments
Optimization algorithm
business.industry
General Neuroscience
Deep learning
General Medicine
Investment (macroeconomics)
Investment portfolio
Prediction algorithms
Portfolio
Artificial intelligence
Volatility (finance)
business
Algorithms
RC321-571
Research Article
Subjects
Details
- ISSN :
- 16875273 and 16875265
- Volume :
- 2021
- Database :
- OpenAIRE
- Journal :
- Computational Intelligence and Neuroscience
- Accession number :
- edsair.doi.dedup.....933a45388269fd5add47acca1d654ff4