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基于深度学习和 NSGA-II 模型的汇率预测。

Exchange Rate Forecasting Based on Deep Learning and NSGA-II Models.

机构信息

SILC Business School, Shanghai University, Shanghai 201800, China.

出版信息

Comput Intell Neurosci. 2021 Sep 22;2021:2993870. doi: 10.1155/2021/2993870. eCollection 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.

摘要

如今,全球外汇交易市场已成为全球最大的交易市场,其成交量可达近 5.345 万亿美元,吸引了大量投资者。本文从投资者和投资机构的角度出发,将理论与实践相结合,创新性地提出了外汇预测分析组合的双重目标优化测量的创新模型。具体来说,本文提出了两种算法来预测汇率的波动,即基于深度学习和 NSGA-II 的双重目标测量优化算法的外汇投资组合。与典型的传统汇率预测算法相比,深度学习模型的结果更加准确,基于 NSGA-II 的模型进一步优化了投资组合的选择,最终为投资者提供了更合理的投资组合计划。总之,本文的建议可以有效地帮助投资者在外汇市场做出更好的投资和决策。

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