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.

中文翻译：

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基于深度学习和 NSGA-II 模型的汇率预测

如今，全球交易所市场已成为全球最大的交易市场，交易量可达近5.345万亿美元，吸引了大量投资者。本文基于投资者和投资机构的视角，将理论与实践相结合，创造性地提出了外汇预测分析组合双目标优化测度的创新模型。更具体地说，本文提出了两种预测交易所波动率的算法，即深度学习和基于 NSGA-II 的交易所投资组合双目标度量优化算法。与典型的传统汇率预测算法相比，深度学习模型结果更准确，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方案。综上所述，本文的提议可以有效帮助投资者在交易所市场进行更好的投资和决策。