基于RNN的黄金投资模型及PSO的最佳投资策略研究

Pakamas Kanchanakantikul, S. Nootyaskool
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引用次数: 0

摘要

目前,算法交易在社区和股票中是一个有趣的研究,而黄金也是一种投资选择。本研究分为两个步骤。三个输入序列包括黄金价格(卖出)、黄金现货和原油。输出有一个指示买入、卖出和等待信号的订单序列。首先,与随机搜索方法相比,采用粒子群算法从历史数据中寻找最佳策略;其次,利用递归神经网络(RNN)模型创建黄金投资。实验结果表明,基于粒子群的RNN交易模型优于RS交易模型,收益率为79.667%。
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Gold Investment Model on RNN and Finding Best Investment Strategy on PSO
Nowadays, Algorithm trading in community and stock is interesting research, while gold is also an investment option. This research presents two steps. Three inputs sequence consists of the gold price(sell), gold spot and crude oil. Output has an order sequence indicating buy, sell, and wait for the signal. Firstly, finding the best strategy from historical data by particle swarm optimization (PSO) compared with random search (RS). That will get buying, selling, or waiting signals in the gold trading market Secondly, creating gold investment by recurrent neural network (RNN) model. The experiment result showed RNN trading model based on PSO is better than RS, which has a profit of 79.667 percent.
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