Investment Algorithm based on the Psychological Expectation

Guanlin Li, Xinyu Chen, Yilin Zhang
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Abstract

As the economy grows, more and more people are profiting from investment products, such as gold, bitcoin, etc. Many people make decisions about their investment options by predicting the future price trend of investment products. We combine the prediction results with investors’ mental expectations to give a new model to help investors better decide their investment options. In this paper, we model portfolio of bitcoin and gold based on the price trend data of bitcoin and gold in the last five years. After predicting the trading price trend, we build a psychological expectation investment model to quantify the investors' psychological expectations and get an investment plan with both return and protection. And thus, we show that quantifying the change in investor psychology is a feasible and universal algorithm.
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基于心理预期的投资算法
随着经济的增长,越来越多的人从投资产品中获利,如黄金、比特币等。许多人通过预测投资产品的未来价格趋势来决定他们的投资选择。我们将预测结果与投资者的心理预期相结合,给出一个新的模型来帮助投资者更好地做出投资选择。本文基于比特币和黄金近5年的价格走势数据,建立了比特币和黄金的组合模型。在预测交易价格走势的基础上,建立心理预期投资模型,量化投资者的心理预期,得出既有回报又有保障的投资方案。因此,我们表明量化投资者心理的变化是一种可行的和通用的算法。
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