Regression and Hidden Markov Models for Gold Price Prediction

被引：0

作者：

Shen, Li ^{[1
]}

Shen, Kun ^{[1
]}

Yi, Chao ^{[1
]}

Chen, Yixin ^{[1
]}

机构：

[1] China Asset Management Co Ltd, Beijing 100033, Peoples R China

来源：

2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2020年

关键词：

gold; prediction; HMM; OLS; ARIMA;

D O I：

10.1109/BigData50022.2020.9378468

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the long run, gold price is positively related to inflation rates because gold is a perfect asset to hedge against inflation. In the short run, gold price fluctuates a lot. Many factors can cause gold price volatility, such as economic and political uncertainties, exchange rates, interest rates and so on. Here we try several models to predict monthly gold prices, including linear regression model and ARIMA model. We also try to predict monthly gold returns with hidden Markov model. It turns out that HMM is much better.

引用

页码：5451 / 5456

页数：6

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