基于深度学习的黄金价格预测

Dhanush N, Preeti R Prajapati, Revanth M, Revathi Ramesh, Ashwini Kodipalli, Roshan Joy Martis
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引用次数: 5

摘要

几个世纪以来,黄金一直是原始价值和交换媒介。根据之前的最后一次重新投入,印度2021年的黄金价格预测为6.03万卢比。通过预测黄金价格,投资者将知道何时买入或卖出这种商品。黄金价格与该国货币直接挂钩,因此影响到股票价格。可以看出,股价下跌会带动金价上涨。本文主要研究了长短期记忆的早期预测模型及其方差。将该模型与广泛使用的线性回归算法进行了比较。观察到线性回归、香草和堆叠LSTM的平均绝对百分比误差(MAPE)值分别为10.94、2.649和2.5009。从MAPE的值可以看出,LSTM比线性回归表现更好。因此,对黄金价格的早期预测有助于投资者以最好的价格投资或出售黄金。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Gold Price using Deep Learning
Gold has been the original value and medium of exchange from many centuries. Gold price prediction in India in 2021 according to the last previous rededication is Rs 60,300. By predicting gold price investors will have an idea about when to buy or sell the commodity. Gold price is directly linked to the country's currency and hence affects the stock price. It is seen that the decrease in stock price increases the gold price. This paper is mainly aiming on the early prediction model using Long Short Term Memory (LSTM) and its variance. The proposed model is compared with the widely used linear regression algorithm. It is observed that the Mean Absolute Percentage Error (MAPE) value of Linear Regression, Vanilla, and Stacked LSTM is 10.94, 2.649, and 2.5009 respectively. From the values of MAPE it is observed that LSTM has outperformed compared to Linear regression. Hence early prediction of gold price helps investors to invest or sell the gold at the best possible price.
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