摘要
针对我国黄金期货价格预测问题,对影响我国黄金期货价格的5项指标进行灰色关联度分析,得出我国黄金期货价格与美国黄金期货价格之间的关联度最高.建立反向传播(BP)神经网络模型对我国黄金期货价格预测,并与GM(1,1)方法和ARIMA(0,2,1)模型下的预测结果进行对比.结果显示:与后两个模型相比,BP神经网络模型在黄金期货价格预测方面的精确性更高,具有较好的实用价值.
For price prediction question of gold futures in China, five factors affecting the price volatility of gold futures were qualitatively analyzed by grey correlation analysis, and the result that the grey relational grade of gold futures prices between China and America is the highest was got. Then,the back propagation（BP）neural network model was established to predict the price of gold futures in China,and its prediction was compared with that from GM （1,1） and ARIMA （0,2, 1） models, The comparison shows that BP neural network model is more accurate in the prediction of gold futures price than the other two models,and it has a good practical value.
出处
《上海工程技术大学学报》
CAS
2017年第1期90-94,共5页
Journal of Shanghai University of Engineering Science
基金
国家级大学生创新创业训练计划资助项目(201610378400)
关键词
反向传播神经网络
黄金期货
价格预测
灰色关联分析
back propagation（BP）neural network
gold futures
price prediction
grey relational analysis
作者简介
宋策（1995-），男，在读本科生，研究方向为区域投资．E—mail：18895679175@163．com
