标题:
基于数据挖掘模型的锌期货价格预测模型Zinc Futures Price Forecasting Model Based on Data Mining Model
作者:
田永忠
关键字:
锌期货, 数据挖掘模型, 随机森林Zinc Futures, Data Mining Model, Random Forest
期刊名称:
《Statistics and Application》, Vol.5 No.3, 2016-09-20
摘要:
对期货市场的价格进行合理地预测，可以规避风险，获得收益。本文利用支持向量机(SVM)回归、决策树(RPART)回归、Bagging回归、Boosting回归、随机森林(Random forest)回归五种数据挖掘模型对锌期货的价格进行预测，预测结果良好，对一个月后锌期货价格变动方向的准确率在60%以上。
Predicting futures market price reasonably can avoid risks and get benefit. In this paper, we used five kinds of data mining models—support vector machine (SVM) regression, decision trees re-gression, bagging regression, boosting regression, random forests regression—to predict zinc fu-tures price. It has got good results, whose accuracy rate can reach above 60% for predicting zinc futures price change direction within one month.