我国黄金期货价格波动率预测研究:来自模型缩减方法的新证据  

Forecasting Volatility of China Gold Futures Price:New Evidence from Model Shrinkage Methods

作　　者：梁超 魏宇 马锋[1] 李霞飞 LIANG Chao;WEI Yu;MA Feng;LI Xia-fei(School of Economics and Management,Southwest Jiaotong University,Chengdu 610031,China;School of Finance,Yunnan University of Finance and Economics,Kunming 650221,China)

机构地区：[1]西南交通大学经济管理学院,四川成都610031 [2]云南财经大学金融学院,云南昆明650221

出　　处：《中国管理科学》2022年第4期30-41,共12页Chinese Journal of Management Science

基　　金：国家自然科学基金资助项目(71671145、71971191、71701170);云南省高校科技创新团队项目(2019014);云南省科技计划基础研究重点项目(202001AS070018)。

摘　　要：黄金作为重要的避险资产,对其价格波动的定量描述和预测对于各类投资者的风险管理决策意义重大。基于标准回归预测模型,采用主成分分析、组合预测和两种主流的模型缩减方法(Elastic net和Lasso)构建新的波动率预测模型,探究哪种方法能够更有效地利用多个预测因子信息。进一步,运用模型信度集合(model confidence set,MCS)、样本外R;和方向测试(Direction-of-Change,DoC)三种评价方法检验新模型的样本外预测精度。实证结果显示:不论是基于哪一种评价方法,相比其它竞争模型,两种缩减模型的样本外预测精度均为最优,可以为我国黄金期货价格的波动率预测提供可靠保障。As an important safe-haven asset,the quantitative description and prediction of the price volatility of gold is of great significance to the risk management decisions for various investors.Based on the standard regression model,principal component analysis,combination forecast,and two model shrinkage methods(i.e.,Elastic net and Lasso)are employed to design new volatility prediction models and investigate which method can more effectively use the information of multiple predictors.In addition,the model confidence set(MCS),out-of-sample R~2,Direction-of-change(DoC)evaluation methods are used to assess the out-of-sample prediction accuracy of the new models.The empirical results show that no matter which evaluation method is used,compared with other competition models,the out-of-sample prediction accuracy of the two shrinkage models is the best,which can provide a reliable guarantee for the volatility forecast of China’s gold futures prices.

关 键 词：已实现波动率 高频数据 组合预测 机器学习 Elastic net Lasso 

分 类 号：F830[经济管理—金融学]