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Machine Learning with Nonstationary Data

作者: 发布时间:2024-09-03 点击数:
主讲人:奚晋
主讲人简介:

奚晋,中国科学院数学与系统科学研究院预测科学研究中心助理研究员。本科就读于北卡罗莱纳大学教堂山分校,获得经济学与数学双学位。2024年于加州大学圣地亚哥分校获得经济学博士学位。她的研究领域是计量经济学,主要涉及的研究领域包括机器学习的预测方法、高维非平稳时间序列、因子模型、政策学习、以及机制设计。

主持人:洪永淼
讲座简介:

Machine learning offers a promising set of tools for forecasting. However, some of the well-known properties do not apply to nonstationary data. I propose a simple procedure to extend machine learning methods to nonstationary data that does not require the researcher to have prior knowledge of which variables are non-stationary or the nature of the nonstationarity. I illustrate theoretically that using this procedure with LASSO or adaptive LASSO generates consistent variable selection on a mix of stationary and nonstationary explanatory variables. In a related paper, this approach was also shown to result in consistent estimation of principal components with the presence of nonstationarity. In an empirical exercise, I examine the success of this approach at forecasting U.S. inflation rates and the industrial production index using a number of different machine learning methods. I find that the proposed method either significantly improves prediction accuracy over traditional practices or delivers comparable performance, making it a reliable choice for obtaining stationary components of high-dimensional data. Another application to the FRED-MD macroeconomic dataset demonstrates that the approach offers similar benefits to those of traditional principal component analysis with some added advantages.

时间:2024-09-10 (Tuesday) 16:30-18:00
地点:厦大经济楼N302、中国科学院数学与系统科学研究院南楼N204、腾讯会议 ID:796 451 039
讲座语言:中文
主办单位:永利集团3044官网欢迎您邹至庄经济研究院、永利集团3044官网欢迎您-中国科学院计量建模与经济政策研究基础科学中心、中国科学院数学与系统科学研究院预测科学研究中心、中国科学院大学经济与管理学院
承办单位:
期数:“邹至庄讲座”青年学者论坛(第67期)
联系人信息:许老师,电话:2182991,邮箱:ysxu@xmu.edu.cn
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