G2TT
来源类型Discussion paper
规范类型论文
来源IDDP17091
DP17091 High Dimensional Factor Models with an Application to Mutual Fund Characteristics
Martin Lettau
发表日期2022-03-07
出版年2022
语种英语
摘要This paper considers extensions of 2-dimensional factor models to higher-dimension data that can be represented as tensors. I describe decompositions of tensors that generalize the standard matrix singular value decomposition and principal component analysis to higher dimensions. I estimate the model using a 3-dimensional data set consisting of 25 characteristics of 1,342 mutual funds observed over 34 quarters. The tensor factor models reduce the data dimensionality by 97% while capturing 93% of the variation of the data. I relate higher-dimensional tensor models to standard 2-dimensional model and show that the components of the model have clear economic interpretations.
主题Financial Economics
关键词Tucker decomposition Cp decomposition Tensors Pca Svd Factor models Mutual funds Characteristics
URLhttps://cepr.org/publications/dp17091
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/546059
推荐引用方式
GB/T 7714
Martin Lettau. DP17091 High Dimensional Factor Models with an Application to Mutual Fund Characteristics. 2022.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Martin Lettau]的文章
百度学术
百度学术中相似的文章
[Martin Lettau]的文章
必应学术
必应学术中相似的文章
[Martin Lettau]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。