| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP17091 |
| 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 |
| URL | https://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. |
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