说明:In the p dimensional space formed by p asset returns, PCA finds the most important k directions that capture the most important variations in the given returns of p assets. Usually, k is less than p. Therefore, by using PCA you can decompose the p as <qq_18822147> 在 上传 | 大小:4194304
说明:In the p dimensional space formed by p asset returns, PCA finds the most important k directions that capture the most important variations in the given returns of p assets. Usually, k is less than p. Therefore, by using PCA you can decompose the p as <qq_18822147> 在 上传 | 大小:450560
说明:In the p dimensional space formed by p asset returns, PCA finds the most important k directions that capture the most important variations in the given returns of p assets. Usually, k is less than p. Therefore, by using PCA you can decompose the p as <qq_18822147> 在 上传 | 大小:480256
说明:In the p dimensional space formed by p asset returns, PCA finds the most important k directions that capture the most important variations in the given returns of p assets. Usually, k is less than p. Therefore, by using PCA you can decompose the p as <qq_18822147> 在 上传 | 大小:2097152