A Regression-Based Interpretation of the Inverse of the Sample Covariance Matrix
The usefulness of covariance and correlation matrices is well-known in various academic fields. Matrix inversion, if required in an analytical setting, tends to mask the intuition in interpreting the corresponding empirical or experimental results. Drawing on the finance literature in mean-variance...
Main Author: | Clarence C. Y. Kwan |
---|---|
Format: | Article |
Language: | English |
Published: |
McMaster University
|
Series: | Spreadsheets in Education |
Online Access: | http://sie.scholasticahq.com/article/4613-a-regression-based-interpretation-of-the-inverse-of-the-sample-covariance-matrix.pdf |
Similar Items
-
An Introduction to Shrinkage Estimation of the Covariance Matrix: A Pedagogic Illustration
by: Clarence C. Y. Kwan -
The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
by: Clarence C. Y. Kwan
Published: (2010-07-01) -
The Requirement of a Positive Definite Covariance Matrix of Security Returns for Mean-Variance Portfolio Analysis: A Pedagogic Illustration
by: Clarence C. Y. Kwan -
Wiener Filter Approximations Without Covariance Matrix Inversion
by: Pranav U. Damale, et al.
Published: (2023-01-01) -
The Performance Analysis Based on SAR Sample Covariance Matrix
by: Esra Erten
Published: (2012-03-01)