Skip to main content

Someone wanted to learn this too, so Grasp built them a personal learning path.

You can keep exploring this one or create a path like this one shaped around you.

Random Matrix Theory for Portfolio Optimization

10 Modules · 69 Lessons

Recommended resources

Module 2

Random Covariance Matrices and Spectral Statistics

Module 3

The Marchenko–Pastur Benchmark

Module 4

Resolvents and the Mathematics Behind the Limit Law

Module 5

Spiked Models, Market Modes, and Eigenvector Information

Module 6

Eigenvalue Cleaning with Random-Matrix Benchmarks

Module 7

Linear and Nonlinear Spectral Shrinkage

Module 8

Adapting RMT to Financial Return Data

Module 9

Portfolio Construction with Cleaned Risk Models

Module 10

Walk-Forward Evaluation and End-to-End Application