Additional Experiments for the ICML2024 Submission: Autonomous Sparse Mean-CVaR Portfolio Optimization (ASMCVaR)

There are 3 folders. Please read the README.md file in each folder to find how to use the corresponding contents.

1. Codes_for_Experiments_in_Paper contains the Matlab codes of ASMCVaR for the experiments already in the paper.
2. Pytorch_Demo contains a Pytorch demonstration of our methodology.
3. Sparse_Relaxation_Test verifies that the proposed sparse relaxation is effective and our methodology can retrieve the ground-truth support set and achieve high accuracy to the global optimum.