Portfolio optimization and back-testing.
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Updated
May 8, 2024 - Python
Portfolio optimization and back-testing.
A Julia package for disciplined convex programming
A Python-embedded modeling language for convex optimization problems.
My github page
COSMO: Accelerated ADMM-based solver for convex conic optimisation problems (LP, QP, SOCP, SDP, ExpCP, PowCP). Automatic chordal decomposition of sparse semidefinite programs.
[WIP] ML-driven betting for UFC fights
Delve into gradient descent visualization, exemplifying its concepts with an example and its role in linear regression modeling
🫒 Ellipsoid Algorithm in Python
Volume Prediction Project for MS&E 349
Clarabel.jl: Interior-point solver for convex conic optimisation problems in Julia.
Clarabel.rs: Interior-point solver for convex conic optimisation problems in Rust.
Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
The Operator Splitting QP Solver
Python interface for SCS
Splitting Conic Solver
Scientific Computational Imaging COde
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
Utilities for Numerical Trajectory Optimization
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
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