Economics

This repository provides a reproducible implementation of a duality-informed convex equilibrium allocation theory. It features a robust solver that finds portfolio weights by minimizing a convex objective that combines risk, return, and distributional robustness, while enforcing simplex constraints.

This module provides a production-ready implementation for a CVaR-Adjusted Update to portfolio weights. The method explicitly penalizes tail risk by down-weighting assets with larger Conditional Value-at-Risk (CVaR), making allocations more robust to extreme downside events.

This module provides a production-ready implementation of a portfolio weight adjustment mechanism inspired by reinforcement learning. It updates weights using a simple multiplicative rule based on a reward signal, ensuring the portfolio remains valid and normalized.

A production-ready implementation of an Entropy Regularization Module. This module encourages portfolio diversification and robustness by penalizing concentrated allocations, using an entropy term and an exponentiated-gradient update.

This module provides a production-ready implementation of an autocorrelation penalty for portfolio updates. The method detects serial correlation in a signal using a Ljung-Box test and applies a shrinkage penalty to reduce exposure when strong autocorrelation is present.

A production-ready implementation of a Wasserstein Distributionally Robust Optimization (DRO) penalty for portfolio updates. This module hedges against distribution shift by penalizing the divergence between historical mean returns and a stressed or perturbed mean.