Financially Guided Deep Portfolio Optimization
This work proposes an end-to-end framework that directly optimizes differentiable surrogates of key financial metrics (Sharpe ratio, Omega ratio, Conditional Value-at-Risk, and risk parity), allowing neural networks to learn portfolio weights via backpropagation, outperforming the equal-weight portfolio, S&P 500, and t...
Rahul Fernandes, Travis J. Desell
· IEEE Conference on Computati... · 0 citations