Optimizer

Mean-CVaR portfolio optimization with NORTA copula simulation and kernel regression

Optimization Parameters

Configure the Mean-CVaR solver and kernel regression

Ready

Alpha (CVaR Confidence)90%

Confidence level for tail risk measurement. Higher = more conservative.

Gamma (Risk Budget)0.07

Maximum acceptable CVaR loss. Lower = tighter risk constraint.

Bandwidth (Kernel)0.5

Nadaraya-Watson kernel bandwidth. Lower = more local weighting.

Configure parameters and click Run Optimization to analyze your portfolio

25 assets · 1,000 Monte Carlo scenarios · Mean-CVaR solver