Clarify daily return units and add GPU-vs-CPU composition comparison in mean_variance_basic#54
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jgoldberg-nvidia wants to merge 2 commits into
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Clarify daily return units and add GPU-vs-CPU composition comparison in mean_variance_basic#54jgoldberg-nvidia wants to merge 2 commits into
jgoldberg-nvidia wants to merge 2 commits into
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…_variance_basic Answers recurring user questions about the notebook's "Expected Return: 0.2914%" figure and how to compare solver results: - Add a units note: all returns are 1-day LOG returns, so every reported statistic is daily, not annualized (0.29%/day ~ 73% annualized log return ~ 108% annualized simple return, in-sample). - Label the portfolio statistics as daily and add an annualized block (x252 log return, exp conversion to simple, sqrt(252) volatility/Sharpe). - Add a portfolio-composition comparison cell (direct cuOpt vs CVXPY-cuOpt vs CLARABEL side by side with per-weight diffs) alongside the existing compare_results metrics comparison. - Rename the CVXPY-API solve results to cvxpy_gpu_* so the direct cuOpt solve no longer silently shadows them. - Re-executed end-to-end on GPU (cuOpt 26.06): all solvers agree at 0.2914%/day expected return with max GPU-vs-CPU weight difference of 5.9e-06. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Addresses user questions about
mean_variance_basic.ipynb(why "Expected Return: 0.2914%", and how to compare CPU vs GPU portfolios):compare_results.cvxpy_gpu_*so the direct cuOpt solve no longer overwrites them.tests/test_skill.py,ci/utils/validate_skills.sh) and full CPU suite pass.🤖 Generated with Claude Code