| # Figure Provenance |
|
|
| For each paper figure: which generation script, which input data sources, which experiment. |
|
|
| ## Figure 1 — `fig:multi_market_equity_curves` (Q1, main text) |
| |
| - **Source script:** `scripts/generate_cross_market_case_figures.py` → `plot_cross_market_equity()` |
| - **PDF:** `figures/case_cross_market_equity_curves.pdf` |
| - **Inputs:** equity_curve.csv from each of 10 runs in Experiment 1 (US 6M + CN 6M, 5 mandates each) |
| - **What it shows:** Daily normalized wealth path per mandate, two stacked panels (CN top, US bottom). |
| - **Last regenerated:** commit `579ed3d` (cash/exposure merge, 1×3 layout) |
| |
| ## Figure 2 — `fig:regime_robustness` (Q2, main text) |
|
|
| - **Source script:** `scripts/generate_cross_market_case_figures.py` → `plot_cross_market_shift()` |
| - **PDF:** `figures/case_cross_market_shift.pdf` |
| - **Inputs:** Aggregated `total_return` and `max_drawdown` from each of 10 runs in Experiment 1, via the multi-personality comparison bundles |
| - **What it shows:** Two-panel slopegraph (return / MDD) of CN-vs-US shift per mandate. |
| - **Last regenerated:** commit `579ed3d` |
|
|
| ## Figure 3 — `fig:behavior_profile` (Q3, main text) |
| |
| - **Source script:** `scripts/generate_cross_market_case_figures.py` → `plot_cross_market_behavior()` |
| - **PDF:** `figures/case_cross_market_behavior_shift.pdf` |
| - **Inputs:** `avg_turnover_ratio`, `avg_cash_ratio`, `avg_position_days` from each of 10 Experiment 1 runs, via comparison bundles |
| - **What it shows:** Three-panel slopegraph (turnover / cash ratio / holding days) of CN-vs-US shift per mandate. |
| - **Last regenerated:** commit `579ed3d` |
|
|
| > Note: gross exposure was an earlier fourth panel; it is the |
| > near-complement of cash ratio and was therefore removed to avoid |
| > redundancy. |
|
|
| ## Figure 4 — `fig:sector_style_matrix` (Q3, main text) |
|
|
| - **Source script:** `scripts/generate_sector_style_matrix_figure.py` → `render_market(US_PROFILE_RUNS, ...)` |
| - **PDF:** `figures/case_us_sector_style_matrix.pdf` |
| - **Inputs:** trades.csv from each of 5 US runs in Experiment 1 + universe CSV `universe/sector_style_universe.csv` |
| - **What it shows:** 5-panel heatmap of per-mandate trading concentration over the 5×4 US sector/style grid. |
| - **Critical fix:** Earlier this script used Experiment-4 (GPT-5.4 3M) run IDs, which made FV appear to "collapse" to a single Mid-Growth Financial. The current commit `a4bf9e6` rewires it to the Experiment-1 (6M case study) runs, where FV in fact spreads across 16 tickers. |
|
|
| ## Figure 5 — `fig:sector_style_matrix_cn` (Q3, appendix) |
| |
| - **Source script:** `scripts/generate_sector_style_matrix_figure.py` → `render_market(CN_PROFILE_RUNS, ...)` |
| - **PDF:** `figures/case_cn_sector_style_matrix.pdf` |
| - **Inputs:** trades.csv from each of 5 CN runs in Experiment 1 + universe CSV |
| - **What it shows:** Mirror of Figure 4 for the CN A-share universe. |
|
|
| ## Figure 6 — `fig:backend_robustness` (Q4, main text) |
| |
| - **Source script:** `scripts/generate_backend_robustness_figure.py` |
| - **PDF:** `figures/case_backend_robustness.pdf` |
| - **Inputs:** `derived/gpt54_robustness/backend_comparison.csv`, which aggregates the 5 GPT-5.4 runs (Experiment 4) and their default-backend counterparts (Experiment 3) |
| - **What it shows:** Per-mandate return and average cash ratio, default vs GPT-5.4 backend, on the matched US 3M window. |
|
|
| ## Figure 7 — `fig:paradigm_flow` (Section 2) |
| |
| - **Source:** Hand-drawn schematic (not generated from data) |
| - **PDF:** `figures/persona_benchmark_flow.pdf` |
| - **What it shows:** System flow diagram: fixed components on the left, doctrine module as the manipulated variable in the middle, mandate set and evaluation outputs on the right. |
| |
