Integrate frozen-cohort dashboard monitoring

.github/workflows/deploy-dashboard.yml

@@ -8,6 +8,13 @@ on:
       - "site/**"
       - "src/experiments/public_dashboard_validation.py"
       - ".github/workflows/deploy-dashboard.yml"
+  pull_request:
+    branches:
+      - main
+    paths:
+      - "site/**"
+      - "src/experiments/public_dashboard_validation.py"
+      - ".github/workflows/deploy-dashboard.yml"
   workflow_dispatch:
 
 permissions:
@@ -23,27 +30,28 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Check out repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v7
 
       - name: Set up Python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v7
         with:
           python-version: "3.12"
 
       - name: Validate sanitized public bundle
         run: python -m src.experiments.public_dashboard_validation --site-dir site
 
       - name: Configure GitHub Pages
-        uses: actions/configure-pages@v5
+        uses: actions/configure-pages@v6
 
       - name: Upload dashboard artifact
-        uses: actions/upload-pages-artifact@v4
+        uses: actions/upload-pages-artifact@v5
         with:
           path: site
 
   deploy:
     name: Deploy dashboard
     needs: validate
+    if: github.ref == 'refs/heads/main'
     runs-on: ubuntu-latest
     permissions:
       pages: write
@@ -54,4 +62,4 @@ jobs:
     steps:
       - name: Deploy to GitHub Pages
         id: deployment
-        uses: actions/deploy-pages@v4
+        uses: actions/deploy-pages@v5

README.md

@@ -5,7 +5,7 @@
 
 ![Python 3.11+](https://img.shields.io/badge/Python-3.11%2B-2563eb)
 ![Research status](https://img.shields.io/badge/status-paper--live_research-d97706)
-![Tests](https://img.shields.io/badge/tests-215_passing-0f766e)
+![Tests](https://img.shields.io/badge/tests-218_passing-0f766e)
 ![License](https://img.shields.io/badge/license-MIT-64748b)
 
 The project asks a narrow investment question:
@@ -209,6 +209,31 @@ before forward use. The six observed sessions will not choose the threshold.
 
 [Review the rebalance-buffer experiment draft →](docs/design/REBALANCE_BUFFER_EXPERIMENT.md)
 
+### Frozen-cohort dashboard
+
+The legacy one-session experiment is now a frozen-cohort monitoring track rather
+than a source of new daily portfolios. Its daily command refreshes prices,
+extends the existing July 20–27 Ridge/XGBoost cohorts, rebuilds the local
+dashboard, and regenerates the sanitized GitHub Pages bundle:
+
+```bash
+python -m src.cli run-live-forward-daily --as-of YYYY-MM-DD
+```
+
+The **Holding-period laboratory** can keep any dated list unchanged or compare
+custom 1–60-session replacement horizons, including 5/10/20-session presets.
+Ridge and XGBoost can be toggled independently while SPY remains permanently
+visible from the shared decision-close baseline. It reports net return,
+SPY-relative return, replacement-only turnover, and rebalance counts under
+identical execution assumptions.
+
+[Open the deployed live-forward dashboard →](https://hansun103.github.io/AI-Driven-Portfolio-Optimization-Backtesting-System/)
+
+This monitoring track does not replace the primary horizon-matched 5/10/20
+experiment described above. The former one-session fitting workflow remains
+available only through the explicit `--retrain` flag and is not part of the
+normal monitoring run.
+
 ## Architecture
 
 The historical system contained many experimental sleeves. Its full architecture

docs/GITHUB_PAGES_DEPLOYMENT.md

@@ -9,10 +9,10 @@ Yahoo Finance and cached inputs
              |
              v
 Daily live-forward pipeline
-  - evaluate prior frozen portfolios
-  - tune and refit Ridge and XGBoost
-  - freeze tomorrow's top-40 lists
-  - calculate stability diagnostics
+  - refresh official closes for archived cohorts
+  - extend frozen Ridge and XGBoost portfolios
+  - replay 1-60-session replacement policies
+  - calculate returns, costs, and turnover
              |
              +--> reports/live_forward/   private, ignored research evidence
              |
@@ -25,10 +25,13 @@ Daily live-forward pipeline
                   GitHub Actions / Pages
 ```
 
-`reports/live_forward/` remains the full local evidence store. The publisher uses explicit field
-allowlists to create `site/data/dashboard.json`; it does not copy local paths, cached input names,
-raw feature rows, model files, credentials, or candidate-trial details. The public bundle is then
-validated for required files, duplicate holdings, forbidden private strings, and a SHA-256 digest.
+`reports/live_forward/` remains the full local evidence store. The publisher uses
+separate explicit field allowlists for model snapshots and frozen-cohort policy
+paths when it creates `site/data/dashboard.json`; it does not copy local paths,
+cached input names, raw price/feature rows, model files, credentials, or
+candidate-trial details. The public bundle is then validated for required files,
+snapshot and cohort schemas, duplicate identifiers or holdings, forbidden
+private strings, and a SHA-256 digest.
 
 ## Daily publication
 
@@ -38,6 +41,16 @@ The standard daily command now refreshes both the local dashboard and the public
 python -m src.cli run-live-forward-daily --as-of YYYY-MM-DD
 ```
 
+This command is monitoring-only by default and reports
+`"new_model_lists": 0`. It rebuilds:
+
+- `reports/live_forward/cohort_monitor.json`;
+- `reports/live_forward/dashboard.html`; and
+- the tracked `site/` deployment bundle.
+
+The historical one-session retraining path requires the explicit `--retrain`
+flag. It should not be used during the frozen-cohort policy experiment.
+
 To rebuild the public bundle without retraining:
 
 ```bash
@@ -52,9 +65,11 @@ Validate exactly what will be published:
 python -m src.cli validate-live-dashboard-site --site-dir site
 ```
 
-Commit `site/` after reviewing the generated changes. A push to `main` that changes the public
-bundle starts `.github/workflows/deploy-dashboard.yml`. The workflow validates the bundle again,
-uploads it as a Pages artifact, and deploys it to the `github-pages` environment.
+Commit `site/` after reviewing the generated changes. A pull request that
+changes the public bundle runs the validation and packaging job without
+deploying. After merge, the resulting push to `main` runs the same validation,
+uploads the Pages artifact, and deploys it to the `github-pages` environment.
+The deploy job is explicitly restricted to `refs/heads/main`.
 
 ## One-time repository setting
 

docs/LIVE_FORWARD_MONITOR.md

@@ -14,53 +14,57 @@ yet a production trading recommendation. Ridge is the stable linear benchmark an
 ranker is the nonlinear challenger. Both select 40 equal-weight names and share SPY as the market
 benchmark.
 
-## Daily after-close workflow
+## Daily after-close workflow: monitoring phase
 
-Run the production-style workflow after Yahoo Finance publishes the final regular-session bar:
+This dashboard track preserves the legacy one-session selections for the
+rebalancing-policy study; it is separate from the primary horizon-matched
+5/10/20-session live-forward experiment. The July 20–27 Ridge and XGBoost
+selections are frozen as permanent cohorts. After Yahoo Finance publishes the
+official daily close, run:
 
 ```bash
 python -m src.cli run-live-forward-daily --as-of YYYY-MM-DD
 ```
 
-The command performs these steps in order:
-
-1. Waits for the final 15:30 hourly bar and verifies the official daily close is available.
-2. Evaluates portfolios frozen before the current session, including one holding-level return
-   record per selected stock.
-3. Immediately rebuilds the local dashboard and sanitized `site/` bundle before model tuning starts.
-4. Incrementally refreshes daily market data, split events, and trailing sector-ETF classifications
-   through the decision date.
-5. Expands sector observations backward-as-of so each historical feature and label uses only the
-   classification available on that date.
-6. Builds forward-return training labels only where the future outcome was already known before the
-   decision date.
-7. Tunes Ridge and XGBoost independently on temporal validation data, refits the selected
-   configurations, and freezes both top-40 lists for the next evaluation session.
-8. Freezes a separate shadow portfolio by blending the two full-universe percentile rankings
-   with the historically selected 25% Ridge / 75% XGBoost weight and applying the same top-40
-   sector cap.
-9. Writes model-agreement, day-over-day selection-stability diagnostics, and candidate split
-   features that are not yet eligible for model fitting.
-10. Rebuilds both dashboard outputs again so they include the newly frozen pending portfolios.
-
-If final market data is unavailable, the command retries and then fails closed. It must not create a
-snapshot from a partial trading day.
-
-## Tuning profiles
-
-Use a full focused retune after changing a feature definition, repairing historical inputs, or as
-a periodic model audit:
+Monitoring-only is the default. The command:
+
+1. requests adjusted daily prices only for SPY and securities present in the archived cohorts;
+2. verifies the requested official close exists and fails closed if Yahoo still has partial data;
+3. extends every unchanged July 20–27 portfolio through the new close;
+4. replays archived rebalance policies for every interval from 1 through 60 sessions;
+5. recalculates net return, SPY-relative return, cumulative turnover, and trades; and
+6. rebuilds the local dashboard and sanitized GitHub Pages bundle.
+
+It does **not** fit a model or create a new stock list. The output explicitly reports
+`"new_model_lists": 0`.
+
+The dashboard's **Holding-period laboratory** supports selecting any July 20–27 list, displaying
+Ridge and XGBoost together with clickable model chips, or replaying a 1–60-session rebalance
+interval. Five-, 10-, and 20-session presets are provided, and the horizon comparison table reports
+every 1–20-session candidate side by side. SPY is permanent and begins from the same zero-return
+decision-close baseline as each portfolio.
+
+The displayed **replacement turnover** excludes the unavoidable initial purchase. An unchanged
+cohort therefore correctly shows 0% replacement turnover. Scheduled policies use the same
+$1 million capital, 8 bps one-way cost, $10 fixed trade fee, and 0.25% minimum trade-weight rule.
+
+## Explicit archived retraining workflow
+
+The old production-style retraining path remains available for reproducibility, but now requires
+the explicit `--retrain` flag:
 
 ```bash
 python -m src.cli run-live-forward-daily \
   --as-of YYYY-MM-DD \
+  --retrain \
   --tuning-folds 5 \
   --ridge-optuna-trials 60 \
   --xgb-optuna-trials 50 \
   --optuna-timeout-seconds 7200
 ```
 
-The focused parameter ranges come from earlier completed live runs. The current decision date and
+Do not use this flag during the frozen-cohort monitoring phase. The focused parameter ranges come
+from earlier completed live runs. The current decision date and
 its future return remain excluded, so narrowing the search does not introduce look-ahead leakage.
 Five purged temporal folds provide a more stable selection estimate, while the separate Ridge and
 XGBoost trial budgets reflect their very different fitting costs.