Prioritize dashboard refresh before daily model tuning

Author: HanSun103

README.md

@@ -258,13 +258,15 @@ boundary, static-site publication, validation gate, and one-time repository conf
 
 The daily command first refreshes the latest prior Ridge and XGBoost portfolios against the
 completed session. Yahoo's final hourly bar begins at 15:30, so the command requires that bar and
-retries five times at 60-second intervals if it is not available yet. It then requires an official
-daily price row for the decision date, independently tunes and refits Ridge and XGBoost, saves both
-new top-40 portfolios, writes `selection_stability_YYYY-MM-DD.json`, and rebuilds the shared
-dashboard. The stability report tracks same-day model overlap, day-over-day retention, top-10
-persistence, rank correlation, entrants/exits, implied replacement, and multi-day consensus names.
-This ordering prevents a successful model retrain from leaving the performance chart stuck at an
-earlier intraday bar.
+retries five times at 60-second intervals if it is not available yet. It evaluates the frozen
+portfolios and refreshes both dashboard outputs before the longer tuning stage begins. It then
+requires an official daily price row for the decision date, independently tunes and refits Ridge
+and XGBoost, saves both new top-40 portfolios, writes
+`selection_stability_YYYY-MM-DD.json`, and refreshes both dashboards again. The stability report
+tracks same-day model overlap, day-over-day retention, top-10 persistence, rank correlation,
+entrants/exits, implied replacement, and multi-day consensus names. This ordering makes the
+completed-session result available promptly and prevents a model retrain from leaving the
+performance chart stuck at an earlier intraday bar.
 
 The July 20, 2026 production-style run requested 25 Optuna trials with a 600-second timeout. Ten
 trials completed, using three 42-session validation folds separated from training by a one-session

docs/LIVE_FORWARD_MONITOR.md

@@ -18,17 +18,17 @@ python -m src.cli run-live-forward-daily --as-of YYYY-MM-DD
 
 The command performs these steps in order:
 
-1. Incrementally refreshes market data and evaluates portfolios frozen before the current session,
-   including one holding-level return record per selected stock.
-2. Waits for the final 15:30 hourly bar and verifies the official daily close is available.
-3. Rebuilds price features through the decision date.
-4. Builds forward-return training labels only where the future outcome was already known before the
+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 and rebuilds price features through the decision date.
+5. Builds forward-return training labels only where the future outcome was already known before the
    decision date.
-5. Tunes Ridge and XGBoost independently on temporal validation data, refits the selected
+6. Tunes Ridge and XGBoost independently on temporal validation data, refits the selected
    configurations, and freezes both top-40 lists for the next evaluation session.
-6. Writes model-agreement and day-over-day selection-stability diagnostics.
-7. Rebuilds `reports/live_forward/dashboard.html`.
-8. Publishes and validates the sanitized static bundle under `site/` for GitHub Pages.
+7. Writes model-agreement and day-over-day selection-stability diagnostics.
+8. 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.

site/data/dashboard.json

@@ -1,10 +1,10 @@
 {
   "schema_version": 1,
-  "generated_at_utc": "2026-07-23T20:15:48.055630+00:00",
-  "latest_decision_date": "2026-07-22",
-  "snapshot_count": 7,
+  "generated_at_utc": "2026-07-23T21:19:53.915157+00:00",
+  "latest_decision_date": "2026-07-23",
+  "snapshot_count": 9,
   "evaluation_count": 7,
-  "dashboard_sha256": "6f483ca0e1b74cd15f32937ab633ee07000515295346e474b295cd2817bf2b9a",
-  "dashboard_bytes": 136241,
+  "dashboard_sha256": "7452a2fc9de30ea073ee22aeaf1faf8869dc4d8f5c182bb278fd6535397a75cb",
+  "dashboard_bytes": 152971,
   "source_policy": "sanitized_live_forward_outputs_only"
 }

site/data/manifest.json

@@ -1446,6 +1446,8 @@ def run_live_forward_daily_command(
         )
         for snapshot in prior
     ]
+    pretraining_dashboard = build_live_dashboard(root)
+    pretraining_public_site = publish_live_dashboard(root, public_site_dir)
 
     cfg = load_config("configs/base.yaml", "configs/data.yaml")
     common = {
@@ -1486,6 +1488,8 @@ def run_live_forward_daily_command(
         "refreshed_prior_snapshots": [str(path) for path in prior],
         "close_reports": close_reports,
         "close_evaluations": close_evaluations,
+        "pretraining_dashboard": pretraining_dashboard["dashboard"],
+        "pretraining_public_site": pretraining_public_site["output_dir"],
         "ridge_output": ridge["output"],
         "xgb_output": xgb["output"],
         "selection_stability": stability["output"],