fix: use actual invested amounts for avg_price in seed data

The seed script was incorrectly using the latest snapshot's market price
as avg_price, resulting in inflated average costs. Now computes avg_price
from actual total invested amounts per ticker.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/scripts/seed_data.py

@@ -42,6 +42,15 @@ TARGETS = {
     "411060": Decimal("15"),
 }
 
+# Actual total invested amounts per ticker (from brokerage records)
+TOTAL_INVESTED = {
+    "069500": Decimal("541040"),
+    "148070": Decimal("15432133"),
+    "284430": Decimal("18375975"),
+    "360750": Decimal("7683515"),
+    "411060": Decimal("6829620"),
+}
+
 # Historical snapshots from data.txt
 SNAPSHOTS = [
     {
@@ -242,13 +251,18 @@ def seed(db: Session):
     print(f"Created {tx_count} transactions from snapshot diffs")
 
     # Set current holdings from latest snapshot
+    # avg_price = total invested amount / quantity (from actual brokerage records)
     latest = SNAPSHOTS[-1]
     for h in latest["holdings"]:
+        ticker = h["ticker"]
+        qty = h["qty"]
+        invested = TOTAL_INVESTED[ticker]
+        avg_price = (invested / qty).quantize(Decimal("0.01"))
         db.add(Holding(
             portfolio_id=portfolio.id,
-            ticker=h["ticker"],
-            quantity=h["qty"],
-            avg_price=h["price"],  # Using current price as avg (best available)
+            ticker=ticker,
+            quantity=qty,
+            avg_price=avg_price,
         ))
     print(f"Set {len(latest['holdings'])} current holdings from {latest['date']}")