feat: macro series

backend/routers/eco.py

@@ -663,6 +663,10 @@ def series_history(
         ff_params: list = [series_id]
         if from_date:
             ff_where.append("event_date >= ?"); ff_params.append(from_date)
+        # Filter to the series' native currency to avoid mixing countries
+        ff_currency = meta.get("ff_currency")
+        if ff_currency:
+            ff_where.append("currency = ?"); ff_params.append(ff_currency)
 
         ff_rows = conn.execute(
             f"SELECT event_date, event_time, event_name, actual_value, "

backend/services/database.py

@@ -1228,6 +1228,16 @@ def init_db():
         except Exception:
             pass
 
+    # ── Migrations ────────────────────────────────────────────────────────────
+    # Re-assign ADP events that were incorrectly mapped to PAYEMS
+    try:
+        c.execute(
+            "UPDATE ff_calendar SET series_id = 'ADP_NFP' "
+            "WHERE series_id = 'PAYEMS' AND event_name LIKE 'ADP%'"
+        )
+    except Exception:
+        pass
+
     conn.commit()
     conn.close()
 

backend/services/fred_bootstrap.py

@@ -29,39 +29,56 @@ FRED_SERIES: Dict[str, Dict[str, Any]] = {
         "unit": "K",
         "freq": "monthly",
         "category": "employment",
+        "ff_currency": "USD",
         "higher_is_bullish": True,
         "assets": ["SPY", "QQQ", "EURUSD=X", "TLT"],
         "zscore_window": 12,
         "transform": None,
         "delta_absolute": False,
     },
+    "ADP_NFP": {
+        "name": "ADP Non-Farm Employment",
+        "unit": "K",
+        "freq": "monthly",
+        "category": "employment",
+        "ff_currency": "USD",
+        "higher_is_bullish": True,
+        "assets": ["SPY", "QQQ"],
+        "zscore_window": 12,
+        "transform": None,
+        "delta_absolute": False,
+        "ff_only": True,
+    },
     "UNRATE": {
         "name": "Unemployment Rate",
         "unit": "%",
         "freq": "monthly",
         "category": "employment",
+        "ff_currency": "USD",
         "higher_is_bullish": False,
         "assets": ["SPY", "QQQ", "EURUSD=X"],
         "zscore_window": 12,
         "transform": None,
-        "delta_absolute": True,   # pp change (e.g. 4.1 → 4.0 = -0.1 pp)
+        "delta_absolute": True,
     },
     "CPIAUCSL": {
         "name": "CPI All Items (YoY %)",
         "unit": "%",
         "freq": "monthly",
         "category": "inflation",
+        "ff_currency": "USD",
         "higher_is_bullish": False,
         "assets": ["TLT", "GLD", "EURUSD=X", "SPY"],
         "zscore_window": 12,
-        "transform": "yoy_pct",   # FRED gives index level → compute YoY
+        "transform": "yoy_pct",
-        "delta_absolute": True,   # pp change between consecutive YoY readings
+        "delta_absolute": True,
     },
     "CPILFESL": {
         "name": "Core CPI (YoY %)",
         "unit": "%",
         "freq": "monthly",
         "category": "inflation",
+        "ff_currency": "USD",
         "higher_is_bullish": False,
         "assets": ["TLT", "GLD", "EURUSD=X"],
         "zscore_window": 12,
@@ -73,6 +90,7 @@ FRED_SERIES: Dict[str, Dict[str, Any]] = {
         "unit": "%",
         "freq": "monthly",
         "category": "inflation",
+        "ff_currency": "USD",
         "higher_is_bullish": False,
         "assets": ["TLT", "GLD", "SPY"],
         "zscore_window": 12,
@@ -84,34 +102,36 @@ FRED_SERIES: Dict[str, Dict[str, Any]] = {
         "unit": "%",
         "freq": "monthly",
         "category": "monetary",
+        "ff_currency": "USD",
         "higher_is_bullish": False,
         "assets": ["TLT", "SPY", "EURUSD=X", "GLD"],
         "zscore_window": 12,
         "transform": None,
-        "delta_absolute": True,   # bp/pp move
+        "delta_absolute": True,
     },
     "ICSA": {
         "name": "Initial Jobless Claims",
         "unit": "K",
         "freq": "weekly",
         "category": "employment",
+        "ff_currency": "USD",
         "higher_is_bullish": False,
         "assets": ["SPY", "QQQ"],
         "zscore_window": 52,
-        "transform": "div1000",   # FRED gives raw count → display in K
+        "transform": "div1000",
         "delta_absolute": False,
     },
     "GDPC1": {
-        # Real GDP level in billions (chained 2017$) → compute QoQ annualized growth
         "name": "GDP Growth (QoQ Ann. %)",
         "unit": "%",
         "freq": "quarterly",
         "category": "growth",
+        "ff_currency": "USD",
         "higher_is_bullish": True,
         "assets": ["SPY", "QQQ", "EURUSD=X", "TLT"],
         "zscore_window": 8,
         "transform": "qoq_annualized",
-        "delta_absolute": True,   # pp change between quarterly readings
+        "delta_absolute": True,
     },
     "BAMLH0A0HYM2": {
         "name": "HY Credit Spread (OAS)",
@@ -122,7 +142,7 @@ FRED_SERIES: Dict[str, Dict[str, Any]] = {
         "assets": ["HYG", "LQD", "SPY"],
         "zscore_window": 52,
         "transform": None,
-        "delta_absolute": True,   # pp change in spread
+        "delta_absolute": True,
     },
     "T10Y2Y": {
         "name": "Yield Spread 10Y-2Y",
@@ -294,6 +314,9 @@ def bootstrap_fred(
         if not meta:
             logger.warning(f"[FRED bootstrap] Unknown series: {sid}")
             continue
+        if meta.get("ff_only"):
+            results[sid] = {"skipped": "ff_calendar only — no FRED fetch"}
+            continue
 
         # Warm-up period: extra years before from_date for transform + z-score
         transform = meta.get("transform")