feat: enrich daily bar schema with valuation/status fields + VWAP

Batch download now pulls baostock's preclose, turn, pctChg, tradestatus,
isST, and peTTM/pbMRQ/psTTM/pcfNcfTTM on top of OHLCV+amount, plus a
derived daily VWAP (amount/volume). VWAP is raw-price scale and not
comparable with adjusted OHLC under qfq/hfq — documented in the schema.

Richer fields live only in the batch path (download_daily_batch ->
download_universe); single-symbol download_daily keeps the legacy
8-column schema that test_downloader.py pins. Also flags intraday/L1-L2
microstructure data as a future phase in the README roadmap.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

CLAUDE.md

@@ -42,7 +42,7 @@ An **alpha** is a signed cross-sectional **position weight**: positive = long, n
 ## Parquet schema contracts
 
 `pipeline/common/schema.py` defines the column contracts that are the *only* interface between phases. Any new phase or alpha must conform:
-- `DATA_COLUMNS` (data output): `symbol_id, symbol_name, date, open, high, low, close, volume, amount`
+- `DATA_COLUMNS` (data output): `symbol_id, symbol_name, date, open, high, low, close, preclose, volume, amount, vwap, turn, pctChg, tradestatus, isST, peTTM, pbMRQ, psTTM, pcfNcfTTM` (`vwap` = `amount/volume` is a raw-price daily VWAP, *not* on the adjusted OHLC scale under qfq/hfq). The richer fields are fetched only by the **batch** path (`download_daily_batch` → `download_universe`); single-symbol `download_daily` keeps the legacy 8-column schema that `tests/test_downloader.py` pins.
 - `ALPHA_COLUMNS` (alpha output): `symbol_id, date, alpha_name, weight`
 - `COMBO_COLUMNS` (combo output): `symbol_id, date, combo_name, weight`
 

README.md

@@ -224,7 +224,11 @@ supplies it and the unrelated `--lookback`/`--vol-window` defaults are ignored.
 The column contracts in `pipeline/common/schema.py` are the only interface
 between phases (data is stored long/tidy):
 
-- **data** (`DATA_COLUMNS`): `symbol_id, symbol_name, date, open, high, low, close, volume, amount`
+- **data** (`DATA_COLUMNS`): `symbol_id, symbol_name, date, open, high, low, close, preclose, volume, amount, vwap, turn, pctChg, tradestatus, isST, peTTM, pbMRQ, psTTM, pcfNcfTTM`
+  (`vwap` = `amount / volume` — a **raw**-price daily VWAP, *not* on the adjusted
+  OHLC scale under `qfq`/`hfq`; `turn` is turnover %, `pctChg` daily % change,
+  `tradestatus`/`isST` are 0/1 flags, and `peTTM`/`pbMRQ`/`psTTM`/`pcfNcfTTM` are
+  baostock valuation ratios.)
 - **alpha** (`ALPHA_COLUMNS`): `symbol_id, date, alpha_name, weight`
 - **combo** (`COMBO_COLUMNS`): `symbol_id, date, combo_name, weight`
 
@@ -258,6 +262,10 @@ execution modeling. The following phases are planned but not built yet:
   richer P&L / risk attribution than `alpha eval`.
 - [ ] **Forward / paper trading** — run the same construction logic on live
   daily data, track simulated fills and a running P&L without real capital.
+- [ ] **Intraday / microstructure data** — bid/ask prices & sizes, mid-price,
+  and intraday VWAP. These need a tick / L1–L2 quote feed (typically a paid or
+  brokerage data tier); the free daily sources here only expose daily bars, so
+  this is a separate data phase rather than extra columns on the daily schema.
 
 Until these land, treat `alpha eval` as a fast sanity check on a weight series,
 not a performance estimate.

data/downloader.py

@@ -9,8 +9,27 @@ logger = logging.getLogger(__name__)
 
 # Map the adjust argument to baostock's adjustflag codes.
 _BAOSTOCK_ADJUST = {"qfq": "2", "hfq": "1", "": "3", "none": "3"}
-_BAOSTOCK_FIELDS = "date,open,high,low,close,volume,amount"
-_OHLCV = ["open", "high", "low", "close", "volume", "amount"]
+
+# Richer field set requested by the batch downloader. On top of OHLCV+amount we
+# pull baostock's preclose, turnover rate, daily % change, trade/ST status, and
+# the four valuation ratios, then derive a daily VWAP (amount / volume).
+_BATCH_FIELDS = (
+    "date,open,high,low,close,preclose,volume,amount,turn,pctChg,"
+    "tradestatus,isST,peTTM,pbMRQ,psTTM,pcfNcfTTM"
+)
+# Every batch field except ``date`` is numeric (flags included: 0/1 strings).
+_BATCH_NUMERIC = [
+    "open", "high", "low", "close", "preclose", "volume", "amount",
+    "turn", "pctChg", "tradestatus", "isST",
+    "peTTM", "pbMRQ", "psTTM", "pcfNcfTTM",
+]
+# Output column order; ``vwap`` is derived (inserted right after ``amount``).
+_BATCH_COLUMNS = [
+    "symbol", "date",
+    "open", "high", "low", "close", "preclose", "volume", "amount", "vwap",
+    "turn", "pctChg", "tradestatus", "isST",
+    "peTTM", "pbMRQ", "psTTM", "pcfNcfTTM",
+]
 
 
 class _SessionLost(Exception):
@@ -163,7 +182,7 @@ def download_daily_batch(
         """One baostock query; returns df, or None (no data), or raises _SessionLost."""
         code = f"{symbol[:2]}.{symbol[2:]}"
         rs = bs.query_history_k_data_plus(
-            code=code, fields=_BAOSTOCK_FIELDS,
+            code=code, fields=_BATCH_FIELDS,
             start_date=start, end_date=end, frequency="d", adjustflag=flag,
         )
         if rs.error_code != "0":
@@ -176,12 +195,14 @@ def download_daily_batch(
             rows.append(rs.get_row_data())
         if not rows:
             return None
-        df = pd.DataFrame(rows, columns=["date", *_OHLCV])
+        df = pd.DataFrame(rows, columns=["date", *_BATCH_NUMERIC])
         # Suspended-trading days come back as empty strings; coerce to NaN
         # rather than crashing the whole symbol.
-        df[_OHLCV] = df[_OHLCV].apply(pd.to_numeric, errors="coerce")
+        df[_BATCH_NUMERIC] = df[_BATCH_NUMERIC].apply(pd.to_numeric, errors="coerce")
+        # Daily VWAP = turnover (yuan) / shares; NaN when no volume (suspended).
+        df["vwap"] = (df["amount"] / df["volume"]).where(df["volume"] > 0)
         df["symbol"] = symbol
-        return df[["symbol", "date", *_OHLCV]]
+        return df[_BATCH_COLUMNS]
 
     bs.login()
     try:

pipeline/common/schema.py

@@ -11,8 +11,19 @@ DATA_COLUMNS: Final[list[str]] = [
     "high",          # float64
     "low",           # float64
     "close",         # float64
+    "preclose",      # float64: previous trading day's close
     "volume",        # float64 (shares)
-    "amount",      # float64 (turnover in yuan)
+    "amount",        # float64 (turnover in yuan, raw/unadjusted)
+    "vwap",          # float64: daily VWAP = amount / volume. NB raw price scale —
+                     #   NOT comparable with adjusted OHLC under qfq/hfq.
+    "turn",          # float64: turnover rate (%)
+    "pctChg",        # float64: daily % change
+    "tradestatus",   # int: 1 = traded, 0 = suspended
+    "isST",          # int: 1 = ST/special-treatment, 0 = normal
+    "peTTM",         # float64: trailing-12m P/E
+    "pbMRQ",         # float64: P/B (most recent quarter)
+    "psTTM",         # float64: trailing-12m P/S
+    "pcfNcfTTM",     # float64: P/CF (net cash flow, TTM)
 ]
 
 # Required columns for alpha parquet files.