research: commit the 2026-10-07/08 studies left in the working tree, overnight mid/small (STOP)

Studies run by earlier sessions and documented in CLAUDE.md, but never
committed: FINRA short volume (SVR) and the research-only svr_momentum veto,
SEC fails-to-deliver, 13D activists and the 13D event sleeve, 13F
institutional flow, GDELT news volume, S&P 400/600 Form 4 insiders,
union_shield, shield_lab; plus the mid/small insider and Tiingo fetcher
changes and midsmall_rebuild.

overnight_midsmall: the overnight-only momentum book on S&P 400/600 earns
0.93 net Sharpe at 3 bp a side (2019-26) with corr 0.83 to the S&P 500 book
(STOP).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

research/lab/fetch_13f.py

@@ -0,0 +1,106 @@
+"""Fetch SEC DERA Form 13F structured data sets and aggregate per quarter.
+
+One ZIP per quarter (2016q1..2023q4 on this host), each holding TSVs of every
+13F filing parsed by the SEC (COVERPAGE + INFOTABLE). We aggregate the info
+table by CUSIP: total shares, total value, number of filers, and a
+representative issuer name.
+
+    https://www.sec.gov/files/structureddata/data/form-13f-data-sets/YYYYqQ_form13f.zip
+
+Writes data/research/dera13f/agg_YYYYqQ.csv (resume-safe: zips are cached and
+quarters with an aggregate CSV are skipped) and prints a summary line per
+quarter.
+
+    PYTHONPATH=. uv run python -m research.lab.fetch_13f
+"""
+from __future__ import annotations
+
+import io
+import os
+import sys
+import zipfile
+from concurrent.futures import ThreadPoolExecutor, as_completed
+
+import pandas as pd
+import requests
+
+from research.lab.fetch_us import _proxy_env
+
+DIR = os.path.join("data", "research", "dera13f")
+BASE = "https://www.sec.gov/files/structureddata/data/form-13f-data-sets/"
+UA = {"User-Agent": "quant-research/0.1 gahow@example.com"}
+QUARTERS = [f"{y}q{q}" for y in range(2016, 2024) for q in (1, 2, 3, 4)]
+
+
+def download(q: str) -> str | None:
+    os.makedirs(DIR, exist_ok=True)
+    path = os.path.join(DIR, f"{q}_form13f.zip")
+    if os.path.exists(path) and os.path.getsize(path) > 1_000_000:
+        return path
+    url = f"{BASE}{q}_form13f.zip"
+    for attempt in range(4):
+        try:
+            r = requests.get(url, headers=UA, timeout=600)
+            r.raise_for_status()
+            with open(path, "wb") as fh:
+                fh.write(r.content)
+            return path
+        except Exception as exc:  # noqa: BLE001
+            print(f"  download {q} attempt {attempt}: {exc}")
+    return None
+
+
+def aggregate(q: str, path: str) -> str | None:
+    out = os.path.join(DIR, f"agg_{q}.csv")
+    if os.path.exists(out):
+        return out
+    try:
+        zf = zipfile.ZipFile(path)
+        names = zf.namelist()
+        info = next((n for n in names if "INFOTABLE" in n.upper() and n.lower().endswith(".tsv")), None)
+        if info is None:
+            print(f"  {q}: no INFOTABLE in {names}")
+            return None
+        with zf.open(info) as fh:
+            df = pd.read_csv(io.TextIOWrapper(fh, encoding="latin-1"), sep="\t", dtype=str,
+                             usecols=lambda c: c.upper() in
+                             ("NAMEOFISSUER", "CUSIP", "VALUE", "SSHPRNAMT", "SSHPRNAMTTYPE"),
+                             low_memory=False)
+        df.columns = [c.upper() for c in df.columns]
+        for col in ("VALUE", "SSHPRNAMT"):
+            df[col] = pd.to_numeric(df[col], errors="coerce")
+        df = df[df.get("SSHPRNAMTTYPE", "SH").fillna("SH").str.upper().isin(["", "SH"])]
+        g = df.groupby("CUSIP", dropna=True)
+        agg = pd.DataFrame({
+            "issuer": g["NAMEOFISSUER"].first(),
+            "shares": g["SSHPRNAMT"].sum(),
+            "value": g["VALUE"].sum(),
+            "n_filers": g.size(),
+        }).reset_index()
+        agg.to_csv(out, index=False)
+        print(f"  {q}: {len(agg)} cusips, {len(df)} rows", flush=True)
+        return out
+    except Exception as exc:  # noqa: BLE001
+        print(f"  {q}: FAILED {exc}")
+        return None
+
+
+def main() -> None:
+    _proxy_env()
+    only = sys.argv[1:] or QUARTERS
+    with ThreadPoolExecutor(max_workers=3) as ex:
+        futs = {ex.submit(download, q): q for q in only}
+        paths = {}
+        for fut in as_completed(futs):
+            q = futs[fut]
+            p = fut.result()
+            if p:
+                paths[q] = p
+                print(f"  downloaded {q}", flush=True)
+    for q in only:
+        if q in paths:
+            aggregate(q, paths[q])
+
+
+if __name__ == "__main__":
+    main()