Gahow Wang
04e2c5c3be
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>
94 lines
3.1 KiB
Python
94 lines
3.1 KiB
Python
"""Extract the SUBJECT company from SC 13D filing headers.
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The EDGAR full index lists the FILER (the activist) in the CIK/company
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columns; the target company appears only inside the document. For Schedule
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13D filings the SGML header's first COMPANY block is the subject company
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(verified on samples: FTE Networks, 30DC, Helius Medical, Genco). This
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fetcher reads data/research/edgar_13d.csv, keeps SC 13D originals, and for
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each one fetches the .txt header, extracting the first company name + CIK.
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Writes data/research/edgar_13d_targets.csv (resume-safe: paths already
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extracted are skipped).
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PYTHONPATH=. uv run python -m research.lab.fetch_13d_targets [--limit N]
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"""
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from __future__ import annotations
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import os
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import re
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import sys
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import time
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from concurrent.futures import ThreadPoolExecutor, as_completed
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import pandas as pd
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import requests
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from research.lab.fetch_us import _proxy_env
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IN = "data/research/edgar_13d.csv"
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OUT = "data/research/edgar_13d_targets.csv"
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UA = {"User-Agent": "quant-research/0.1 gahow@example.com", "Accept-Encoding": "gzip"}
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NAME_RE = re.compile(r"COMPANY CONFORMED NAME:\s*(.+)")
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CIK_RE = re.compile(r"CENTRAL INDEX KEY:\s*(\d+)")
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WORKERS = 5
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def fetch_target(path: str) -> tuple[str, str, int] | None:
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url = "https://www.sec.gov/Archives/" + path
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for attempt in range(3):
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try:
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r = requests.get(url, headers=UA, timeout=60)
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if r.status_code == 404:
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return path, "", 0
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r.raise_for_status()
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head = r.text[:20000]
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name = NAME_RE.search(head)
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cik = CIK_RE.search(head)
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return path, (name.group(1).strip() if name else ""), int(cik.group(1)) if cik else 0
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except Exception: # noqa: BLE001
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time.sleep(1.0 * (attempt + 1))
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print(f" FAILED {path}")
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return None
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def main() -> None:
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_proxy_env()
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limit = None
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if "--limit" in sys.argv:
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limit = int(sys.argv[sys.argv.index("--limit") + 1])
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ev = pd.read_csv(IN)
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ev = ev[ev["form"] == "SC 13D"].copy()
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done: set[str] = set()
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frames = []
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if os.path.exists(OUT):
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prev = pd.read_csv(OUT)
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frames.append(prev)
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done = set(prev["path"])
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todo = ev[~ev["path"].isin(done)]
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if limit:
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todo = todo.head(limit)
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print(f"13D originals: {len(ev)}, done: {len(done)}, fetching: {len(todo)}")
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rows = []
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with ThreadPoolExecutor(max_workers=WORKERS) as ex:
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futs = {ex.submit(fetch_target, p): p for p in todo["path"]}
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n = 0
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for fut in as_completed(futs):
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res = fut.result()
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n += 1
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if res is not None:
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path, name, cik = res
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rows.append({"path": path, "target_name": name, "target_cik": cik})
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if n % 500 == 0:
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print(f" {n}/{len(todo)}")
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df = pd.DataFrame(rows)
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if len(df):
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meta = todo.set_index("path")[["filed", "cik", "company"]]
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df = df.join(meta, on="path")
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allrows = pd.concat(frames + [df]) if frames or len(df) else pd.DataFrame()
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allrows.to_csv(OUT, index=False)
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print(f"stored {len(allrows)} rows -> {OUT}")
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if __name__ == "__main__":
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main()
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