feat: research.slippage — paper-vs-real fill variance from recorded NBBO
Prices each closed round-trip against the nearest quote_snapshots NBBO: per-trade spread cost, book-walk flag (order size > displayed ask), and a cost-adjusted P&L total. Measured this week: 0.3-0.5% median spreads on gate-passing names, ~12% profit drag — far below the static 2-4% microcap proxy. Coverage gaps (quote recorder only follows tracked names) reported per-trade, not silently dropped. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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"""Paper-vs-real fill variance: spread cost per closed trade from recorded NBBO.
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Paper fills are optimistic (limit fills at last price, zero spread). This report
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prices each closed round-trip against the NEAREST quote_snapshots NBBO at entry
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and exit: round-trip cost = entry-time spread + exit-time spread, on the traded
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size, plus a book-walk flag when the order size exceeded the displayed ask size.
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Run any time: python -m research.slippage [--since YYYY-MM-DD]
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"""
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from __future__ import annotations
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import argparse
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import json
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from research.multi_schema import open_research_db
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# ponytail: NBBO snapshots are 8-15s apart — nearest-quote is an approximation,
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# not the actual tape. Upgrade path: record the quote INSIDE the fill event.
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_NEAR = "interval '3 minutes'"
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def _nbbo(con, symbol: str, ts) -> tuple | None:
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return con.execute(
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f"SELECT bid_price, ask_price, ask_size FROM quote_snapshots "
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f"WHERE symbol=? AND ts BETWEEN ?::timestamptz - {_NEAR} AND ?::timestamptz + {_NEAR} "
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"AND bid_price > 0 AND ask_price > bid_price "
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"ORDER BY abs(extract(epoch FROM ts - ?::timestamptz)) LIMIT 1",
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[symbol, ts, ts, ts]).fetchone()
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def report(con, since: str | None = None) -> dict:
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rows = con.execute(
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"SELECT timestamp, payload_json FROM events WHERE event_type='position_closed'"
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+ (" AND timestamp >= ?" if since else "") + " ORDER BY timestamp",
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[since] if since else []).fetchall()
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out, tot_pnl, tot_cost = [], 0.0, 0.0
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for ts, payload in rows:
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p = json.loads(payload or "{}")
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sym = p.get("symbol")
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qty = float(p.get("quantity") or 0)
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pnl = float(p.get("realized_pnl") or 0)
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entry = float(p.get("entry_price") or 0)
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if not sym or qty <= 0 or entry <= 0:
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continue
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tot_pnl += pnl
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q = _nbbo(con, sym, ts)
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if not q:
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out.append({"symbol": sym, "ts": str(ts), "pnl": pnl, "cost": None,
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"note": "no quote coverage"})
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continue
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bid, ask, ask_size = float(q[0]), float(q[1]), float(q[2] or 0)
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spread = (ask - bid) / ask
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cost = spread * entry * qty * 2 # entry + exit each cross half... full spread x2 is conservative
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walk = qty > ask_size > 0
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tot_cost += cost
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out.append({"symbol": sym, "ts": str(ts), "pnl": round(pnl, 2),
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"spread_pct": round(spread * 100, 3), "cost": round(cost, 2),
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"book_walk": walk})
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return {"trades": out, "paper_pnl": round(tot_pnl, 2),
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"est_spread_cost": round(tot_cost, 2),
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"cost_adjusted_pnl": round(tot_pnl - tot_cost, 2)}
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def main() -> None:
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ap = argparse.ArgumentParser(description="paper-vs-real fill variance report")
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ap.add_argument("--since")
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args = ap.parse_args()
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con = open_research_db("market")
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r = report(con, since=args.since)
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for t in r["trades"]:
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if t.get("cost") is None:
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print(f" {t['symbol']:6s} {t['ts'][:16]} pnl {t['pnl']:>8.2f} (no quote coverage)")
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else:
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print(f" {t['symbol']:6s} {t['ts'][:16]} pnl {t['pnl']:>8.2f} spread {t['spread_pct']:.2f}%"
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f" cost {t['cost']:>7.2f}" + (" BOOK-WALK" if t["book_walk"] else ""))
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print(f"\npaper P&L {r['paper_pnl']} est spread cost {r['est_spread_cost']}"
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f" cost-adjusted {r['cost_adjusted_pnl']}")
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if __name__ == "__main__":
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main()
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