mirror of
https://github.com/jaxperro/winning-wallet-finder.git
synced 2026-07-27 15:57:47 +00:00
f176ba134a
- Add copyback.py (in-sample copy backtest), oos.py (out-of-sample test), huntwide.py (wide insider sweep) — completes the detect→hunt→validate→watch pipeline. - Rewrite README around Winning Wallet Finder: the z-score idea explained, how the pieces fit, quickstart, data sources, live-watcher setup, honest verdict. - Extend FINDINGS with the insider-detection results and the in-sample vs out-of-sample copy verdict (+545% in-sample collapsed to one-wallet variance out-of-sample). - Refresh config.example.json to the current schema (discord/alchemy/watch). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
154 lines
5.5 KiB
Python
154 lines
5.5 KiB
Python
#!/usr/bin/env python3
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"""Out-of-sample test of the copy-the-edge-wallets strategy.
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SELECT wallets using only resolved bets in [Feb 1 - Apr 30] (z-score), with NO
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knowledge of May-June. Then COPY those wallets' entries forward from May 30,
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compounding. If the forward return is strong, the edge is real; if it collapses,
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the in-sample +545% was selection theater.
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"""
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import math
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import time
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from collections import defaultdict
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import smart_money as sm
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from insider import resolved_bets, norm_sf
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from copyback import entries_after, outcomes, _parse, BET_K, START_BANKROLL
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SEL_T0 = _parse("2026-02-01") # selection window start (resolution time)
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SEL_T1 = _parse("2026-04-30") # selection window end — nothing after this is seen
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TEST_START = _parse("2026-05-30") # copy entries on/after this
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Z_PICK = 4.0 # insider-grade cut, judged AS OF Apr 30
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MIN_BETS = 15
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def score_pre(wallet):
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"""z-score over resolved bets in the selection window only."""
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bets = [b for b in resolved_bets(wallet, SEL_T0 - 10 * 86400)
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if SEL_T0 <= b["res_t"] <= SEL_T1]
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if len(bets) < MIN_BETS:
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return None
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wins = sum(1 for b in bets if b["won"])
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exp = sum(b["p"] for b in bets)
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var = sum(b["p"] * (1 - b["p"]) for b in bets) or 1e-9
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z = (wins - exp) / math.sqrt(var)
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return {"wallet": wallet, "n": len(bets), "wins": wins, "z": z, "pval": norm_sf(z)}
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def candidate_pool():
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import csv
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seen = {}
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try:
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for r in csv.DictReader(open("huntwide.csv")):
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seen[r["wallet"]] = r["username"]
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except FileNotFoundError:
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pass
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return seen
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def main():
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from concurrent.futures import ThreadPoolExecutor, as_completed
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pool = candidate_pool()
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print(f"candidate pool: {len(pool)} wallets · scoring on [Feb1–Apr30] only...", flush=True)
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selected = []
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with ThreadPoolExecutor(max_workers=12) as ex:
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futs = {ex.submit(score_pre, w): w for w in pool}
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done = 0
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for f in as_completed(futs):
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done += 1
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try:
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r = f.result()
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except Exception:
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r = None
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if r and r["z"] >= Z_PICK:
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r["name"] = pool[r["wallet"]]
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selected.append(r)
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if done % 50 == 0:
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print(f" {done}/{len(pool)}", flush=True)
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selected.sort(key=lambda r: r["z"], reverse=True)
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print(f"\nINSIDER-GRADE AS OF APR 30 (z>={Z_PICK}): {len(selected)} wallets")
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for r in selected:
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print(f" {r['name'][:18]:18} z={r['z']:>4.1f} p={r['pval']:.1e} "
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f"{r['wins']}/{r['n']} (pre-period)")
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if not selected:
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print("\nNo wallets were insider-grade as of Apr 30 — the edge wallets are "
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"too new to have a pre-period track record. That itself is the answer.")
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return
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# forward copy from May 30, z(pre)-weighted, compounding
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tot_z = sum(r["z"] for r in selected)
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weights = {r["wallet"]: r["z"] / tot_z for r in selected}
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names = {r["wallet"]: r["name"] for r in selected}
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print(f"\ncopying {len(selected)} wallets forward from 2026-05-30 "
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f"(z-pre weighted, compounding)...", flush=True)
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bets = []
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now = time.time()
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for r in selected:
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w = r["wallet"]
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ent = entries_after(w, TEST_START)
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outc = outcomes(w)
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for a, (price, ts, title) in ent.items():
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if a not in outc or not (0 < price < 1):
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continue
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cur, end = outc[a]
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bets.append({"w": w, "ts": ts, "price": price, "mark": cur,
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"res_ts": end or now, "resolved": bool(end and end < now)})
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print(f"forward copied bets: {len(bets)}", flush=True)
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events = []
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for i, b in enumerate(bets):
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events.append((b["ts"], 0, i))
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if b["resolved"]:
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events.append((b["res_ts"], 1, i))
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events.sort()
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cash = START_BANKROLL
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open_cost = 0.0
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posn = {}
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wins = losses = 0
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realized = 0.0
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bw = defaultdict(float)
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for ts, kind, i in events:
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b = bets[i]
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if kind == 0:
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bankroll = cash + open_cost
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stake = min(weights[b["w"]] * BET_K * bankroll, cash)
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if stake < 1:
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continue
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posn[i] = (stake / b["price"], stake)
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cash -= stake
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open_cost += stake
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else:
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if i not in posn:
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continue
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shares, stake = posn.pop(i)
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payout = shares * (1 if b["mark"] >= 0.5 else 0)
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cash += payout
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open_cost -= stake
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realized += payout - stake
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bw[names[b["w"]]] += payout - stake
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wins += b["mark"] >= 0.5
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losses += b["mark"] < 0.5
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open_val = sum(sh * bets[i]["mark"] for i, (sh, st) in posn.items())
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equity = cash + open_val
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print(f"\n{'='*64}")
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print(f" OUT-OF-SAMPLE forward result (selection knew nothing past Apr 30)")
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print(f" resolved: {wins+losses} ({wins}W/{losses}L"
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f"{f' · {wins/(wins+losses)*100:.0f}%' if wins+losses else ''}) "
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f"· open: {len(posn)}")
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print(f" realized P&L: ${realized:+,.2f} ({realized/START_BANKROLL*100:+.1f}%)")
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print(f" unrealized: ${open_val-open_cost:+,.2f}")
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print(f" ── ending equity ${equity:,.2f} -> {(equity/START_BANKROLL-1)*100:+.1f}% "
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f"on $1,000 over {(now-TEST_START)/86400:.0f}d")
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print(f"{'='*64}")
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for n in sorted(bw, key=lambda k: bw[k], reverse=True):
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print(f" {n[:18]:18} {bw[n]:+,.2f}")
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if __name__ == "__main__":
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main()
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