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https://github.com/jaxperro/winning-wallet-finder.git
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jaxperro
2ee8e79d00
The lead-time gate in validate_timing.py is a COPYABILITY heuristic, not proof of inside information: a short entry->resolution lead can be a genuine insider OR just someone who trades fast-resolving markets (live sports, hourly) well — indistinguishable, and irrelevant for copy purposes since either way the window is too tight to mirror. Rename the verdict accordingly. Gate unchanged (median lead >=24h to count as a copyable sharp; 50 sharps). Docs updated to current p80 numbers (218 profile matches, 62/83 forward-profitable, 50 sharps). The genuine insider-detection scanner (insider.py, z-score / Bubblemaps fingerprint) keeps its name — that's a different, correctly-named thing. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
77 lines
3.2 KiB
Python
77 lines
3.2 KiB
Python
#!/usr/bin/env python3
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"""Last-minute-vs-sharp check on the standout conviction wallets.
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This is a COPYABILITY heuristic, not proof of inside information: a near-100%
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win rate is only useful to us if we can actually mirror it. The tell is entry->
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resolution lead time on their WINNING conviction bets:
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* mostly < 1h before resolution -> last-minute, you can't follow it in time
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* hours-to-days of lead -> a sharp you could actually mirror
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A short lead can mean a genuine insider OR just someone who trades fast-resolving
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markets (live sports, hourly) well — we can't tell which, and for copy purposes
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it doesn't matter: either way the window is too tight to mirror.
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"""
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import json
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import os
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import statistics as st
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from concurrent.futures import ThreadPoolExecutor
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import cache
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HERE = os.path.dirname(__file__)
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COPYABLE_MED_LEAD = 24.0 # median lead (h) on winning conviction bets to count as copyable
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def lead_profile(w):
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ent = cache.get_entries(w)
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bets = cache.get_bets(w)
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cut = cache.conv_cutoff(b["size"] for b in bets) # this wallet's top-20% stake cutoff
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leads = [(b["res_t"] - ent[b["cond"]]) / 3600.0 for b in bets
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if b["won"] and (b["size"] or 0) >= cut and b["cond"] in ent
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and b["res_t"] and b["res_t"] >= ent[b["cond"]]]
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if not leads:
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return None
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med = st.median(leads)
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u6 = sum(1 for l in leads if l < 6) / len(leads)
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verdict = ("last-minute" if (med < 6 or sum(1 for l in leads if l < 1) / len(leads) > 0.5)
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else "borderline" if med < COPYABLE_MED_LEAD else "sharp")
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return dict(n=len(leads), med=med, u6=u6, verdict=verdict)
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def main():
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conv = json.load(open(os.path.join(HERE, "conviction_wallets.json")))
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print(f"validating timing on {len(conv)} conviction wallets…\n", flush=True)
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with ThreadPoolExecutor(max_workers=10) as ex:
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profs = list(ex.map(lambda c: (c, lead_profile(c["wallet"])), conv))
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sharps = []
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for c, p in profs:
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if p:
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c["med_lead_h"] = round(p["med"], 1)
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c["timing"] = p["verdict"]
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if p["verdict"] == "sharp":
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sharps.append(c)
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sharps.sort(key=lambda c: (c["fwd_conv_roi"] is not None, c.get("fwd_conv_roi") or -9,
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c["train_conv_roi"]), reverse=True)
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counts = {}
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for c, p in profs:
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counts[p["verdict"] if p else "no-data"] = counts.get(p["verdict"] if p else "no-data", 0) + 1
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print(f"timing breakdown: {counts}")
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print(f"COPYABLE SHARPS (median lead >= {COPYABLE_MED_LEAD:.0f}h): {len(sharps)}\n")
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h = (f"{'tr_win':>7}{'tr_roi':>7}{'medLeadH':>9}{'fw_win':>7}{'fw_roi':>7}{'fw_n':>5} wallet")
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print(h); print("-" * len(h))
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for c in sharps[:30]:
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fw = f"{c['fwd_win']:.0f}%" if c["fwd_win"] is not None else "—"
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fr = f"{c['fwd_conv_roi']:+.0%}" if c["fwd_conv_roi"] is not None else "—"
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print(f"{c['train_win']:>6.0f}%{c['train_conv_roi']:>+6.0%}{c['med_lead_h']:>9.0f}"
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f"{fw:>7}{fr:>7}{c['fwd_n']:>5} {c['wallet']}")
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json.dump(sharps, open(os.path.join(HERE, "watch_sharps.json"), "w"), indent=2)
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print(f"\n-> watch_sharps.json ({len(sharps)} copyable sharps, last-minute wallets filtered out)")
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if __name__ == "__main__":
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main()
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