jaxperro
34d02956d8
Moved the 8 tested-and-failed strategy tools into archive/ (copytrade, backtest, edge_research, lookback, table_77, lp_screener, lp_paper, xarb) with an archive/README explaining each. Root now holds the keepers: insider.py (made self-sufficient — dropped the copytrade load_json dependency) and smart_money.py (data foundation). New FINDINGS.md is the honest scorecard: six systematic public-data edges all efficient/illusory, the win-rate survivorship-bias finding, and the one real signal (z-score improbability + funding clustering). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
88 lines
3.4 KiB
Python
88 lines
3.4 KiB
Python
#!/usr/bin/env python3
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"""Aggregate the 77 copyable wallets into one table: total staked, PnL, ROI,
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consistency. Prints sorted by ROI and writes copyable_77.csv."""
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import csv
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import json
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import statistics
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import time
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from collections import defaultdict
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from concurrent.futures import ThreadPoolExecutor, as_completed
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import smart_money as sm
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from lookback import resolved # reuse the 120d+ resolved-bet puller
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WEEK = 7 * 86400
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def compute(r):
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cutoff = time.time() - 120 * 86400
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bets = resolved(r["wallet"], cutoff)
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if not bets:
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return None
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by_week = defaultdict(lambda: [0.0, 0.0])
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for b in bets:
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wk = int(b["ts"] // WEEK)
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by_week[wk][0] += b["pnl"]
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by_week[wk][1] += b["stake"]
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weeks = sorted(by_week)
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wpnl = [by_week[w][0] for w in weeks]
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wroi = [by_week[w][0] / by_week[w][1] if by_week[w][1] else 0 for w in weeks]
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total_bet = sum(b["stake"] for b in bets)
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total_pnl = sum(b["pnl"] for b in bets)
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gw = sum(p for p in wpnl if p > 0)
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gl = abs(sum(p for p in wpnl if p < 0))
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mean = statistics.mean(wroi)
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std = statistics.pstdev(wroi) if len(wroi) > 1 else 0
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oldest_days = round((time.time() - min(b["ts"] for b in bets)) / 86400)
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return {
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"username": r["username"], "wallet": r["wallet"],
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"weeks": len(weeks), "bets": len(bets),
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"total_bet": round(total_bet), "total_pnl": round(total_pnl),
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"roi_pct": round(total_pnl / total_bet * 100, 1) if total_bet else 0,
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"pct_weeks_green": round(sum(1 for p in wpnl if p > 0) / len(weeks) * 100),
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"profit_factor": round(gw / gl, 2) if gl else 999,
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"weekly_sharpe": round(mean / std, 2) if std else 0,
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"hold_pct": r["copy"]["hold_pct"],
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"history_days": oldest_days,
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"avg_bet": round(total_bet / len(bets)) if bets else 0,
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}
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def main():
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cop = [r for r in json.load(open("edge_profitable.json")) if r.get("copyable")]
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out = []
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with ThreadPoolExecutor(max_workers=12) as ex:
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futs = {ex.submit(compute, r): r for r in cop}
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for f in as_completed(futs):
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r = f.result()
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if r:
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out.append(r)
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out.sort(key=lambda r: r["roi_pct"], reverse=True)
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cols = ["username", "roi_pct", "total_bet", "total_pnl", "avg_bet",
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"pct_weeks_green", "profit_factor", "weekly_sharpe", "weeks",
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"bets", "hold_pct", "history_days", "wallet"]
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with open("copyable_77.csv", "w", newline="") as f:
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w = csv.DictWriter(f, fieldnames=cols)
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w.writeheader()
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w.writerows(out)
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print(f"{'#':>3} {'Trader':<20}{'ROI%':>7}{'TotalBet':>13}{'TotalPnL':>13}"
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f"{'AvgBet':>9}{'%grn':>6}{'PF':>6}{'Shrp':>6}{'wks':>4}{'hist_d':>7}")
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print("-" * 100)
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for i, r in enumerate(out, 1):
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print(f"{i:>3} {r['username'][:20]:<20}{r['roi_pct']:>6}%"
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f"{'$'+format(r['total_bet'], ','):>13}{'$'+format(r['total_pnl'], ','):>13}"
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f"{'$'+format(r['avg_bet'], ','):>9}{r['pct_weeks_green']:>5}%"
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f"{r['profit_factor']:>6.1f}{r['weekly_sharpe']:>6.2f}{r['weeks']:>4}"
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f"{r['history_days']:>7}")
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print("-" * 100)
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print(f"{len(out)} copyable wallets · saved to copyable_77.csv")
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print(f" total staked across all: ${sum(r['total_bet'] for r in out):,}")
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print(f" median history: {statistics.median([r['history_days'] for r in out])} days")
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if __name__ == "__main__":
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main()
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