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║ ╚══════╝ ╚══╝╚══╝ ╚═╝ ╚═╝╚═╝ ╚═╝╚═╝ ╚═╝ EDGE ║
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║ AI PREDICTION MARKET ENGINE STATUS: LIVE ● ║
║ VENUE: POLYMARKET MODE: PAPER TRADING ║
║ COMPANY: SWARM AXIS CYCLE: 60 MIN ║
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║ ┌─────────────┬─────────────┬─────────────┬─────────────┐ ║
║ │ MARKETS │ TRADES │ EDGE │ BET SIZE │ ║
║ │ 15 │ 6 │ ≥ 5.0% │ $100 │ ║
║ └─────────────┴─────────────┴─────────────┴─────────────┘ ║
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╚═══════════════════════════════════════════════════════════════════════╝
"If you can model the future better than the crowd, you can trade the difference."
Swarm Edge deploys an adversarial AI committee against live prediction markets. Operators forecast. Skeptics attack. An arbiter resolves. When the swarm's consensus diverges from the live market price by sufficient edge — and agents agree — it fires a paper trade.
Every evaluation is logged. Every trade is scored. The endgame is real capital.
polymarket_watchlist.json [20 verified slugs]
│
▼
INFER LOOP ── every 60 min
│
├─ live price fetch ── Gamma API
├─ OPERATORS ── independent p_yes
├─ SKEPTICS ── challenge assumptions
└─ ARBITER ── consensus + disagreement
│
├── edge < 0.05 → SKIP
├── disagreement > 0.45 → SKIP
└── edge ≥ 0.05 → TRADE [$100]
│
▼
RESOLVER [on demand]
outcome → brier score → P&L
min_edge_abs ≥ 0.05 model must beat market by 5%+
max_disagreement ≤ 0.45 agents must align
min_hours_to_resolution ≥ 24h no expiring markets
paper_size = $100 fixed for clean scoring
US POLITICS ── blue wave 2026 · tariff refund ruling
MACRO / FED ── recession 2026 · 0 / 1 / 2 / 3 / 4 / 5 rate cuts
CRYPTO ── eth flips btc · btc $150k by june 2026
SPORTS ── masters 2026 · nba finals 2026
[✓] ENGINE CORE complete
[✓] POLYMARKET LIVE complete
[✓] LLM REASONING active ●
[~] BRIER SCORING in progress
[ ] KALSHI planned
[ ] REAL CAPITAL pending proof of edge
cd ~/blackglasslab
# start
nohup bash scripts/run_live.sh >> logs/infer_loop.log 2>&1 &
# monitor
tail -f logs/infer_loop.log
# last evaluation
python3 -c "
import json
d = json.load(open('signals/infer_diagnostics.json'))
print('run:', d.get('ts_utc'))
for r in d.get('rows', []):
print(f' {r[\"slug\"][:42]:<42} {r[\"decision\"]} edge={r[\"edge_abs\"]:.3f} {r[\"reason\"]}')
"
# view trades
python3 -c "
import sqlite3
conn = sqlite3.connect('memory/runs.sqlite')
rows = conn.execute('SELECT ts_utc, market_id, side, edge, size_usd FROM paper_trades ORDER BY ts_utc DESC').fetchall()
print(len(rows), 'trades'); [print(r) for r in rows]
"
# resolve + score
python3 scripts/resolve_paper_trades.py
python3 scripts/watch_resolutions.py live_runner.py core engine
scripts/run_live.sh infer loop daemon
scripts/resolve_paper_trades.py resolve closed trades · brier score
scripts/watch_resolutions.py P&L summary
markets/polymarket_watchlist.json 20 verified active slugs
memory/runs.sqlite trades · runs · forecasts
SWARM EDGE · SWARM AXIS · PAPER TRADING LIVE · APRIL 2026
REAL CAPITAL IS THE ENDGAME