polymarket-optimizer

Automatic parameter optimizer for polymarket-executor. Reads performance_metrics.json every 6 hours, analyzes win rates and P&L per strategy, adjusts learned_config.json to improve future performance. Also builds paper trade metrics and assesses live trading readiness. Part of the Wesley Agent Ecosystem — mirrors crypto-executor-optimizer pattern.

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Install skill "polymarket-optimizer" with this command: npx skills add georges91560/polymarket-optimizer

Polymarket Optimizer — Adaptive Parameter Tuner

🧠 WHAT IT DOES

Reads trading performance from polymarket-executor, analyzes what works, and adjusts parameters automatically.

Runs every 6 hours via OpenClaw cron job. Zero manual intervention required.

Input files (written by executor):

  • performance_metrics.json — per-strategy win rates, P&L, trade counts
  • paper_trades.json — all simulated trade records
  • portfolio.json — capital, positions, daily P&L

Output files (read by executor at next startup):

  • learned_config.json — updated thresholds, Kelly fraction, allocations
  • optimizer_log.jsonl — full history of every optimization run

⚡ QUICK START

cd /data/.openclaw/workspace/skills/polymarket-optimizer
python3 polymarket_optimizer.py

Expected output:

============================================================
POLYMARKET OPTIMIZER v1.0.0
Run time: 2026-03-05 14:00:00 UTC
============================================================
[CONFIG] Loaded. Optimization #1
[PORTFOLIO] Health: HEALTHY
[PORTFOLIO] Capital: $102.34 | Return: 2.3%
[ANALYSIS] parity_arbitrage: EXCELLENT | WR=100.0% | Trades=8 | P&L=+0.523
[ANALYSIS] tail_end: GOOD | WR=75.0% | Trades=12 | P&L=+0.312
[OPTIMIZER] 2 adjustments made:
  🚀 parity_arb excellent → min_profit 0.020 → 0.015
  📈 parity_arb allocation 30% → 40%
[READINESS] Resolved trades: 8/30
[READINESS] Win rate: 84.6% (need 55%+)
[TELEGRAM] Report sent.
============================================================
OPTIMIZER COMPLETE
============================================================

🔧 WHAT IT ADJUSTS

Strategy Thresholds

If strategy is...Action
Poor (WR < 50%)Raise threshold → trade only best opportunities
Underperforming (WR 50–65%)Slight threshold increase
Average (WR 65–80%)No change
Good (WR 65–80%, positive P&L)No change
Excellent (WR > 80%)Lower threshold → capture more volume

Capital Allocation

If strategy is...Action
PoorReduce allocation (min 5–10%)
ExcellentIncrease allocation (max 50–70%)

Allocations always normalized to sum to 100%.

Kelly Fraction

Portfolio healthAction
Critical (return < -10%)Reduce Kelly → smaller positions
Excellent (return > 10%, WR > 65%)Increase Kelly → larger positions

Scan Frequency

ConditionAction
WR > 80% + 20+ tradesScan faster (min 120s)
Portfolio warning/criticalScan slower (max 600s)

📊 LIVE READINESS ASSESSMENT

Every run evaluates whether paper trading results justify going live.

4 criteria must ALL pass:

CriterionThreshold
Resolved trades≥ 30
Win rate≥ 55%
Total P&LPositive
Circuit breakerNot active

Telegram report includes readiness status automatically.


📱 TELEGRAM REPORT

🧠 POLYMARKET OPTIMIZER REPORT
🕐 2026-03-05 14:00 UTC
🔄 Optimization #4

Portfolio Health: 🟢 HEALTHY
💰 Capital: $108.45
📈 Return: 8.5%
🎯 Win Rate: 76.9%
📊 Total Trades: 20

Strategy Performance:
  🚀 parity_arbitrage: 100.0% WR | 8 trades | P&L: +0.523
  ✅ tail_end: 75.0% WR | 12 trades | P&L: +0.312

Adjustments Made:
  🚀 parity_arb excellent → min_profit 0.020 → 0.015
  📈 parity_arb allocation 30% → 40%
  ⚖️ Allocations renormalized

Live Trading Readiness:
🔴 NOT YET READY
  ❌ Need 30+ resolved trades
  📊 Progress: 20/30 trades
  🎯 Win rate: 76.9% (need 55%+) ✅

📁 FILES

FileLocationDescription
polymarket_optimizer.pyskills/polymarket-optimizer/Main optimizer script
learned_config.jsonWORKSPACE/Output — read by executor
optimizer_log.jsonlWORKSPACE/Full optimization history

⏰ CRON JOB

Add to OpenClaw cron configuration:

# Run optimizer every 6 hours
0 */6 * * * docker exec openclaw-yyvg-openclaw-1 python3 /data/.openclaw/workspace/skills/polymarket-optimizer/polymarket_optimizer.py

Version: 1.0.0 | License: MIT | Author: Georges Andronescu (Wesley Armando)

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