Polymarket Skills BuilderandClaude Opus 4.6
068b2adc75
Composable Agent Skills (SKILL.md format) for Polymarket prediction market trading. Includes scanner, analyzer, monitor, paper trader, strategy advisor, and live executor. All tested against live Polymarket APIs. Security audited with all HIGH/MEDIUM findings resolved. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
102 lines
3.5 KiB
Markdown
102 lines
3.5 KiB
Markdown
# Polymarket Fee Model
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## Overview
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Most Polymarket markets are **fee-free**. Dynamic taker fees apply only to
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short-duration crypto markets (5-minute and 15-minute expiry).
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## Fee-Free Markets
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The vast majority of markets on Polymarket -- political, sports, entertainment,
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weather, and long-duration crypto markets -- charge **zero fees** for both makers
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and takers. This makes arbitrage significantly more viable than on traditional
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exchanges.
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## Dynamic Taker Fees (Crypto Short-Duration Only)
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For 5-minute and 15-minute crypto prediction markets, a dynamic taker fee applies:
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```
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feeQuote = baseRate * min(price, 1 - price) * size
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```
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Where:
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- `baseRate` is set per market (typically 0.063 or 6.3%)
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- `price` is the execution price (0 to 1)
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- `size` is the number of shares
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### Effective Fee Rate by Price
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| Price | min(p, 1-p) | Effective Rate (baseRate=0.063) |
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|-------|-------------|-------------------------------|
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| 0.05 | 0.05 | 0.315% (0.063 * 0.05) |
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| 0.10 | 0.10 | 0.630% |
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| 0.20 | 0.20 | 1.260% |
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| 0.30 | 0.30 | 1.890% |
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| 0.40 | 0.40 | 2.520% |
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| 0.50 | 0.50 | 3.150% (maximum) |
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| 0.60 | 0.40 | 2.520% |
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| 0.70 | 0.30 | 1.890% |
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| 0.80 | 0.20 | 1.260% |
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| 0.90 | 0.10 | 0.630% |
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| 0.95 | 0.05 | 0.315% |
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The fee is **parabolic**, peaking at p=0.50 and dropping sharply near the extremes.
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This was explicitly designed to kill latency arbitrage on these fast markets.
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### Fee Calculator
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```python
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def calculate_fee(price: float, size: float, base_rate: float = 0.063) -> dict:
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"""Calculate dynamic taker fee for crypto short-duration markets."""
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fee_rate = base_rate * min(price, 1 - price)
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fee_amount = fee_rate * size
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cost_basis = price * size
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total_cost = cost_basis + fee_amount
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effective_rate = fee_amount / cost_basis if cost_basis > 0 else 0
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return {
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"fee_rate": fee_rate,
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"fee_amount": fee_amount,
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"cost_basis": cost_basis,
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"total_cost": total_cost,
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"effective_rate_pct": effective_rate * 100,
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}
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```
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### Breakeven Analysis for Arbitrage
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For an arbitrage trade buying both YES and NO:
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```python
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def arbitrage_breakeven(yes_price, no_price, base_rate=0.063):
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"""Calculate if arb is profitable after fees on fee-bearing markets."""
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raw_sum = yes_price + no_price
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raw_edge = 1.0 - raw_sum # Positive = underpriced
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yes_fee = base_rate * min(yes_price, 1 - yes_price)
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no_fee = base_rate * min(no_price, 1 - no_price)
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total_fee_rate = yes_fee + no_fee
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net_profit_per_share = raw_edge - total_fee_rate
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return {
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"raw_edge": raw_edge,
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"total_fee_rate": total_fee_rate,
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"net_profit_per_share": net_profit_per_share,
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"profitable": net_profit_per_share > 0,
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}
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```
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## Maker Rebates
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Post-only limit orders (introduced January 2026) receive maker rebates on
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qualifying markets. This creates a structural advantage for market-making
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strategies that provide liquidity.
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## Practical Implications
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1. **Fee-free markets**: Arbitrage edges as small as $0.01 are worth capturing
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2. **Fee-bearing markets**: Need at least 3-6% raw edge at mid-prices to break even
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3. **Extreme prices** (< 0.10 or > 0.90): Fees are minimal even on fee-bearing markets
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4. **Market making**: Maker rebates make spread-capture profitable on thin books
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