24h Price Curve Arbitrage Trader

This is a template. The default signal is implied-CDF violation detection across crypto price-threshold markets — remix it with additional assets, curve-fitting models, or cross-venue price feeds. The skill handles all the plumbing (market discovery, curve construction, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Polymarket lists dozens of price-threshold markets for the same asset and date:

• "Will BTC be above $64,000 on March 27?"
• "Will BTC be above $68,000 on March 27?"
• "Will BTC be between $68,000 and $70,000 on March 27?"
• "Will BTC be above $70,000 on March 27?"

Retail trades each market as an isolated bet. But together, these markets form an implied probability distribution curve — a CDF of where the market thinks the price will be.

This skill reconstructs that curve and finds where it is mathematically broken.

The Edge: Butterfly Arbitrage for Prediction Markets

In options markets, quant traders analyze the implied volatility surface across strikes to find mispriced options. This is the prediction market equivalent.

Violation Type 1: Monotonicity Break

The probability of being above a lower price must always be greater than or equal to being above a higher price:

P(BTC > $68k) >= P(BTC > $70k) >= P(BTC > $74k)

If a higher strike is priced above a lower strike, the curve is broken.

Violation Type 2: Range-Sum Inconsistency

A "between" market's price must equal the difference of two "above" markets:

P($68k < BTC < $70k) == P(BTC > $68k) - P(BTC > $70k)

If the market prices the range at 54% but the above-markets imply 48%, that's 6% of mathematical arbitrage.

Why This Works

1. Retail trades in silos — most users view each market independently and don't cross-reference the full strike ladder
2. No options infrastructure — unlike traditional markets, there's no market maker maintaining curve consistency across strikes
3. Mathematical, not opinion — the violations are provable inconsistencies, not subjective edge calls
4. High volume — BTC price markets are the most actively traded category on Polymarket

Signal Logic

1. Discover all crypto price-threshold markets via keyword search
2. Parse each question: extract asset (BTC/ETH), strike price(s), date, and type (above/between/dip)
3. Group into curves by (asset, date)
4. For each curve with 2+ points:
   • Check monotonicity across "above" markets
   • Check range-sum consistency for "between" markets
5. Rank violations by magnitude
6. Trade only violations that also pass threshold gates (YES_THRESHOLD / NO_THRESHOLD)
7. Size by conviction (violation magnitude), not flat amount

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.

autostart: false and cron: null mean nothing runs automatically until configured in Simmer UI.

Required Credentials

Tunables (Risk Parameters)

All declared as tunables in clawhub.json and adjustable from the Simmer UI.

Edge Thesis

Traditional options markets have market makers who enforce curve consistency (no-arbitrage pricing). Polymarket has no such mechanism — each market is priced by its own order book with its own liquidity pool. This creates systematic micro-inconsistencies in the implied distribution, especially when:

• New markets are created at previously unlisted strikes
• Large directional flow pushes one strike without propagating to neighbors
• Market makers leave gaps during low-liquidity hours

This skill treats the strike ladder as a probability lattice and trades the repair.

Dependency

simmer-sdk by Simmer Markets (SpartanLabsXyz)

• PyPI: https://pypi.org/project/simmer-sdk/
• GitHub: https://github.com/SpartanLabsXyz/simmer-sdk