48h 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

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

Signal Logic

Discover all crypto price-threshold markets via keyword search
Parse each question: extract asset (BTC/ETH), strike price(s), date, and type (above/between/dip)
Group into curves by (asset, date)
For each curve with 2+ points:
- Check monotonicity across "above" markets
- Check range-sum consistency for "between" markets
Rank violations by magnitude
Trade only violations that also pass threshold gates (YES_THRESHOLD / NO_THRESHOLD)
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.

| Scenario | Mode | Financial risk | |---|---|---| | python trader.py | Paper (sim) | None | | Cron / automaton | Paper (sim) | None | | python trader.py --live | Live (polymarket) | Real USDC |

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

Required Credentials

| Variable | Required | Notes | |---|---|---| | SIMMER_API_KEY | Yes | Trading authority. Treat as a high-value credential. |

Tunables (Risk Parameters)

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

| Variable | Default | Purpose | |---|---|---| | SIMMER_MAX_POSITION | 40 | Max USDC per trade at full conviction | | SIMMER_MIN_TRADE | 5 | Floor for any trade | | SIMMER_MIN_VOLUME | 5000 | Min market volume filter (USD) | | SIMMER_MAX_SPREAD | 0.08 | Max bid-ask spread | | SIMMER_MIN_DAYS | 0 | Min days until resolution (0 = allow same-day) | | SIMMER_MAX_POSITIONS | 8 | Max concurrent open positions | | SIMMER_YES_THRESHOLD | 0.38 | Buy YES only if market probability <= this | | SIMMER_NO_THRESHOLD | 0.62 | Sell NO only if market probability >= this | | SIMMER_MIN_VIOLATION | 0.04 | Min curve violation magnitude to trigger a trade |

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