Kalshi F1 Race Momentum Trader

This is a template. The default signal uses static recent results -- remix it with live F1 API data for automatic momentum recalculation after each race weekend. The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Recent form matters in F1. A driver on a hot streak (wins, podiums in the last 3 races) has demonstrably higher championship probability than their season-long average suggests. Markets are slow to fully price in momentum shifts -- they anchor to pre-season expectations and lag behind recent performance changes.

Key advantages:

Recency bias is real and quantifiable -- last 3 races predict next-race performance better than season average
Markets anchor to narratives -- "Verstappen always wins" persists even during cold streaks
Weighted recency -- most recent race gets 3x weight, capturing acceleration/deceleration in form
Hot/cold classification -- simple trend labels (HOT/COLD/FLAT) identify tradeable regimes

Signal Logic

Momentum Model

Collect last 3 race results per driver (position finished)
Convert positions to performance scores: P1=1.0, P20=0.0
Apply recency weights: [3x, 2x, 1x] for [most recent, second, third]
Compute momentum score: normalized to [-1.0, +1.0]
Adjust base probability: adjusted = base + momentum * SCALE * base
Compare adjusted probability to Kalshi market price
Trade when |adjusted - market| >= entry_edge

Momentum Categories

| Momentum Score | Category | Meaning | |---------------|----------|---------| | > +0.3 | HOT | Driver outperforming, probability should be higher | | -0.3 to +0.3 | FLAT | Stable form, no momentum edge | | < -0.3 | COLD | Driver underperforming, probability should be lower |

Conviction-Based Sizing

conviction = min(|edge| / entry_edge, 2.0) / 2.0
size = max($1.00, conviction * MAX_POSITION_USD)
Larger edge = larger position, capped at MAX_POSITION_USD

Risk Parameters

| Parameter | Default | Notes | |-----------|---------|-------| | Entry edge | 10% | Min model-vs-market divergence to trade | | Exit threshold | 45% | Sell when position price reaches this | | Max position size | $5.00 USDC | Per market | | Max trades per run | 5 | Rate limiting | | Max slippage | 15% | Skip if slippage exceeds | | Min liquidity | $0 | Disabled by default |

Installation & Setup

clawhub install kalshi-f1-race-momentum-trader

Requires: SIMMER_API_KEY and SOLANA_PRIVATE_KEY environment variables.

Cron Schedule

Cron is set to null -- the skill does not run on a schedule until you configure it in the Simmer UI.

Safety & Execution Mode

The skill defaults to dry-run mode. Real trades only execute when --live is passed explicitly.

| Scenario | Mode | Financial risk | |----------|------|----------------| | python trader.py | Dry run | None | | Cron / automaton | Dry run | None | | python trader.py --live | Live (Kalshi via DFlow) | Real USDC |

Required Credentials

| Variable | Required | Notes | |----------|----------|-------| | SIMMER_API_KEY | Yes | Trading authority. Treat as a high-value credential. | | SOLANA_PRIVATE_KEY | Yes | Base58-encoded Solana private key for live trading. |

Tunables (Risk Parameters)

| Variable | Default | Purpose | |----------|---------|---------| | SIMMER_F1_RACEMOM_ENTRY_EDGE | 0.10 | Min divergence to trigger trade | | SIMMER_F1_RACEMOM_EXIT_THRESHOLD | 0.45 | Sell position when price reaches this level | | SIMMER_F1_RACEMOM_MAX_POSITION_USD | 5.00 | Max USDC per trade | | SIMMER_F1_RACEMOM_MAX_TRADES_PER_RUN | 5 | Max trades per execution cycle | | SIMMER_F1_RACEMOM_SLIPPAGE_MAX | 0.15 | Max slippage before skipping trade | | SIMMER_F1_RACEMOM_MIN_LIQUIDITY | 0 | Min market liquidity USD (0 = disabled) |

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

PyPI: https://pypi.org/project/simmer-sdk/
GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
Publisher: hello@simmer.markets