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#

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

Momentum Categories#

Momentum ScoreCategoryMeaning> +0.3HOTDriver outperforming, probability should be higher-0.3 to +0.3FLATStable form, no momentum edge< -0.3COLDDriver 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#

ParameterDefaultNotesEntry edge10%Min model-vs-market divergence to tradeExit threshold45%Sell when position price reaches thisMax position size$5.00 USDCPer marketMax trades per run5Rate limitingMax slippage15%Skip if slippage exceedsMin liquidity$0Disabled by default

Installation & Setup#

bash

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.

ScenarioModeFinancial riskpython trader.pyDry runNoneCron / automatonDry runNonepython trader.py --liveLive (Kalshi via DFlow)Real USDC

Required Credentials#

VariableRequiredNotesSIMMER_API_KEYYesTrading authority. Treat as a high-value credential.SOLANA_PRIVATE_KEYYesBase58-encoded Solana private key for live trading.

Tunables (Risk Parameters)#

VariableDefaultPurposeSIMMER_F1_RACEMOM_ENTRY_EDGE``0.10Min divergence to trigger tradeSIMMER_F1_RACEMOM_EXIT_THRESHOLD``0.45Sell position when price reaches this levelSIMMER_F1_RACEMOM_MAX_POSITION_USD``5.00Max USDC per tradeSIMMER_F1_RACEMOM_MAX_TRADES_PER_RUN``5Max trades per execution cycleSIMMER_F1_RACEMOM_SLIPPAGE_MAX``0.15Max slippage before skipping tradeSIMMER_F1_RACEMOM_MIN_LIQUIDITY``0Min 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