Kalshi Fed Data Reaction Trader
by @diagnostikon
Trades Fed rate markets on Kalshi based on macro data releases (CPI, jobs). Scans CPI bin markets for implied CPI, adjusts rate cut probabilities using data...
clawhub install kalshi-fed-data-reaction-traderπ About This Skill
name: kalshi-fed-data-reaction-trader description: Trades Fed rate markets on Kalshi based on macro data releases (CPI, jobs). Scans CPI bin markets for implied CPI, adjusts rate cut probabilities using data sensitivity model. Requires SIMMER_API_KEY and simmer-sdk. metadata: author: Diagnostikon owner: Diagnostikon version: "1.0.0" displayName: Kalshi Fed Data Reaction Trader difficulty: advanced homepage: "https://simmer.markets/skills" repository: "https://github.com/SpartanLabsXyz/simmer-sdk" requires_env: "SIMMER_API_KEY" requires_pip: "simmer-sdk" default_mode: "paper" live_flag: "--live"
Kalshi Fed Data Reaction Trader
> This is a template. > The default signal uses static data sensitivity coefficients -- remix it with live BLS data feeds, real-time CPI nowcasts, or Fed funds futures reactions. > The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.
Strategy Overview
After CPI/jobs data releases, Fed rate probabilities adjust predictably. This skill scans Kalshi CPI bin markets to compute the market-implied CPI, classifies the data regime (high CPI, low CPI, neutral), and adjusts the fair probability of a rate cut accordingly. When the adjustment creates a gap vs. rate cut market prices, it trades.
Key advantages:
Signal Logic
Data Sensitivity Model
1. Scan CPI bin markets to compute probability-weighted implied CPI
2. Classify regime: high_cpi (>3.5%), low_cpi (<2.5%), or neutral
3. Apply sensitivity shift to baseline cut probability (50%)
4. Compare adjusted fair probability to rate cut market prices
5. Trade when |fair - market| >= entry_edge
Sensitivity Coefficients
| Regime | Cut Probability Shift | |--------|----------------------| | High CPI | -15% (hawkish) | | Low CPI | +10% (dovish) | | Strong jobs | -10% (hawkish) | | Weak jobs | +15% (dovish) |
Conviction-Based Sizing
conviction = min(|edge| / entry_edge, 2.0) / 2.0size = max($1.00, conviction * MAX_POSITION_USD)Risk Parameters
| Parameter | Default | Notes | |-----------|---------|-------| | Entry edge | 10% | Min fair-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 | 3 | Rate limiting | | Max slippage | 15% | Skip if slippage exceeds | | Min liquidity | $0 | Disabled by default |
Installation & Setup
clawhub install kalshi-fed-data-reaction-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_FED_DATA_ENTRY_EDGE | 0.10 | Min divergence to trigger trade |
| SIMMER_FED_DATA_EXIT_THRESHOLD | 0.45 | Sell position when price reaches this level |
| SIMMER_FED_DATA_MAX_POSITION_USD | 5.00 | Max USDC per trade |
| SIMMER_FED_DATA_MAX_TRADES_PER_RUN | 3 | Max trades per execution cycle |
| SIMMER_FED_DATA_SLIPPAGE_MAX | 0.15 | Max slippage before skipping trade |
| SIMMER_FED_DATA_MIN_LIQUIDITY | 0 | Min market liquidity USD (0 = disabled) |
Dependency
simmer-sdk is published on PyPI by Simmer Markets.
Review the source before providing live credentials if you require full auditability.