Kalshi Econ Bin Sum Trader
This is a template.
The default signal uses the fundamental constraint that mutually exclusive outcome bins must sum to 100% -- remix it with Bayesian priors, consensus forecasts, or cross-event correlation models.
The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.
Strategy Overview
CPI range bin markets on Kalshi price each outcome bin independently. Since exactly one bin must resolve YES, the probabilities must sum to 100%. When the market sum deviates beyond tolerance, at least one bin is mispriced. This skill normalizes the distribution and trades the most mispriced bin.
Key advantages:
- Mathematical certainty -- bins MUST sum to 100%, any deviation is a guaranteed mispricing
- No forecasting needed -- the strategy is model-free, relying purely on arbitrage math
- Self-correcting -- as the sum approaches 100%, signals disappear (no stale trades)
- Works across any bin-style market -- CPI, GDP, unemployment, any mutually exclusive set
Signal Logic
Bin Sum Normalization
- Group CPI bin markets by event (e.g., "March 2026 CPI")
- Sum all bin prices in the group
- If
|sum - 1.0| > sum_tolerance, normalize:fair_prob = price / sum - Compute edge per bin:
edge = fair_prob - market_price - Trade the bin with the largest absolute edge
Example
| Bin | Market Price | Fair (normalized) | Edge | Action |
|---|---|---|---|---|
| CPI < 2.0% | 5% | 4.8% | -0.2% | Hold |
| CPI 2.0-2.5% | 25% | 23.8% | -1.2% | Hold |
| CPI 2.5-3.0% | 35% | 33.3% | -1.7% | BUY NO |
| CPI 3.0-3.5% | 30% | 28.6% | -1.4% | Hold |
| CPI > 3.5% | 10% | 9.5% | -0.5% | Hold |
| Sum | 105% | 100% |
Conviction-Based Sizing
conviction = min(|edge| / deviation, 2.0) / 2.0size = max($1.00, conviction * MAX_POSITION_USD)- Larger edge relative to total deviation = larger position
Remix Ideas
- Cross-event sum: Apply same logic to GDP, unemployment, or Fed rate bins
- Consensus prior: Weight normalization toward consensus CPI forecasts
- Multi-bin arbitrage: Trade multiple bins simultaneously for hedged positions
- Rolling rebalance: Re-run as market moves to capture dynamic mispricing
Risk Parameters
| Parameter | Default | Notes |
|---|---|---|
| Sum tolerance | 5% | Min deviation from 100% before trading |
| 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-econ-bin-sum-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 |
The automaton cron is set to null -- it does not run on a schedule until you configure it in the Simmer UI. autostart: false means it won't start automatically on install.
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)
All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes.
| Variable | Default | Purpose |
|---|---|---|
SIMMER_ECON_BINSUM_SUM_TOLERANCE | 0.05 | Min deviation from 100% sum before trading |
SIMMER_ECON_BINSUM_EXIT_THRESHOLD | 0.45 | Sell position when price reaches this level |
SIMMER_ECON_BINSUM_MAX_POSITION_USD | 5.00 | Max USDC per trade |
SIMMER_ECON_BINSUM_MAX_TRADES_PER_RUN | 3 | Max trades per execution cycle |
SIMMER_ECON_BINSUM_SLIPPAGE_MAX | 0.15 | Max slippage before skipping (0.15 = 15%) |
SIMMER_ECON_BINSUM_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
Review the source before providing live credentials if you require full auditability.