Kalshi Econ Bin Sum Trader

Trades CPI range bin markets on Kalshi using the constraint that mutually exclusive bins must sum to ~100%. Normalizes and trades the most mispriced bin when deviation exceeds tolerance. Requires SIMMER_API_KEY and simmer-sdk.

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

1. Group CPI bin markets by event (e.g., "March 2026 CPI")
2. Sum all bin prices in the group
3. If |sum - 1.0| > sum_tolerance, normalize: fair_prob = price / sum
4. Compute edge per bin: edge = fair_prob - market_price
5. 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) / 2.0
• size = 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

bash

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: [e-mail]

Review the source before providing live credentials if you require full auditability.