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#

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#

BinMarket PriceFair (normalized)EdgeActionCPI < 2.0%5%4.8%-0.2%HoldCPI 2.0-2.5%25%23.8%-1.2%HoldCPI 2.5-3.0%35%33.3%-1.7%BUY NOCPI 3.0-3.5%30%28.6%-1.4%HoldCPI > 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#

ParameterDefaultNotesSum tolerance5%Min deviation from 100% before tradingExit threshold45%Sell when position price reaches thisMax position size$5.00 USDCPer marketMax trades per run3Rate limitingMax slippage15%Skip if slippage exceedsMin liquidity$0Disabled 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.

ScenarioModeFinancial riskpython trader.pyDry runNoneCron / automatonDry runNonepython trader.py --liveLive (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#

VariableRequiredNotesSIMMER_API_KEYYesTrading authority. Treat as a high-value credential.SOLANA_PRIVATE_KEYYesBase58-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.

VariableDefaultPurposeSIMMER_ECON_BINSUM_SUM_TOLERANCE``0.05Min deviation from 100% sum before tradingSIMMER_ECON_BINSUM_EXIT_THRESHOLD``0.45Sell position when price reaches this levelSIMMER_ECON_BINSUM_MAX_POSITION_USD``5.00Max USDC per tradeSIMMER_ECON_BINSUM_MAX_TRADES_PER_RUN``3Max trades per execution cycleSIMMER_ECON_BINSUM_SLIPPAGE_MAX``0.15Max slippage before skipping (0.15 = 15%)SIMMER_ECON_BINSUM_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

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