Kalshi ETH Bin Distribution Trader#

This is a template. The default signal uses the 100% sum constraint on price bins -- remix it with implied distribution fitting, volatility smile analysis, or cross-venue arbitrage. The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview#

Kalshi ETH price markets are structured as mutually exclusive bins (e.g., "ETH above $3000", "ETH $2500-$3000") that must sum to exactly 100%. When retail flow pushes individual bins out of alignment, the sum deviates from 100% and creates structural arbitrage.

Key advantages:

• Mathematical certainty -- bins MUST sum to 100%, deviations are temporary
• No external data needed -- pure internal consistency check
• Self-correcting -- market makers eventually re-align bins

Signal Logic#

Sum Constraint Model#

1. Fetch all active ETH price bin markets from Kalshi
2. Group bins by resolution date (weekly, monthly)
3. Sum probabilities across all bins in each group
4. If sum deviates > sum_tolerance from 100%, flag the group
5. Normalize each bin: fair = current / total_sum
6. Trade bins where |fair - market| >= entry_edge

Example (with defaults)#

BinMarket PFair P (normalized)EdgeActionETH $2000-$250025%23.1%-1.9%HoldETH $2500-$300035%32.4%-2.6%HoldETH $3000-$350030%27.8%-2.2%HoldETH above $350018%16.7%-1.3%Hold**Sum****108%****100%**Overpriced

Conviction-Based Sizing#

• conviction = min(|edge| / entry_edge, 2.0) / 2.0
• size = max($5.00, conviction * MAX_POSITION_USD)
• Larger edge = larger position, capped at MAX_POSITION_USD

Remix Ideas#

• Implied volatility fitting: Fit a lognormal distribution to bin prices
• Cross-venue arb: Compare Kalshi bin structure to Polymarket/Betfair
• Historical mean reversion: Track how fast bin sums revert to 100%
• Options-implied distribution: Use ETH options chain for fair bin prices

Risk Parameters#

ParameterDefaultNotesEntry edge8%Min per-bin edge to tradeExit threshold45%Sell when position price reaches thisMax position size$5.00 USDCPer marketMax trades per run3Rate limitingSum tolerance5%Min sum deviation to trigger analysisMax slippage15%Skip if slippage exceedsMin liquidity$0Disabled by default

Installation & Setup#

bash

clawhub install kalshi-eth-bin-distribution-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 -- keep this credential private.SOLANA_PRIVATE_KEYFor liveBase58-encoded Solana private key for DFlow transactions.

Tunables (Risk Parameters)#

All risk parameters are declared in clawhub.json as tunables and adjustable from the Simmer UI without code changes.

VariableDefaultPurposeSIMMER_ETH_BINDIST_ENTRY_EDGE``0.08Min per-bin edge to trigger tradeSIMMER_ETH_BINDIST_EXIT_THRESHOLD``0.45Sell position when price reaches this levelSIMMER_ETH_BINDIST_MAX_POSITION_USD``5.00Max USDC per tradeSIMMER_ETH_BINDIST_MAX_TRADES_PER_RUN``3Max trades per execution cycleSIMMER_ETH_BINDIST_SLIPPAGE_MAX``0.15Max slippage before skipping (15%)SIMMER_ETH_BINDIST_MIN_LIQUIDITY``0Min market liquidity USD (0 = disabled)SIMMER_ETH_BINDIST_SUM_TOLERANCE``0.05Min bin sum deviation to trigger analysis

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.