Kalshi Econ Bin Sum Trader
/install kalshi-econ-bin-sum-trader
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Kalshi Econ Bin Sum Trader\r
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This is a template. \r 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. \r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r
Strategy Overview\r
\r 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.\r \r Key advantages:\r
- Mathematical certainty -- bins MUST sum to 100%, any deviation is a guaranteed mispricing\r
- No forecasting needed -- the strategy is model-free, relying purely on arbitrage math\r
- Self-correcting -- as the sum approaches 100%, signals disappear (no stale trades)\r
- Works across any bin-style market -- CPI, GDP, unemployment, any mutually exclusive set\r \r
Signal Logic\r
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Bin Sum Normalization\r
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- Group CPI bin markets by event (e.g., "March 2026 CPI")\r
- Sum all bin prices in the group\r
- If
|sum - 1.0| > sum_tolerance, normalize:fair_prob = price / sum\r - Compute edge per bin:
edge = fair_prob - market_price\r - Trade the bin with the largest absolute edge\r \r
Example\r
\r | Bin | Market Price | Fair (normalized) | Edge | Action |\r |-----|-------------|-------------------|------|--------|\r | CPI \x3C 2.0% | 5% | 4.8% | -0.2% | Hold |\r | CPI 2.0-2.5% | 25% | 23.8% | -1.2% | Hold |\r | CPI 2.5-3.0% | 35% | 33.3% | -1.7% | BUY NO |\r | CPI 3.0-3.5% | 30% | 28.6% | -1.4% | Hold |\r | CPI > 3.5% | 10% | 9.5% | -0.5% | Hold |\r | Sum | 105% | 100% | | |\r \r
Conviction-Based Sizing\r
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conviction = min(|edge| / deviation, 2.0) / 2.0\rsize = max($1.00, conviction * MAX_POSITION_USD)\r- Larger edge relative to total deviation = larger position\r \r
Remix Ideas\r
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- Cross-event sum: Apply same logic to GDP, unemployment, or Fed rate bins\r
- Consensus prior: Weight normalization toward consensus CPI forecasts\r
- Multi-bin arbitrage: Trade multiple bins simultaneously for hedged positions\r
- Rolling rebalance: Re-run as market moves to capture dynamic mispricing\r \r
Risk Parameters\r
\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Sum tolerance | 5% | Min deviation from 100% before trading |\r | Exit threshold | 45% | Sell when position price reaches this |\r | Max position size | $5.00 USDC | Per market |\r | Max trades per run | 3 | Rate limiting |\r | Max slippage | 15% | Skip if slippage exceeds |\r | Min liquidity | $0 | Disabled by default |\r \r
Installation & Setup\r
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clawhub install kalshi-econ-bin-sum-trader\r
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Requires: `SIMMER_API_KEY` and `SOLANA_PRIVATE_KEY` environment variables.\r
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## Cron Schedule\r
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Cron is set to `null` -- the skill does not run on a schedule until you configure it in the Simmer UI.\r
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## Safety & Execution Mode\r
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**The skill defaults to dry-run mode. Real trades only execute when `--live` is passed explicitly.**\r
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| Scenario | Mode | Financial risk |\r
|----------|------|----------------|\r
| `python trader.py` | Dry run | None |\r
| Cron / automaton | Dry run | None |\r
| `python trader.py --live` | Live (Kalshi via DFlow) | Real USDC |\r
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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.\r
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## Required Credentials\r
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| Variable | Required | Notes |\r
|----------|----------|-------|\r
| `SIMMER_API_KEY` | Yes | Trading authority. Treat as a high-value credential. |\r
| `SOLANA_PRIVATE_KEY` | Yes | Base58-encoded Solana private key for live trading. |\r
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## Tunables (Risk Parameters)\r
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All risk parameters are declared in `clawhub.json` as `tunables` and adjustable from the Simmer UI without code changes.\r
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| Variable | Default | Purpose |\r
|----------|---------|---------|\r
| `SIMMER_ECON_BINSUM_SUM_TOLERANCE` | `0.05` | Min deviation from 100% sum before trading |\r
| `SIMMER_ECON_BINSUM_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_ECON_BINSUM_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_ECON_BINSUM_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_ECON_BINSUM_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping (0.15 = 15%) |\r
| `SIMMER_ECON_BINSUM_MIN_LIQUIDITY` | `0` | Min market liquidity USD (0 = disabled) |\r
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## Dependency\r
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`simmer-sdk` is published on PyPI by Simmer Markets.\r
- PyPI: https://pypi.org/project/simmer-sdk/\r
- GitHub: https://github.com/SpartanLabsXyz/simmer-sdk\r
- Publisher: [email protected]\r
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Review the source before providing live credentials if you require full auditability.\r
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install kalshi-econ-bin-sum-trader - After installation, invoke the skill by name or use
/kalshi-econ-bin-sum-trader - Provide required inputs per the skill's parameter spec and get structured output
What is 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... It is an AI Agent Skill for Claude Code / OpenClaw, with 82 downloads so far.
How do I install Kalshi Econ Bin Sum Trader?
Run "/install kalshi-econ-bin-sum-trader" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Kalshi Econ Bin Sum Trader free?
Yes, Kalshi Econ Bin Sum Trader is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Kalshi Econ Bin Sum Trader support?
Kalshi Econ Bin Sum Trader is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Kalshi Econ Bin Sum Trader?
It is built and maintained by diagnostikon (@diagnostikon); the current version is v1.0.1.