Kalshi Fed Speech Signal Trader
/install kalshi-fed-speech-signal-trader
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Kalshi Fed Speech Signal Trader\r
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This is a template.\r The default signal uses static keyword dictionaries -- remix it with NLP sentiment models, live Fed speech transcripts via FRED API, or real-time news feeds.\r The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.\r \r
Strategy Overview\r
\r Fed speeches contain hawkish and dovish signals that predict rate decisions. This skill scores net sentiment from keyword matching on market question text, then adjusts the fair probability of a rate cut. When the adjustment creates a gap vs. rate cut market prices, it trades.\r \r Key advantages:\r
- No external data needed -- extracts signal from market question text itself\r
- Extensible -- add new keywords, adjust weights, or plug in NLP models\r
- Cross-signal aggregation -- pools sentiment across all Fed-related markets\r \r
Signal Logic\r
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Sentiment Scoring\r
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- Scan all Fed rate market questions for hawkish/dovish keywords\r
- Weight matches (some keywords stronger signals than others)\r
- Compute net sentiment: dovish_total - hawkish_total\r
- Adjust baseline cut probability by 5% per net unit\r
- Trade rate cut markets when
|fair - market| >= entry_edge\r \r
Keyword Dictionaries\r
\r Hawkish (reduce cut probability): "inflation persistent", "tightening", "restrictive", "price stability", "higher for longer", etc.\r \r Dovish (increase cut probability): "data dependent", "labor softening", "gradual", "balanced", "appropriate to reduce", etc.\r \r
Conviction-Based Sizing\r
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conviction = min(|edge| / entry_edge, 2.0) / 2.0\rsize = max($1.00, conviction * MAX_POSITION_USD)\r- Larger edge = larger position, capped at MAX_POSITION_USD\r \r
Risk Parameters\r
\r | Parameter | Default | Notes |\r |-----------|---------|-------|\r | Entry edge | 10% | Min fair-vs-market divergence to trade |\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-fed-speech-signal-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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## 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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| Variable | Default | Purpose |\r
|----------|---------|---------|\r
| `SIMMER_FED_SPEECH_ENTRY_EDGE` | `0.10` | Min divergence to trigger trade |\r
| `SIMMER_FED_SPEECH_EXIT_THRESHOLD` | `0.45` | Sell position when price reaches this level |\r
| `SIMMER_FED_SPEECH_MAX_POSITION_USD` | `5.00` | Max USDC per trade |\r
| `SIMMER_FED_SPEECH_MAX_TRADES_PER_RUN` | `3` | Max trades per execution cycle |\r
| `SIMMER_FED_SPEECH_SLIPPAGE_MAX` | `0.15` | Max slippage before skipping trade |\r
| `SIMMER_FED_SPEECH_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-fed-speech-signal-trader - After installation, invoke the skill by name or use
/kalshi-fed-speech-signal-trader - Provide required inputs per the skill's parameter spec and get structured output
What is Kalshi Fed Speech Signal Trader?
Trades Fed rate markets on Kalshi based on hawkish/dovish sentiment signals from market question text. Scores net sentiment from keyword dictionaries and adj... It is an AI Agent Skill for Claude Code / OpenClaw, with 109 downloads so far.
How do I install Kalshi Fed Speech Signal Trader?
Run "/install kalshi-fed-speech-signal-trader" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Kalshi Fed Speech Signal Trader free?
Yes, Kalshi Fed Speech Signal Trader is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Kalshi Fed Speech Signal Trader support?
Kalshi Fed Speech Signal Trader is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Kalshi Fed Speech Signal Trader?
It is built and maintained by diagnostikon (@diagnostikon); the current version is v1.0.2.