Kalshi Fed Speech Signal Trader
/install kalshi-fed-speech-signal-trader
\r \r
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
```\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
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install kalshi-fed-speech-signal-trader - 安装完成后,直接呼叫该 Skill 的名称或使用
/kalshi-fed-speech-signal-trader触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Kalshi Fed Speech Signal Trader 是什么?
Trades Fed rate markets on Kalshi based on hawkish/dovish sentiment signals from market question text. Scores net sentiment from keyword dictionaries and adj... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 109 次。
如何安装 Kalshi Fed Speech Signal Trader?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install kalshi-fed-speech-signal-trader」即可一键安装,无需额外配置。
Kalshi Fed Speech Signal Trader 是免费的吗?
是的,Kalshi Fed Speech Signal Trader 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Kalshi Fed Speech Signal Trader 支持哪些平台?
Kalshi Fed Speech Signal Trader 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Kalshi Fed Speech Signal Trader?
由 diagnostikon(@diagnostikon)开发并维护,当前版本 v1.0.2。