kalshi-fed-data-reaction-trader

Trades Fed rate markets on Kalshi based on macro data releases (CPI, jobs). Scans CPI bin markets for implied CPI, adjusts rate cut probabilities using data sensitivity model. Requires SIMMER_API_KEY and simmer-sdk.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "kalshi-fed-data-reaction-trader" with this command: npx skills add Diagnostikon/kalshi-fed-data-reaction-trader

Kalshi Fed Data Reaction Trader

This is a template. The default signal uses static data sensitivity coefficients -- remix it with live BLS data feeds, real-time CPI nowcasts, or Fed funds futures reactions. The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

After CPI/jobs data releases, Fed rate probabilities adjust predictably. This skill scans Kalshi CPI bin markets to compute the market-implied CPI, classifies the data regime (high CPI, low CPI, neutral), and adjusts the fair probability of a rate cut accordingly. When the adjustment creates a gap vs. rate cut market prices, it trades.

Key advantages:

  • Data-driven -- uses market-implied CPI from Kalshi's own CPI bin markets
  • Predictable reaction function -- high CPI is hawkish, low CPI is dovish
  • Cross-market information -- extracts signal from CPI markets to trade rate markets

Signal Logic

Data Sensitivity Model

  1. Scan CPI bin markets to compute probability-weighted implied CPI
  2. Classify regime: high_cpi (>3.5%), low_cpi (<2.5%), or neutral
  3. Apply sensitivity shift to baseline cut probability (50%)
  4. Compare adjusted fair probability to rate cut market prices
  5. Trade when |fair - market| >= entry_edge

Sensitivity Coefficients

RegimeCut Probability Shift
High CPI-15% (hawkish)
Low CPI+10% (dovish)
Strong jobs-10% (hawkish)
Weak jobs+15% (dovish)

Conviction-Based Sizing

  • conviction = min(|edge| / entry_edge, 2.0) / 2.0
  • size = max($1.00, conviction * MAX_POSITION_USD)
  • Larger edge = larger position, capped at MAX_POSITION_USD

Risk Parameters

ParameterDefaultNotes
Entry edge10%Min fair-vs-market divergence to trade
Exit threshold45%Sell when position price reaches this
Max position size$5.00 USDCPer market
Max trades per run3Rate limiting
Max slippage15%Skip if slippage exceeds
Min liquidity$0Disabled by default

Installation & Setup

clawhub install kalshi-fed-data-reaction-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 risk
python trader.pyDry runNone
Cron / automatonDry runNone
python trader.py --liveLive (Kalshi via DFlow)Real USDC

Required Credentials

VariableRequiredNotes
SIMMER_API_KEYYesTrading authority. Treat as a high-value credential.
SOLANA_PRIVATE_KEYYesBase58-encoded Solana private key for live trading.

Tunables (Risk Parameters)

VariableDefaultPurpose
SIMMER_FED_DATA_ENTRY_EDGE0.10Min divergence to trigger trade
SIMMER_FED_DATA_EXIT_THRESHOLD0.45Sell position when price reaches this level
SIMMER_FED_DATA_MAX_POSITION_USD5.00Max USDC per trade
SIMMER_FED_DATA_MAX_TRADES_PER_RUN3Max trades per execution cycle
SIMMER_FED_DATA_SLIPPAGE_MAX0.15Max slippage before skipping trade
SIMMER_FED_DATA_MIN_LIQUIDITY0Min market liquidity USD (0 = disabled)

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

Multi Edge-TTS CN

Edge-TTS 在线语音合成 skill。基于微软 Edge TTS 引擎,生成速度快(1-2秒),支持多种音色和输出格式。同时支持飞书(OGG/Opus)和企业微信(AMR)。默认音色 xiaoxiao_lively。需联网。

Registry SourceRecently Updated
General

vedic-destiny

吠陀命盘分析中文入口。用于完整命盘研判、命主盘 Rashi chart 与九分盘 Navamsha chart 联读、既往事件回看、出生时间稳定度判断、事业主题、婚姻主题、时空盘专题,以及基于 Jagannatha Hora PDF、星盘截图或文本命盘数据的系统拆盘。当用户提到完整星盘、事业方向、婚姻问题、关系窗...

Registry SourceRecently Updated
General

One Person Company OS

Build a visual operating cockpit for an AI-native one-person company across promise, buyer, product, delivery, cash, learning, and assets. / 为 AI 一人公司建立可视化经营...

Registry SourceRecently Updated
General

健康追踪

健康追踪技能 - 追踪饮水、睡眠、步数等健康数据,JSON存储。

Registry SourceRecently Updated