Kalshi Fed Speech Signal Trader

This is a template. 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. The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

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.

Key advantages:

• No external data needed -- extracts signal from market question text itself
• Extensible -- add new keywords, adjust weights, or plug in NLP models
• Cross-signal aggregation -- pools sentiment across all Fed-related markets

Signal Logic

Sentiment Scoring