AI-scored hawkishness of the most recent FOMC monetary policy statement, fetched from federalreserve.gov and analyzed by Claude Haiku. Scored 0-100 where 0 = maximally dovish (rate cuts, accommodation language) and 100 = maximally hawkish (rate hike bias, inflation focus, restrictive language). Inverse signal: high hawkishness = bearish for equities (rising rates compress multiples). Updates after each FOMC meeting (~8×/year). PCS is intentionally higher than the social sentiment signals because Fed policy is the single most studied equity-return predictor at 0-6 month horizons.

Fed rate policy directly affects the discount rate used in equity valuation. Hawkish language reliably forecasts higher short-term rates, which (1) compress PE multiples via the Gordon Growth Model, (2) increase the cost of corporate debt, and (3) strengthen the dollar which weighs on multinational earnings. The language itself is leading because the Fed often signals intentions before acting — markets price the signal, not just the rate move.

The lead time above is a design assumption, not an out-of-sample-validated relationship for a specific security or index. This is one Rates input among 47; it measures macro context, not a full investment thesis.

SPY · QQQ · TLT · GLD · JPM · BAC · GS

Scores are derived from macro signals (FRED, EIA, SEC filings, FINRA short interest) and updated as new data arrives. This is not financial advice. Past signal accuracy does not guarantee future results.
unstructuredalpha.com · Not financial advice