Event-Driven Backtest
ANALYZE · How assets historically behave around FOMC, CPI, NFP, Earnings Season, VIX Spikes. Synthetic 2020–2025 pattern data. NOT advice. NOT live market data.
Return Distribution After Event (frequency histogram)
Return After Event by Date (colored by outcome)
By-Outcome Breakdown
| Outcome |
Events (n) |
Avg Return After |
Hit Rate |
Skew |
Full Event Log
| # |
Date |
Outcome |
Regime |
Before (%) |
Day-Of (%) |
After (%) |
Signal |
Methodology & Honesty Gaps — All instance data is synthetic/representative (2020-2025 pattern reconstruction based on published academic estimates). Returns shown for the configured day-window around each event date.
Window scaling beyond base 5/20 days is approximate (linear scalar — not regression-derived).
sharpe_around_event = mean(after) / std(after) — event-window basis only, not annualized.
information_ratio = mean(after − before) / std(after − before).
Hit rate = % of instances with positive after-window return.
NOT live market data. NOT financial advice.
Sources: Bernanke-Kuttner 2005 (FOMC ±0.85% mean), Bauer-Swanson 2022 (CPI ±0.75% mean), BLS historical NFP surprises.
Hash: event-backtest-2026-06-06-v1