# EMPIRICAL_DESIGN.md

Working design document — expands as stages complete. Authoritative parameter values live in config/. Protocol reference: project CLAUDE.md §§7–16.

# Objects of interest

Shocks: idiosyncratic residual-return extremes (lagged conditional quantiles / robust SD multiples), separated by sign; volume, range, and illiquidity-proxy shocks.
Propagation outcomes: breadth, speed (censoring-aware), intensity, amplification (ISAR), persistence, asymmetry, at horizons h ∈ {1,2,5,10,15,30,60,120} min within session.
Networks: estimated strictly pre-shock (rolling/frozen windows): correlation, partial correlation, lead–lag, volatility spillover, sparse VAR/glasso; centrality roles.
Evolution: flexible year effects first; era bins only as secondary presentation.

# Identification strategy (threat: common information)

Exclude scheduled macro windows from the idiosyncratic baseline.
Isolation filters: low contemporaneous market/sector return, no simultaneous extreme in >2% of universe, leave-one-out factors.
Placebo timing matched on stock, minute-of-day, volatility state.
Permuted networks preserving degree/sector/size/liquidity.
Negative controls: future network weights (falsification only), pre-shock outcomes.

# Inference

Two-way clustering (source × date) as baseline; day-block bootstrap for distribution-level statements; randomization inference for event studies; multiple-testing corrections within outcome families.

# Status

Stage A pilot audit (2026-07-13)
Stage B full download (2026-07-13)
Stage C full raw audit
Stage D clean panels
Stage E descriptive evidence
Stage F shocks & propagation (baseline, F2 network/cumulative/co-jumps, robustness)
Stage G paper (v1.0 2026-07-13; v1.1 revised 2026-10-17)
Revision diagnostics from stored events (scripts/17, 2026-10-17)

Implemented vs planned (as of 2026-10-17): implemented — residual shocks |z|≥6 with isolation, placebo timing, ΔΔ, day/month/ticker bootstrap, lagged top-20 correlation neighbours, cumulative breadth, co-jump minutes, pre-event levels, co-arrival classes, stratified estimator. Not implemented — two-way clustering regressions, local projections with fixed effects, permuted networks, future network weights, multiple-testing corrections, sector proxies (no security master), macro-window propagation as a separate object, ML extension. See paper §8 and REVIEW-REPORT §8.