# ⚡ Faster, Wider, More Fragile? **UQO Working Paper No. 15** — *The Evolution of Intraday Shock Propagation in U.S. Equity Markets, 1992–2026* [-b31b1b?logo=latex&logoColor=white)](paper/main.pdf) [-b31b1b?logo=latex&logoColor=white)](paper/main_irfa.pdf) [](pyproject.toml) [](docs/DATA_AUDIT.md) [-2e7d32)](scripts/) [](https://uqo.ca) [](mailto:simon-pierre.boucher@uqo.ca) > **TL;DR** — Using 7.69 billion one-minute bars on the full listed *and delisted* U.S. equity > cross-section (1992–2026), we track how intraday shocks propagate. (1) Markets absorb > idiosyncratic shocks: across 1.85 million isolated ±6σ minute events, abnormal market-wide > propagation against matched within-stock placebos is economically zero at 1–120 minutes, in every > decade. (2) Transmission is concentrated and intensifying: the shocked stock's twenty closest > lagged-correlation neighbours respond strongly (+64×10⁻⁴ abnormal jump probability at five > minutes) and this network channel tripled from the 1990s (+28) to the 2020s (+90) while > market-wide spillover stayed at zero. (3) Tail synchronisation migrated to the market-wide > minute: ordinary extreme minute returns became 108× rarer than in the 1990s, the Epps curve > flattened (one-minute pairwise correlation 0.004 in 1996 vs 0.30 in 2015), and severe co-jump > minutes spike by orders of magnitude in 2008 and 2020. Modern markets absorb the idiosyncratic > and transmit the systemic. --- ## 📌 Status | Item | Value | |---|---| | Version | 1.0 (July 2026) — UQO working-paper cover added 2026-10-17 | | SSRN | not yet submitted | | Journal | *International Review of Financial Analysis* — submission package ready in `outputs/release/` (manuscript, anonymous manuscript, highlights, cover letter, title page, online appendix), **not yet submitted** (`outputs/release/submission_checklist.md`: online appendix and data-licence note still open) | | Code & data | reproducible from `scripts/` (see Quick start); raw minute bars (88 GB) not redistributed | ## 🎯 What this paper does Has the U.S. equity market become faster, wider and more fragile at the intraday horizon? The paper answers with the longest and broadest minute-level panel assembled to date — every listed and delisted common stock from 1992 to 2026 — and three complementary measurement devices: 1. **Shock-propagation event studies**: 1.85 million isolated ±6σ one-minute events, each matched to a within-stock placebo minute, tracked at horizons of 1 to 120 minutes for breadth (share of other stocks jumping), gradient (response by liquidity/size tier) and network response (twenty nearest lagged-correlation neighbours); 2. **Epps curves**: pairwise correlation as a function of sampling interval, by year; 3. **Co-jump counts**: the number of stocks with extreme minute returns in the same minute, with a severity scale calibrated on calm, GFC and COVID periods. All headline numbers are macro-generated from machine-readable registries (`paper/results_macros.tex`, built by `scripts/15_build_results_macros.py`); no number is hand-typed. ## 🏆 Headline results | Object | Estimate | |---|---| | Panel | 7,686,275,524 bars, 81,306 tickers, 221,957 listing spells | | Isolated ±6σ events (real / placebo) | 1,854,384 / 1,766,058 | | Abnormal market-wide breadth, 5 min / 30 min | −1.04 (0.90) / −3.10 (1.01) ×10⁻⁴ — zero | | Network response (20 neighbours), 5 / 15 / 30 min | +64.0 (1.8) / +55.4 (1.8) / +49.6 (1.8) ×10⁻⁴ | | Network response by decade (5 min) | 1990s +28 → 2000s +30 → 2010s +81 → 2020s +90 | | Extreme minute returns (>1%), 1990s → 2010s | 518 → 4.8 per million (÷108) | | Epps: 1-min correlation, 1996 / 2015 / 2024 | 0.004 / 0.30 / 0.21 | | Severe co-jump minutes, calm / GFC / COVID | 3.5 / 9.3 / 6.4 per 10,000 ; COVID severe share 83.7 % vs 9.53 % pre-COVID | | Robustness (Table VIII) | 11 designs incl. placebo-network falsification, month-cluster bootstrap, post-decimalisation | ## 🗂 Repository layout ``` intraday-fragility/ ├── config/ # all parameters (YAML) — no magic constants in code ├── src/intraday_fragility/ # package: download, audit, cleaning, features, shocks, networks, econometrics, tables, figures ├── scripts/ # 00_download_pilot … 16_robustness (numbered pipeline) ├── tests/ # pytest (7 tests) ├── data/ # manifests only (raw bars never committed) ├── outputs/ │ ├── estimates/ # machine-readable estimates (707 MB, not committed) │ ├── diagnostics/ # audit JSON reports │ ├── figures/, tables/ # generated figures (PDF+PNG with source CSV) and LaTeX tables │ └── release/ # IRFA submission package (manuscript, anonymous, highlights, cover letter, title page, online appendix) ├── appendix/ # Internet Appendix (internet_appendix.tex → .pdf) ├── docs/ # DATA_AUDIT, DATA_DICTIONARY, DECISION_LOG, EMPIRICAL_DESIGN, LIMITATIONS, LITERATURE_MAP, REPRODUCIBILITY, COMPUTE_LOG ├── logs/ # pipeline logs ├── STATUS.md # stage-by-stage progress log └── paper/ ├── main.tex # UQO working-paper version (template cover) → main.pdf ├── main_irfa.tex # journal version (elsarticle, IRFA) → main_irfa.pdf ├── main_irfa_anon.tex # anonymous journal version → main_irfa_anon.pdf ├── highlights.tex # Elsevier highlights ├── sections/, figures/, tables/, bibliography/references.bib, results_macros.tex ``` ## 🚀 Quick start ```bash uv sync # or: pip install -e . python -m intraday_fragility.cli probe-data python -m intraday_fragility.cli download --start 1992-01 --end 2026-03 # 411 monthly parquet files, 87.7 GB python -m intraday_fragility.cli verify-download make # runs scripts/00 … 16 in order (see Makefile) python scripts/15_build_results_macros.py # → paper/results_macros.tex cd paper && make # UQO WP → main.pdf cd paper && latexmk -pdf main_irfa.tex main_irfa_anon.tex # journal + anonymous versions ``` Full download and cleaning run on the MacLustr cluster (see `docs/COMPUTE_LOG.md`); the estimation stages run on a 64 GB Apple-silicon node. ## 🗃 Data Minute-level OHLCV bars from the Hugging Face dataset `mito0o852/OHLCV-1m`, pinned at revision `776328445b7ac6e7815ef3a483e9c8ded1eb6d56` (411 monthly Parquet files, 87.7 GB, 1992-01 → 2026-03, no missing months; upstream source Finnhub.io per the dataset card). Schema: UTC bar-start timestamp, unadjusted OHLC, integer volume, ticker; **no zero-volume bars** (missing minute = no trade). Delisted securities are present (only 22–26 % of 1992 tickers survive). Cleaning: exchange calendar truncation, split/reverse-split screens (6,944 events), OHLC-violation and duplicate screens, corporate-action filters before any variance-based measure. Full audit: `docs/DATA_AUDIT.md`; variable definitions: `docs/DATA_DICTIONARY.md`. The dataset card carries no licence — the raw data are therefore not redistributed (`docs/LIMITATIONS.md`). ## 🔬 Methodology 1. **Universe & cleaning** (`scripts/04`–`08`, `src/…/cleaning.py`): monthly audits, split refinement, clean minute panel by listing spell. 2. **Aggregates** (`09`–`10`): extreme-return frequencies, realised variance, Epps curves, staleness. 3. **Shock detection & propagation** (`11`–`14`, `src/…/shocks.py`, `networks.py`): isolated ±6σ events, matched within-stock placebos, breadth / gradient / network responses at 1–120 min, difference-in-differences by decade. 4. **Co-jumps** (`13`–`14`): market-wide extreme-minute counts and severity regimes. 5. **Inference** (`src/…/econometrics.py`): event-clustered and month-cluster bootstrap standard errors. 6. **Robustness** (`16`): 11 designs — post-decimalisation, mid-day, ex-announcement, calm/crisis, |z| ≥ 8/12, ex-non-common, placebo network. 7. **Reporting** (`15`, `src/…/tables.py`, `figures.py`): results macros, LaTeX tables, CVD-safe vector figures. ## 🖼 Figures & tables inventory | Figure | Content | |---|---| | `figP1_coverage`, `figP2_seasonality` | pilot coverage and intraday seasonality | | `figE1_coverage` … `figE9_splits` | universe coverage, survivorship, seasonality, concentration, extreme minutes, realised variance, staleness, Epps curves, splits | | `figF1_irf_decade` | propagation impulse responses by decade | | `figF2_evolution` | evolution of breadth vs network channel | | `figF3_gradient_state` | response gradient by liquidity tier and market state | | `figF4_network` | nearest-neighbour network response | | `figF5_cojumps` | co-jump counts and severity regimes | Tables (`paper/tables/*.tex`): data audit, sample cascade, propagation estimates by horizon and decade, gradient, network, co-jumps, Epps, robustness battery (Table VIII). ## ⚠️ Limitations - Bars are trade-conditional (no zero-volume bars) and the venue scope (consolidated vs single venue) is not documented upstream. - Security-type classification relies on suffix heuristics; non-common securities are excluded in robustness only. - Data licence unspecified on the dataset card: research use with citation, no redistribution of derived minute data. - Extended online appendix tables still to be finalised before journal submission. ## 📝 Citation ```bibtex @techreport{boucher2026fragile, author = {Boucher, Simon-Pierre}, title = {Faster, Wider, More Fragile? The Evolution of Intraday Shock Propagation in U.S. Equity Markets, 1992--2026}, institution = {Universit\'e du Qu\'ebec en Outaouais, D\'epartement des sciences administratives}, type = {Working Paper}, number = {15}, year = {2026}, month = {July} } ``` ## 👤 Author & contact **Simon-Pierre Boucher** — Département des sciences administratives, Université du Québec en Outaouais (UQO), Gatineau, QC. 📧 [simon-pierre.boucher@uqo.ca](mailto:simon-pierre.boucher@uqo.ca) ## 🗒 Notes - Numbering: the project was first filed as `UQO_WP_001`; it is **Working Paper No. 15** since 2026-10-17 (No. 1 is the amenity-capitalisation paper). - `paper/main.tex` (UQO cover, template of `Recherche-UQO/_modele-working-paper`) was created on 2026-10-17 from the IRFA manuscript; the pre-existing skeleton (“Preliminary — do not cite”) was discarded. Scientific content is identical to `main_irfa.tex`; only the cover, bibliography style (`aer`) and layout differ. - Three PDFs are committed on purpose: `main.pdf` (working paper), `main_irfa.pdf` (journal), `main_irfa_anon.pdf` (anonymous review copy). - `outputs/estimates/` (707 MB) is excluded from git; regenerate with the pipeline. - Original project brief: `docs/PROMPT_INITIAL_CLAUDE.md`; development conventions: `docs/CLAUDE.md`.