# 🌐 Intraday Volatility Transmission Across Asset Classes

UQO Working Paper No. 6 — A Connectedness Analysis of Equities, Fixed Income, Commodities, and Cryptocurrencies

TL;DR — Daily realized volatility is built from 5-minute bars (2008–2026) for 10 instruments spanning equity futures (ES, NQ), FX (EURUSD, USDJPY, GBPUSD), commodities (GC, CL), crypto (BTC, ETH) and the VIX, and fed to the Diebold–Yilmaz (2012) connectedness framework (VAR(4), 10-day GFEVD). Total spillover is 55.4 %; ES and NQ are the dominant transmitters (+26.8 / +19.7 pp net), the VIX the main receiver (−23.4 pp), and crypto stays largely isolated (own-shock share > 77 %). Connectedness peaks at 81.6 % in February 2018; during COVID USD/JPY becomes the top shock originator and in the 2022 hiking cycle Bitcoin turns into a net transmitter (+7.9 pp).

# 📌 Status

# 🎯 What this paper does

The paper measures how volatility shocks travel across asset classes at the daily frequency, using realized volatility computed from intraday data rather than low-frequency proxies. Ten representative instruments are followed over 2008–2026 and the generalized forecast-error variance decomposition of a VAR is used to build directional, net and total spillover indices:

RV_{i,t} = Σ_k r²_{i,t,k}  (5-min returns)      →  VAR(4) on log RV  →  GFEVD(H = 10)  →  TSI, TO, FROM, NET

Full-sample, rolling (200-day) and regime-specific (pre-COVID, COVID crash, 2022 rate hikes) decompositions are complemented by a trading-session analysis (Asian / European / U.S. hours) and Granger-causality tests between equity futures, the VIX and crypto.

# 🏆 Headline results

# 🗂 Repository layout

intraday-volatility-connectedness/
├── data/
│   ├── raw/                  # futures_5min / fx_5min / crypto_5min .duckdb (see data/raw/README.md) — not committed
│   └── processed/
├── scripts/
│   └── 01_analysis.py        # RV construction, VAR/GFEVD, rolling & regime analysis, sessions, Granger, figures
├── results/                  # table1…table4 CSV, daily_rv_all.csv, rolling_total_spillover.csv
├── figures/                  # fig1…fig7 PNG (copied into paper/figures)
└── paper/                    # main.tex + sections/ + appendix/ → main.pdf

# 🚀 Quick start

python3 -m pip install -r requirements.txt
# place the three DuckDB files in data/raw/ (or export WP6_DATA_DIR=/path/to/dbs)
python3 scripts/01_analysis.py      # ≈ 10 min, ≈ 8 GB RAM (loads 235 M bars)
cd paper && make                    # latexmk → main.pdf

# 🗃 Data

5-minute OHLCV bars from FirstRate Data, 2008–2026: CME/CBOE continuous futures (ES, NQ, GC, CL, VX), spot FX (EURUSD, USDJPY, GBPUSD) and crypto spot (BTC, ETH). Realized volatility is the daily sum of squared 5-minute log returns; sessions are defined in exchange time. See data/raw/README.md.

# 🔬 Methodology

1. Realized volatility per instrument and day from 5-minute closes (scripts/01_analysis.py, §1–2).
2. Diebold–Yilmaz (2012) connectedness: VAR(4) on log RV, generalized FEVD at H = 10, total / directional / net spillovers (§3).
3. Rolling 200-day windows for time variation (§4).
4. Regime sub-samples: pre-COVID, COVID crash, 2022 rate hikes (§5).
5. Trading sessions: hourly volatility profiles and session-level Granger causality (§6).
6. Network graph of net pairwise spillovers (§7).

# 🖼 Figures & tables inventory

Tables (results/*.csv): descriptive statistics, full connectedness table, three regime tables, session Granger tests.

# ⚠️ Limitations

• Continuous futures series splice contracts at roll dates; roll returns are not removed.
• Crypto trades 24/7 while futures and FX have session gaps, so daily RV windows differ across classes.
• The GFEVD depends on the VAR lag (4) and horizon (10); robustness to these choices is reported in the appendix only.

# 📝 Citation

@techreport{boucher2026connectedness,
  author      = {Boucher, Simon-Pierre},
  title       = {Intraday Volatility Transmission Across Asset Classes: A Connectedness Analysis of Equities, Fixed Income, Commodities, and Cryptocurrencies},
  institution = {Universit\'e du Qu\'ebec en Outaouais, D\'epartement des sciences administratives},
  type        = {Working Paper},
  number      = {6},
  year        = {2026},
  month       = {May}
}

# 👤 Author & contact

Simon-Pierre Boucher — Département des sciences administratives, Université du Québec en Outaouais (UQO), Gatineau, QC. 📧 simon-pierre.boucher@uqo.ca

# 🗒 Notes

• References are typeset with an inline thebibliography (paper/sections/references.tex, apalike style), not a .bib file — kept as is (deviation from HARMONISATION.md §3).
• The original flat manuscript (paper.tex, May 2026) is archived in Recherche-UQO/_archives/versions-mai-2026/intraday-volatility-connectedness--flat-tex-20260520/.