spb/phd_thesis Public
PhD thesis — Three essays on high-frequency return and volatility dynamics in commodities and financial futures markets (Université Laval).
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1# 🎓 Three Essays on High-Frequency Return and Volatility Dynamics in Commodities and Financial Futures Markets23<p align="center">4 <img alt="PhD" src="https://img.shields.io/badge/PhD-Finance-8B0000?style=for-the-badge&logo=googlescholar&logoColor=white">5 <img alt="University" src="https://img.shields.io/badge/Universit%C3%A9-Laval-E30513?style=for-the-badge&logo=academia&logoColor=white">6 <img alt="LaTeX" src="https://img.shields.io/badge/Made%20with-LaTeX-008080?style=for-the-badge&logo=latex&logoColor=white">7 <img alt="Status" src="https://img.shields.io/badge/D%C3%A9p%C3%B4t-2026-blueviolet?style=for-the-badge">8</p>910<p align="center">11 <img alt="Chapters" src="https://img.shields.io/badge/chapters-3-success?style=flat-square">12 <img alt="Pages" src="https://img.shields.io/badge/thesis-188%20pages-informational?style=flat-square">13 <img alt="Data" src="https://img.shields.io/badge/data-high--frequency%20(1--5%20min)-orange?style=flat-square">14 <img alt="Markets" src="https://img.shields.io/badge/markets-energy%20%7C%20metals%20%7C%20equity%20%7C%20rates-yellow?style=flat-square">15 <img alt="Compiled" src="https://img.shields.io/badge/latexmk-0%20errors%20%7C%200%20warnings-brightgreen?style=flat-square">16</p>1718> **Doctoral thesis by articles (thèse par articles)** — Simon-Pierre Boucher,19> Faculté des sciences de l'administration (FSA), Université Laval.20> Co-authors: Marie-Hélène Gagnon & Gabriel J. Power.2122---2324## 🗂️ Repository Contents2526| 📁 Folder | 📄 Content | 🏷️ Status |27|---|---|---|28| [`phd_chap1_20260731/`](phd_chap1_20260731/) | 🛢️ **Chapter 1** — Speculative trading in energy markets | 🟢 Revised for *The Energy Journal* |29| [`phd_chap2_20260731/`](phd_chap2_20260731/) | 📈 **Chapter 2** — iNAV & commodity volatility transmission | 🟡 Submission version, *Journal of Futures Markets* |30| [`PHD_chapitre3_theses_20260731/`](PHD_chapitre3_theses_20260731/) | 🏦 **Chapter 3** — FOMC tone & novelty (NLP) | 🟡 Manuscript (2026-03-06) |31| [`these-ulaval/`](these-ulaval/) | 📕 **Global thesis** — full ULaval document (`ulthese`/memoir) | 🟢 Compiles clean, 188 pp. |3233---3435## 🛢️ Chapter 1 — Speculative Trading in Energy Markets: Evidence from Macroeconomic Surprises363738394041**Question:** Does speculative trading amplify or dampen the impact of macroeconomic news on commodity futures?4243Using high-frequency data and 26 macroeconomic announcement releases, this essay measures how the intensity of speculation (an NLS proxy built from the CFTC disaggregated Commitments of Traders — money managers vs. swap dealers) conditions the reaction of energy (crude oil, natural gas) and metals (gold, silver, copper, palladium) futures to standardized macro surprises.4445**Key findings** 🎯46- 🧯 Increased speculative trading **dampens** the impact of macro surprises on price drift, volatility, and bid-ask spreads.47- 💧 Speculators **improve liquidity and price discovery** while reducing volatility.48- ⚡ The damping effect is stronger for **procyclical commodities** (oil, gas) than for safe havens (gold).49- 👤 The beneficial effects are driven by **money managers**, not swap dealers.5051📦 *In the folder:* `main.tex` (monolithic article), `tables.tex` (14 tables), `figures.tex` (6 figures), COVID & ZLB appendices, `master.bib`.5253---5455## 📈 Chapter 2 — Seeing Through the ETF: Indicative NAV and Commodity Volatility Transmission565758596061**Question:** How does volatility flow between commodity ETFs and their underlying assets — and what does the intraday **indicative NAV (iNAV)** reveal that daily data cannot?6263This essay builds a **novel minute-level iNAV dataset** for four single-commodity ETFs (gold, silver, oil, natural gas), decomposes realized variance into continuous and jump components (Barndorff-Nielsen–Shephard), and estimates HAR-X / HAR-CJ-X models at 1, 5 and 30 minutes plus a Bayesian VAR.6465**Key findings** 🎯66- 🪞 The iNAV gives a **sharper image** of the ETF–underlying volatility relationship.67- 💥 Transmission runs primarily through **jumps**, not diffusion.68- ⏱️ **Sampling frequency matters**: 1-minute estimates are up to **2× larger** than 30-minute ones.69- 🥇 Precious metals: **unidirectional** (iNAV → ETF, passive arbitrage); ⛽ energy: **bidirectional & asymmetric**.7071📦 *In the folder:* `main.tex` + `sections/` (intro, data, methods, results, conclusion), 13 tables, 8 figures (RV & IRF plots), `master.bib`, compiled `main.pdf`.7273---7475## 🏦 Chapter 3 — Returns and Volatility Around FOMC Announcements: A High-Frequency Analysis of Policy Tone and Novelty76777879%20%C2%B7%20Jord%C3%A0%20LPs%20%C2%B7%20panels-9cf?style=flat-square)808182**Question:** When the Fed speaks, what moves markets — **what** it says (tone) or **how new** it is (novelty)?8384FOMC statements (217 releases, 2000–2025) are decomposed into **policy tone** (hawkish/dovish) and **informational novelty** using a dual-model NLP ensemble (MiniLM + BERT, TSDAE+MNRL fine-tuning, PCA-based reference selection), then linked to 1-minute futures data via event regressions, minute-level panels and Jordà local projections, with placebo tests and five inference methods.8586**Key findings** 🎯87- 🗣️ **Tone predicts directional returns**: a 1σ dovish shift → equity gains building to ≈ **+12 bps within two hours**.88- 🆕 **Novelty predicts volatility**: the stance × novelty interaction on VIX persists 5–120 min (*t* = −5.06).89- 📊 Stance moves realized volatility in **6 of 7 contracts** (*p* < 0.01).90- 🧪 Pre-announcement placebos are null — effects are announcement-driven.9192📦 *In the folder:* `chapitre3.tex` + `sections/`, 24 tables, 19 figures, mathematical proofs appendix, `master.bib`, compiled `chapitre3.pdf`.9394---9596## 📕 Global Thesis — `these-ulaval/`9798-008080?style=flat-square)99100101102The full **thesis-by-articles document** assembled for the FESP (Faculté des études supérieures et postdoctorales) requirements:103104- 🇫🇷 French front matter (résumé, remerciements, avant-propos) + 🇬🇧 English abstracts per chapter105- 📖 General introduction · 3 chapters · general conclusion · appendices A–B (Chapter 3 proofs & extras)106- 📚 Consolidated bibliography (`bib/these.bib`, 271 unique keys merged from the three articles)107- 🧾 [`INVENTAIRE.md`](these-ulaval/INVENTAIRE.md) — exhaustive audit of the sources, conflicts and every mechanical fix (labels prefixed `chN:`, package conflicts, BibTeX dedup…)108109```bash110cd these-ulaval111latexmk # → main.pdf (0 errors, 0 undefined refs, 0 missing citations)112```113114---115116## 🧭 Thread of the Thesis117118The three essays share one lens: **high-frequency data around information events**.119120```121 🛢️ Ch. 1 📈 Ch. 2 🏦 Ch. 3122 macro announcements → ETF ↔ underlying → FOMC statements123 × speculation volatility tone × novelty124 (who trades matters) transmission (what & how new)125 └──────────── returns · volatility · liquidity ────────────┘126```127128---129130## ✍️ Authors131132| | |133|---|---|134| **Simon-Pierre Boucher** | PhD candidate in Finance, Université Laval — [simon-pierre.boucher.1@ulaval.ca](mailto:simon-pierre.boucher.1@ulaval.ca) |135| **Marie-Hélène Gagnon** | Professor of Finance, CRREP, Université Laval |136| **Gabriel J. Power** | IG Wealth Management Chairholder, Professor of Finance, CRREP & CRIB, Université Laval |137138> 🙏 Funding: Social Sciences and Humanities Research Council (SSHRC) & Chaire Industrielle-Alliance Groupe financier.139140---141142<p align="center">143 <sub>📌 Folder suffix <code>20260731</code> = frozen snapshot of each article (July 31, 2026 versions). Sources are never edited in place — all thesis adaptations live in <code>these-ulaval/</code>.</sub>144</p>145