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GSF-6053 Financial Econometrics I — matériel de cours (Université Laval).

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# GSF-6053 — Financial Econometrics I (Économétrie Financière)

Author / Auteur : Simon-Pierre Boucher 📧 Contact : contact@spboucher.ai 🏛️ Département de finance, assurance et immobilier — Faculté des sciences de l'administration, Université Laval

LaTeX Stata Course Level Credits Language

# 📚 Course Description

This repository contains the complete teaching material for GSF-6053 — Financial Econometrics I, a graduate course (Hiver 2022) that introduces students to the practical aspects of econometric methods and estimation techniques as applied in finance. All lecture decks are written in LaTeX (Beamer), in French, and each folder ships both the .tex source and the compiled .pdf.

The course emphasizes modeling challenges specific to financial applications: OLS regression, maximum likelihood, hypothesis testing, heteroskedasticity, autocorrelation, panel data models, and time-series analysis (ARMA/ARIMA, unit roots, cointegration), with hands-on Stata application sessions.

# 📋 Prerequisites

A basic understanding of statistics and linear algebra is recommended to engage fully with the course material.

# 🗂️ Detailed Content by Session

# Section 02 — Régression et Moindres Carrés Ordinaires (MCO / OLS)

Session Folder Topics
Séance 2 Séance 2/ Modèle de régression, dérivation des MCO (sommation et format matriciel), exemples numériques, nuages de points et impact de la variance des erreurs
Séance 3 Séance 3/ Maximum de vraisemblance (MLE), MLE pour le modèle de régression linéaire, estimateur sans biais de la variance, propriétés des estimateurs MLE et MCO
Séance 4 Séance 4/ Analyse de variance, R², R² ajusté, tests d'hypothèses, contraintes linéaires, tests de Wald, LR (ratio de vraisemblance) et LM (multiplicateur de Lagrange), liens entre F, Wald, LR et LM
Séance 5 Séance 5/ Suite de la Section 02 (PDF compilé fourni)

# Section 03 — Extensions au modèle linéaire simple

Session Folder Topics
Séance 6 Séance 6/ Hétéroscédasticité : définition, conséquences et tests diagnostiques (Breusch-Pagan, White)
Séance 7 Séance 7/ Autocorrélation des erreurs : diagnostic (Durbin-Watson), transformations de Cochrane-Orcutt et Prais-Winsten, estimateur robuste de Newey-West

# Section 04 — Les modèles panels

Session Folder Topics
Séance 8 Séance 8/ Avantages des données panel, notation générale, modèle pooled, modèle à effets fixes, Least Squares Dummy Variable (LSDV)
Séance 9 Séance 9/ Modèle empilé, within-group estimator, modèle à effets aléatoires, transformation de Fuller-Battese

# Section 05 — Les séries chronologiques

Session Folder Topics
Séance 10 Séance 10/ Séries stationnaires et non stationnaires, opérateur de retard, autocovariance et autocorrélation (ACF/PACF), équations de Yule-Walker, modèle AR(1)
Séance 11 Séance 11/ Estimation des moments, tests de bruit blanc (Box-Pierce, Ljung-Box), tests de racine unitaire (Dickey-Fuller augmenté, Phillips-Perron), cointégration et tests de cointégration
Séance 12 Séance 12/ Processus autorégressifs (AR), moyennes mobiles (MA), ARMA(p,q), ARIMA(p,d,q), méthodologie Box-Jenkins

# 💻 Stata Application Sessions

Session Folder Topics
STATA S02 STATA_S02/ Application Stata de la Section 02 : statistiques descriptives, régressions MCO, t-test, F-test, analyse des résidus (avec captures d'écran des sorties Stata)
STATA S03 STATA_S03/ Application Stata de la Section 03 : détection et correction de l'hétéroscédasticité (tests de Breusch-Pagan et de White, tables du χ²)

# 📁 Repository Structure

text
GSF6053/
├── README.md                  ← this file
├── Séance 2/ … Séance 12/     ← lecture decks (Beamer .tex + compiled .pdf + build files)
│   └── GSF6053_S<n>.tex/.pdf
├── STATA_S02/                 ← Stata lab, Section 02 (deck + Stata output screenshots .png)
│   └── GSF6053_STATA_02.tex/.pdf
└── STATA_S03/                 ← Stata lab, Section 03 (deck + Stata output screenshots .png)
    └── GSF6053_STATA_03.tex/.pdf

Each session folder contains:

  • .tex — the Beamer source (UTF-8, French)
  • .pdf — the compiled slide deck, ready to use
  • .png / .jpg — figures, regression outputs, statistical tables referenced by the deck
  • Auxiliary LaTeX build files (.aux, .log, .nav, .out, .snm, .toc, .synctex.gz)

# 🔨 Building the Slides

All decks compile with a standard TeX distribution (TeX Live / MacTeX). From a session folder:

bash
cd "Séance 2"
pdflatex GSF6053_S2.tex
pdflatex GSF6053_S2.tex   # second pass for the table of contents / navigation

Or compile everything at once from the repository root:

bash
for d in "Séance "*/ STATA_S0*/; do
  (cd "$d" && f=$(ls *.tex 2>/dev/null) && [ -n "$f" ] && pdflatex -interaction=nonstopmode "$f" && pdflatex -interaction=nonstopmode "$f")
done

Requirements: beamer, graphicx, inputenc (utf8) — all included in any full TeX Live / MacTeX install. Images must stay next to their .tex file (they are referenced by relative path).

# 🎓 Learning Outcomes

By the end of this course, students will be able to:

  • Derive and apply the OLS and maximum-likelihood estimators to financial data;
  • Perform and interpret hypothesis tests (t, F, Wald, LR, LM);
  • Diagnose and correct heteroskedasticity and autocorrelation;
  • Estimate panel-data models (pooled, fixed effects, random effects);
  • Model financial time series (AR, MA, ARMA, ARIMA), test for unit roots and cointegration, and apply the Box-Jenkins methodology;
  • Implement all of the above in Stata.

# 🤝 Contributing

This repository is primarily for educational purposes. If you find any errors or have suggestions for improvements, feel free to open an issue or submit a pull request.

# 📄 License & Usage

This material is intended for students enrolled in the GSF-6053 course and for educational use. For any other use, please contact the author.

Simon-Pierre Boucher — 📧 contact@spboucher.ai

⭐ Star this repository if you find it helpful! ⭐