LinkedIn AMS MathSciNet Author Profile
Teaching and Supervision

Online Teaching Material

  • 2010-: Institut Mines-Télécom Atlantique, Brest, lectures (in French) on nonstationary processes (Mathematical and Computational Engineering Lectures).
    My 3rd year lectures on nonstationary processes for the academic year 2020-2021 will take place in March 2021. They have been quite rewritten from scratch, after reviewing a long series of papers and books (over 70 and counting) on these issues for Mathematical Reviews®. The new section on deep learning and AI is obviously expanding. The writing of the book supporting these lectures is in progress.
    List of past lectures for the academic year 2020-2021:
    • Lecture 1 (Monday 8th March 2021): Volatility models. GARCH model: definition, properties, dependence structure, QML estimation. Slides
    • Lecture 2 (Tuesday 9th March 2021): Exponential GARCH model. Bootstrap methods and their application to model-free prediction and inference of univariate models. Multivariate models. Change-point models. Slides
    • Lecture 3 (Monday 22th March 2021): Long-range dependent and multifractal volatility models. Wavelet analysis of volatility processes. Slides
    • Lecture 4 (Tuesday 23th March2021): Volatility estimation of high frequency time series. Deep Learning: convolutional, recurrent and hybrid architectures, with the PyTorch and libraries. Slides
  • 2009: Aarhus University, PhD lectures, based on the draft version of the book Large Sample Inference for Long Memory Processes (2012) Imperial College Press. In 2013, I wrote the review of this book for Mathematical Reviews®. If you are a MathSciNet subscriber, you could read this review from my  author profile
    Additional material not covered in that book: Slides
  • 2006-2007: Ensae, lectures (in French) on Long-range dependence and change-points, Applications to univariate and multivariate financial time series: Leçon 1 : Processus fortement dépendants, Transparents ; Leçon 2 : Tests de détection de longue portée et estimateurs du paramètre de longue portée, Transparents; Leçon 3 : Tests de détection de ruptures, Transparents; Leçon 4 : Méthodes statistiques robustes aux ruptures, Transparents.
  • 1993-1996: Lectures on optimization techniques with Maple. I have typed a 200 pages document.

Other Teaching and Supervision Resources

Updated January 2, 2021.