Beatrice Foroni

Postodoctoral Researcher at University of Pisa.

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Department of Economics and Management

via Cosimo Ridolfi 10

University of Pisa

I obtained my PhD in Models for Economics and Finance in 2023 at the Sapienza University of Rome (Italy) with a thesis on Hidden Markov models for time series data analysis. I am one of the members of the Quantile Regression Lab and I collaborate with national and international institutions, including the McGill University (Canada), and the Sapienza University of Rome (Italy). From 2023 to 2024 I was a postdoctoral researcher in statistics at the MEMOTEF Department of Sapienza University of Rome (Italy). As of April, I am a postdoctoral researcher at the Economics and Management Department of University of Pisa (Italy). My research interests lie in quantile regression, Hidden Markov models, random forest and graphical models with applications to time series and correlated data.

news

Dec 20, 2025 I will be chairing a session (TBA) at the 19th international CMStatistics 2025 conference hosted by King’s College London.
Jun 15, 2025 I will participate at the invited session ‘Statistical methods for measuring the sustainability’ at the IES 2025.

selected publications

  1. hmgh.png
    Hidden Markov Graphical Models with Generalized Hyperbolic Distributions: A Financial Analysis on Commodities and Green Energy Indexes
    Beatrice Foroni, Luca Merlo, and Lea Petrella
    In Methodological and Applied Statistics and Demography IV: SIS 2024, Short Papers, Contributed Sessions 2, 2025
  2. quantile.png
    Quantile and expectile copula-based hidden Markov regression models for the analysis of the cryptocurrency market.
    Beatrice Foroni, Luca Merlo, and Lea Petrella
    Statistical Modelling, 2024
  3. expectile.jpeg
    Expectile hidden Markov regression models for analyzing cryptocurrency returns
    Beatrice Foroni, Luca Merlo, and Lea Petrella
    Statistics and Computing, 2024
  4. network.png
    The network of commodity risk
    Beatrice Foroni, Giacomo Morelli, and Lea Petrella
    Energy Systems, 2022