activity
20242026
collaborators
Showing stat.APShow all

5 papers · 1 filter

stat.AP2026

Tail Dependence in EU Carbon Markets: Graphical Models of Extremes for EUA Futures

Jan Maciejowski, Manuele Leonelli

Understanding how extreme price movements propagate across financial and energy markets is critical for risk management and regulatory design in the EU Emissions Trading System (EU…

stat.AP2025

Disentangling Spatial and Structural Drivers of Housing Prices through Bayesian Networks: A Case Study of Madrid, Barcelona, and Valencia

Alvaro Garcia Murga, Manuele Leonelli

Understanding how housing prices respond to spatial accessibility, structural attributes, and typological distinctions is central to contemporary urban research and policy. In citi…

stat.AP2025

Uncovering Drivers of EU Carbon Futures with Bayesian Networks

Jan Maciejowski, Manuele Leonelli

The European Union Emissions Trading System (EU ETS) is a key policy tool for reducing greenhouse gas emissions and advancing toward a net-zero economy. Under this scheme, tradeabl…

stat.AP2024

Predicting and understanding shooting performance in professional biathlon: A Bayesian approach

Manuele Leonelli

Biathlon is a unique winter sport that combines precision rifle marksmanship with the endurance demands of cross-country skiing. We develop a Bayesian hierarchical model to predict…

stat.AP2024

An analysis of factors impacting team strengths in the Australian Football League using time-variant Bradley-Terry models

Carlos Rafael Gonzalez Soffner, Manuele Leonelli

Australian Rules Football is a field invasion game where two teams attempt to score the highest points to win. Complex machine learning algorithms have been developed to predict ma…