Linda Mhalla

Linda Mhalla is a Researcher and Statistical consultant at the Swiss Federal Institute of Technology (EPFL) in the Department of Mathematics, School of Basic Sciences. She has also served as a Scientific collaborator at HEC Lausanne, Department of Operations, and as a Postdoctoral Fellow at HEC Montreal, Department of Decision Sciences.

• PhD in Statistics, University of Geneva, 2018
• MSc in Statistics and Financial Mathematics, EPFL, 2014
• BSc in Mathematics, EPFL, 2012

Her research focuses on extreme value theory and its applications to environmental and financial data, including:

• Quantitative risk modeling
• Smooth modeling techniques
• Causal inference in extreme events
• Climate risk assessment
• GAM (Generalized Additive Models) methodology
• Statistical consulting for environmental and financial sectors

Linda's publications highlight the application of extreme value theory to diverse domains such as finance, environmental science, and climate modeling. Her work includes modeling extremal dependence through nonlinear regression, causal inference in river discharge data, and Bayesian spatiotemporal approaches for extreme hot-spots. Collaborations span institutions like HEC Lausanne, HEC Montreal, and University of Geneva.

• Extremal Connectedness and Systemic Risk of Hedge Funds (Mar 5, 2020)
• Causal mechanism of extreme river discharges (Jul 1, 2019)
• Tail risk and style dependence in the fund industry (Jun 21, 2019)
• Quantile-based approaches for tail causality (Jun 13, 2019)
• Exceedance-based nonlinear regression of residual dependence (Dec 16, 2017)
• Regression type models for extremal dependence (Jun 26, 2017)
• Semi-parametric estimation of non-stationary Pickands dependence functions (Apr 25, 2016)