Martin Jehli is a researcher in computational econometrics specializing in Bayesian statistics, probabilistic programming, and quantitative risk modeling. He holds a PhD in Computational Econometrics from the University of Bern. His academic work focuses on uncertainty quantification in economic and financial models, including Bayesian structural VARs, shrinkage methods, and Bayesian approaches to endogeneity treatment in empirical model estimation.
At the World Trade Institute, University of Bern, he works on applied econometric research involving Bayesian methods and computational approaches to policy and market analysis. His broader research agenda sits at the intersection of financial econometrics, portfolio risk, and probabilistic modeling, with a particular interest in settings where parameter uncertainty and latent dynamics materially affect risk estimates.
In parallel with his academic work, he has held quantitative research and strategy roles at UBS and Credit Suisse, where he developed models for strategic asset allocation, capital market assumptions, portfolio risk estimation, and tail-risk-aware optimization. His current research applies Bayesian methods to risk measurement in illiquid assets and private market investments.
