My research interests include, but is not limited to, quantitative risk management, dependence uncertainty, sensitivity analysis for insurance, risk measures, stress testing and systemic risk.

My research is supported by Natural Sciences and Engineering Research Council of Canada (DGECR-2020-00333, RGPIN-2020-04289).

Submitted papers

Pesenti, S.M., Wang, Q., Wang, R. Optimizing distortion riskmetrics with distributional uncertainty, available on SSRN.

Pesenti, S.M and Jaimungal, S. Portfolio Optimisation within a Wasserstein Ball, available on SSRN.

Bernard, C., Pesenti S., Vanduffel, S. Robust Distortion Risk Measures, available on SSRN.

Pesenti, S. M., Bettini, A., Millossovich, P., Tsanakas A. Scenario Weights for Importance Measurement (SWIM) – an R package for sensitivity analysis , available on SSRN.

Pesenti, S. M., Millossovich P. and Tsanakas A. Cascade Sensitivity Measures , available on SSRN.

Published /Accepted papers

Pesenti, S. M., Millossovich P. and Tsanakas A., 2019. Reverse sensitivity testing: What does it take to break the model? European Journal of Operational Research, 274(2), pp. 654–670

Pesenti, S. M., Millossovich P. and Tsanakas A., 2018. Euler allocations in the presence of non-linear reinsurance: comment on Major (2018). Insurance, Mathematics and Economics, 83, pp. 29–31.

Pesenti, S. M., Millossovich P. and Tsanakas A., 2016. Robustness regions for measures of risk aggregation. Dependence Modeling, 4(1), pp. 348–367.

Software

Pesenti, S. M., Bettini, A., Millossovich, P., Tsanakas A. (2020). SWIM: Scenario Weights for Importance Measurement. R package version 0.2.0.