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).

Working papers

Ince, A., Peri, I., Pesenti, S., Risk Contributions of Lambda Quantiles.

Pesenti, S.M., Reverse Sensitivity Analysis for Risk Modelling.

Pesenti, S. M., Millossovich P. and Tsanakas A., Cascading Credit Risk Defaults.

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.

Published /Accepted papers

Pesenti, S. M., Millossovich P. and Tsanakas A. Cascade Sensitivity Measures , (forthcoming in Risk Analysis), available on SSRN.

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

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.