Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Pesenti A. M."'
We consider the problem where an agent aims to combine the views and insights of different experts' models. Specifically, each expert proposes a diffusion process over a finite time horizon. The agent then combines the experts' models by minimising t
Externí odkaz:
http://arxiv.org/abs/2407.04860
Autor:
Pesenti, Silvana M., Vanduffel, Steven
We employ scoring functions, used in statistics for eliciting risk functionals, as cost functions in the Monge-Kantorovich (MK) optimal transport problem. This gives raise to a rich variety of novel asymmetric MK divergences, which subsume the family
Externí odkaz:
http://arxiv.org/abs/2311.12183
Differential sensitivity measures provide valuable tools for interpreting complex computational models used in applications ranging from simulation to algorithmic prediction. Taking the derivative of the model output in direction of a model parameter
Externí odkaz:
http://arxiv.org/abs/2310.06151
We introduce a framework for quantifying propagation of uncertainty arising in a dynamic setting. Specifically, we define dynamic uncertainty sets designed explicitly for discrete stochastic processes over a finite time horizon. These dynamic uncerta
Externí odkaz:
http://arxiv.org/abs/2308.12856
We study a reinsurer who faces multiple sources of model uncertainty. The reinsurer offers contracts to $n$ insurers whose claims follow compound Poisson processes representing both idiosyncratic and systemic sources of loss. As the reinsurer is unce
Externí odkaz:
http://arxiv.org/abs/2308.11828
We define and develop an approach for risk budgeting allocation - a risk diversification portfolio strategy - where risk is measured using a dynamic time-consistent risk measure. For this, we introduce a notion of dynamic risk contributions that gene
Externí odkaz:
http://arxiv.org/abs/2305.11319
Risk budgeting is a portfolio strategy where each asset contributes a prespecified amount to the aggregate risk of the portfolio. In this work, we propose an efficient numerical framework that uses only simulations of returns for estimating risk budg
Externí odkaz:
http://arxiv.org/abs/2302.01196
Stress testing, and in particular, reverse stress testing, is a prominent exercise in risk management practice. Reverse stress testing, in contrast to (forward) stress testing, aims to find an alternative but plausible model such that under that alte
Externí odkaz:
http://arxiv.org/abs/2211.03221
Given an n-dimensional stochastic process X driven by P-Brownian motions and Poisson random measures, we seek the probability measure Q, with minimal relative entropy to P, such that the Q-expectations of some terminal and running costs are constrain
Externí odkaz:
http://arxiv.org/abs/2206.14844
The robustness of risk measures to changes in underlying loss distributions (distributional uncertainty) is of crucial importance in making well-informed decisions. In this paper, we quantify, for the class of distortion risk measures with an absolut
Externí odkaz:
http://arxiv.org/abs/2205.08850