Multivariate Optimized Certainty Equivalent Risk Measures and their Numerical Computation
“We present a framework for constructing multivariate risk measures that is inspired from univariate Optimized Certainty Equivalent (OCE) risk measures. We show that this new class of risk measures verifies the desirable properties such as convexity, monotonocity and cash invariance. We also address numerical aspects of their computations using stochastic algorithms instead of using Monte […]
Corporate Controversies and Financial Stability in the Non-Life Insurance Industry
“Neural networks are suggested for learning a map from d-dimensional samples with any underlying dependence structure to multivariate uniformity in d′ dimensions.” Lire
Dependence model assessment and selection with DecoupleNets
“Neural networks are suggested for learning a map from d’ dimensional samples with any underlying dependence structure to multivariate uniformity in d′ dimensions.” Lire
Reinforcement Learning with Dynamic Convex Risk Measures
“We develop an approach for solving time-consistent risk-sensitive stochastic optimization problems using model-free reinforcement learning (RL). Specifically, we assume agents assess the risk of a sequence of random variables using dynamic convex risk measures. We employ a time-consistent dynamic programming principle to determine the value of a particular policy, and develop policy gradient update rules. […]