163 citations · 237 across the 9 of their papers we have counts for
11 papers
Risk exchange under infinite-mean Pareto models
Yuyu Chen, Paul Embrechts, Ruodu Wang
We study the optimal decisions and equilibria of agents who aim to minimize their risks by allocating their positions over extremely heavy-tailed (i.e., infinite-mean) and possibly…
An unexpected stochastic dominance: Pareto distributions, dependence, and diversification
Yuyu Chen, Paul Embrechts, Ruodu Wang
We find the perhaps surprising inequality that the weighted average of independent and identically distributed Pareto random variables with infinite mean is larger than one such ra…
Robustness in the Optimization of Risk Measures
Paul Embrechts, Alexander Schied, Ruodu Wang
We study issues of robustness in the context of Quantitative Risk Management and Optimization. We develop a general methodology for determining whether a given risk measurement rel…
Data-driven polynomial chaos expansion for machine learning regression
E. Torre, S. Marelli, P. Embrechts +1
We present a regression technique for data-driven problems based on polynomial chaos expansion (PCE). PCE is a popular technique in the field of uncertainty quantification (UQ), wh…
A general framework for data-driven uncertainty quantification under complex input dependencies using vine copulas
E. Torre, S. Marelli, P. Embrechts +1
Systems subject to uncertain inputs produce uncertain responses. Uncertainty quantification (UQ) deals with the estimation of statistics of the system response, given a computation…
Bernoulli and tail-dependence compatibility
Paul Embrechts, Marius Hofert, Ruodu Wang
The tail-dependence compatibility problem is introduced. It raises the question whether a given -matrix of entries in the unit interval is the matrix of pairwise tail-de…