This paper studies the approximation of extreme quantiles of random sums of heavy-tailed random variables, or more specifically, subexponential random variables. A key application of this approximation is the calculation of operational VaR (value at risk) for financial institutions, to determine...

The class of spectrally positive Lévy processes is a frequent choice for modelling loss processes in areas such as insurance or operational risk. Dependence between such processes (for example, between different lines of business) can be modelled with Lévy copulas. This approach is a...

Models of dependence in asset returns with non-Gaussian marginals are investigated on ETF daily return data. The first is a full rank Gaussian copula. The second is a linear mixture of independent Lévy processes. The third correlates Gaussian components in a variance gamma representation. On a...

Realized variance can be broken down into continuous volatility and jumps. We show that these two components have very different predictive powers on future long-term excess stock market returns. While continuous volatility is a key driver of medium to long-term risk-return relationships, jumps...

We study how changes to the informativeness of signals in Bayesian games and single‐agent decision problems affect the distribution of equilibrium actions. Focusing on supermodular environments, we provide conditions under which a more precise private signal for one agent leads to an...