Journal of Applied Probability

Aggregation of log-linear risks

Paul Embrechts, Enkelejd Hashorva, and Thomas Mikosch


In this paper we work in the framework of a k-dimensional vector of log-linear risks. Under weak conditions on the marginal tails and the dependence structure of a vector of positive risks, we derive the asymptotic tail behaviour of the aggregated risk {and present} an application concerning log-normal risks with {stochastic volatility.

Article information

J. Appl. Probab., Volume 51A (2014), 203-212.

First available in Project Euclid: 2 December 2014

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 60G15: Gaussian processes
Secondary: 60G70: Extreme value theory; extremal processes

Risk aggregation log-linear model subexponential distribution Gumbel max-domain of attraction


Embrechts, Paul; Hashorva, Enkelejd; Mikosch, Thomas. Aggregation of log-linear risks. J. Appl. Probab. 51A (2014), 203--212. doi:10.1239/jap/1417528476.

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