A new risk management model using quantile-based risk measure, with applications to non-normal distributions

Authors:
Maria Tudor;Silvia Dedu
Affiliations:
Department of Applied Mathematics, The Bucharest University of Economics, Bucharest, Romania;Department of Applied Mathematics, The Bucharest University of Economics
Venue:
BICA'12 Proceedings of the 5th WSEAS congress on Applied Computing conference, and Proceedings of the 1st international conference on Biologically Inspired Computation
Year:
2012

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Parameter and quantile estimation for the generalized pareto distribution

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Abstract

In this paper we propose a new risk optimization model, based on Limited Value-at-Risk measure. We determine the analytical form of the LVaR measure corresponding to the aggregate loss in a stoploss reinsurance model and formulate an optimization problem using this new risk measure. Necessary and sufficient conditions for the existence of the optimal solution are derived. The solution obtained extends the results of [4] and [5]. The Limited Value-at-Risk measure can be successfully used to evaluate risk and to solve optimization problems in the case of non-normal distributions. The results obtained are illustrated using simulations. Computational results are provided.