Marcelo Brutti Righi, Fernanda Maria Müller, Marlon Ruoso Moresco
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A risk measurement approach from risk-averse stochastic optimization of score functions
We propose a risk measurement approach for a risk-averse stochastic problem. We provide results that guarantee the existence of a solution to our problem. We characterize and explore the properties of the argmin as a risk measure and the minimum as a generalized deviation measure. We provide an example to demonstrate a specific application of our approach. Additionally, we present a numerical example of the problem's solution to illustrate the usefulness of our approach in risk management analysis.
期刊介绍：
Insurance: Mathematics and Economics publishes leading research spanning all fields of actuarial science research. It appears six times per year and is the largest journal in actuarial science research around the world.
Insurance: Mathematics and Economics is an international academic journal that aims to strengthen the communication between individuals and groups who develop and apply research results in actuarial science. The journal feels a particular obligation to facilitate closer cooperation between those who conduct research in insurance mathematics and quantitative insurance economics, and practicing actuaries who are interested in the implementation of the results. To this purpose, Insurance: Mathematics and Economics publishes high-quality articles of broad international interest, concerned with either the theory of insurance mathematics and quantitative insurance economics or the inventive application of it, including empirical or experimental results. Articles that combine several of these aspects are particularly considered.
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