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- W2103187733 abstract "The paper derives many existing risk measures and premium principles by minimizing a Markov bound for the tail probability. Our approach involves two exogenous functions v ( S ) and φ ( S , π ) and another exogenous parameter α ≤ 1. Minimizing a general Markov bound leads to the following unifying equation: E [ φ ( S , π )] = αE [ v ( S )]. For any random variable, the risk measure π is the solution to the unifying equation. By varying the functions φ and v , the paper derives the mean value principle, the zero-utility premium principle, the Swiss premium principle, Tail VaR, Yaari's dual theory of risk, mixture of Esscher principles and more. The paper also discusses combining two risks with super-additive properties and sub-additive properties. In addition, we recall some of the important characterization theorems of these risk measures." @default.
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- W2103187733 date "2003-11-01" @default.
- W2103187733 modified "2023-10-16" @default.
- W2103187733 title "A Unified Approach to Generate Risk Measures" @default.
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- W2103187733 doi "https://doi.org/10.1017/s0515036100013428" @default.
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