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- W2101930638 abstract "In risk theory we often encounter stochastic models containing randomly weighted sums. In these sums, each primary real-valued random variable, interpreted as the net loss during a reference period, is associated with a nonnegative random weight, interpreted as the corresponding stochastic discount factor to the origin. Therefore, a weighted sum of m terms, denoted as , represents the stochastic present value of aggregate net losses during the first m periods. Suppose that the primary random variables are independent of each other with long-tailed distributions and are independent of the random weights. We show conditions on the random weights under which the tail probability of —the maximum of the first n weighted sums—is asymptotically equivalent to that of —the last weighted sum." @default.
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- W2101930638 date "2011-11-01" @default.
- W2101930638 modified "2023-10-01" @default.
- W2101930638 title "The Maximum of Randomly Weighted Sums with Long Tails in Insurance and Finance" @default.
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- W2101930638 doi "https://doi.org/10.1080/07362994.2011.610163" @default.
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