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- W3008849169 abstract "Coherent risk measures have received increasing attention in recent years among both researchers and practitioners. The problem of estimating a coherent risk measure can be cast as estimating the maximum expected loss taken under a set of probability measures. In this paper, we consider the set of probability measures is finite, and study the estimation of a coherent risk measure via an upper confidence bound (UCB) approach, where samples of the portfolio loss are simulated sequentially from one of the probability measures. We study in depth the so-called Grand Average estimator, and establish statistical guarantees, including its strong consistency, asymptotic normality, and asymptotic mean squared error. We also construct asymptotically valid confidence intervals." @default.
- W3008849169 created "2020-03-06" @default.
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- W3008849169 date "2019-12-01" @default.
- W3008849169 modified "2023-09-27" @default.
- W3008849169 title "An Upper Confidence Bound Approach to Estimating Coherent Risk Measures" @default.
- W3008849169 cites W1625390266 @default.
- W3008849169 cites W2019291268 @default.
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- W3008849169 doi "https://doi.org/10.1109/wsc40007.2019.9004921" @default.
- W3008849169 hasPublicationYear "2019" @default.
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