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- W2195890687 abstract "In this paper we deal with the computational burden for estimating quantile based risk measures such as Valueat- Risk using Monte Carlo simulation. The estimator is a conditional expectation type estimator where two stage simulation are needed to compute the risk measure : an outer simulation for risk factors and inner simulation are used to reprice the portfolio conditioned on the risk factors. We propose a new set of algorithm based on a non uniform distribution of the computational budget between risk factors scenarios. The algorithms give more importance to scenario that are more likely to have a direct impact on the value of the estimator. At the end, we demonstrate using simple experimental settings that our set of algorithm outperforms the uniform one and results in a lower variance and bias with the same initial settings and resources." @default.
- W2195890687 created "2016-06-24" @default.
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- W2195890687 date "2015-01-01" @default.
- W2195890687 modified "2023-09-27" @default.
- W2195890687 title "Non-Uniform Nested Simulation Algorithms in Portfolio Risk Measurement" @default.
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- W2195890687 doi "https://doi.org/10.2139/ssrn.2553920" @default.
- W2195890687 hasPublicationYear "2015" @default.
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