Efficient simulation for expectations over the union of half-spaces

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We consider the problem of estimating expectations over the union of half-spaces. Such a problem arises in many applications such as option pricing and stochastic activity networks. More recent applications include systemic risk measurements of financial networks. Assuming that random variables follow a multivariate elliptical distribution, we develop a conditional Monte Carlo method and prove its asymptotic efficiencies. We then demonstrate the numerical performance of the proposed method in three different application areas.
Publisher
ASSOC COMPUTING MACHINERY
Issue Date
2018-07
Language
English
Article Type
Article
Keywords

FINANCIAL NETWORKS; SYSTEMIC RISK; PROBABILITIES

Citation

ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION, v.28, no.3

ISSN
1049-3301
DOI
10.1145/3167969
URI
http://hdl.handle.net/10203/245427
Appears in Collection
IE-Journal Papers(저널논문)
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