Journal ArticleDOI
Linear-time accurate lattice algorithms for tail conditional expectation
Bryant Chen,William W. Y. Hsu,William W. Y. Hsu,Jan-Ming Ho,Jan-Ming Ho,Ming-Yang Kao +5 more
- Vol. 3, pp 87-140
TLDR
A key finding is that combining the techniques of tilting lattice, extrapolation, and fractional steps substantially increases speed and accuracy.Abstract:
This paper proposes novel lattice algorithms to compute tail conditional expectation of European calls and puts in linear time. We incorporate the technique of prefix-sum into tilting, trinomial, and extrapolation algorithms as well as some syntheses of these algorithms. Furthermore, we introduce fractional-step lattices to help reduce interpolation error in the extrapolation algorithms. We demonstrate the efficiency and accuracy of these algorithms with numerical results. A key finding is that combining the techniques of tilting lattice, extrapolation, and fractional steps substantially increases speed and accuracy.read more
Citations
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Journal ArticleDOI
Multivariate tail conditional expectation for elliptical distributions
TL;DR: In this article, a multivariate tail conditional expectation (MTCE) risk measure for the elliptical family of distributions is introduced and an explicit closed-form expression for this risk measure is derived.
Journal ArticleDOI
Tail conditional moments for elliptical and log-elliptical distributions
TL;DR: In this paper, the authors provided the tail conditional moments for the class of elliptical distributions, which was introduced in Kelker (1970) and was widely discussed in Gupta et al. (2013).
References
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