Linear-time accurate lattice algorithms for tail conditional expectation

Bryant Chen, William W.Y. Hsu*, Jan Ming Ho, Ming-Yang Kao

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)87-140
Number of pages54
JournalAlgorithmic Finance
Volume3
Issue number1-2
DOIs
StatePublished - Jan 1 2014

Fingerprint

Conditional Expectation
Linear Time
Tail
Extrapolation
Fractional Step
Tilting
Interpolation Error
Prefix
Interpolation
Conditional tail expectation
Synthesis
Numerical Results
Demonstrate

Keywords

  • Value-at-Risk
  • extrapolation
  • fractional steps
  • lattice
  • prefix sum
  • tail conditional expectation

ASJC Scopus subject areas

  • Finance
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Computational Mathematics

Cite this

Chen, Bryant ; Hsu, William W.Y. ; Ho, Jan Ming ; Kao, Ming-Yang. / Linear-time accurate lattice algorithms for tail conditional expectation. In: Algorithmic Finance. 2014 ; Vol. 3, No. 1-2. pp. 87-140.
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Linear-time accurate lattice algorithms for tail conditional expectation. / Chen, Bryant; Hsu, William W.Y.; Ho, Jan Ming; Kao, Ming-Yang.

In: Algorithmic Finance, Vol. 3, No. 1-2, 01.01.2014, p. 87-140.

Research output: Contribution to journalArticle

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