Linear-time accurate lattice algorithms for tail conditional expectation

Bryant Chen (), William W.Y. Hsu (), Jan-Ming Ho and Ming-Yang Kao ()
Additional contact information
Bryant Chen: Department of Computer Science, University of California at Los Angeles, Postal: Department of Computer Science, University of California at Los Angeles, Los Angeles, CA, USA
William W.Y. Hsu: Department of Computer Science and Engineering, National Taiwan Ocean University, Postal: Department of Computer Science and Engineering, National Taiwan Ocean University, Keeling, Taiwan
Jan-Ming Ho: Research Center for Information Technology Innovation, Postal: Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan
Ming-Yang Kao: Department of Electrical Engineering & Computer Science, Northwestern University, Postal: Department of Electrical Engineering & Computer Science, Northwestern University, Evanston, IL, USA

Algorithmic Finance, 2014, vol. 3, issue 1-2, 87-140

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.

Keywords: Value-at-Risk; tail conditional expectation; lattice; prefix sum; extrapolation; fractional steps (search for similar items in EconPapers)
JEL-codes: C00 C01 C02 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:ris:iosalg:0010

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