By the same authors

Computational Methods for Derivatives with Early Exercise Features

Research output: Chapter in Book/Report/Conference proceedingChapter

Standard

Computational Methods for Derivatives with Early Exercise Features. / Chiarella, Carl; Kang, Boda; Meyer, G.H.; Ziogas, A.

Handbook of Computational Economics. ed. / Karl Schmedders; Kenneth L. Judd. Vol. 3 Elsevier, 2014. p. 225-275.

Research output: Chapter in Book/Report/Conference proceedingChapter

Harvard

Chiarella, C, Kang, B, Meyer, GH & Ziogas, A 2014, Computational Methods for Derivatives with Early Exercise Features. in K Schmedders & KL Judd (eds), Handbook of Computational Economics. vol. 3, Elsevier, pp. 225-275. https://doi.org/10.1016/B978-0-444-52980-0.00005-0

APA

Chiarella, C., Kang, B., Meyer, G. H., & Ziogas, A. (2014). Computational Methods for Derivatives with Early Exercise Features. In K. Schmedders, & K. L. Judd (Eds.), Handbook of Computational Economics (Vol. 3, pp. 225-275). Elsevier. https://doi.org/10.1016/B978-0-444-52980-0.00005-0

Vancouver

Chiarella C, Kang B, Meyer GH, Ziogas A. Computational Methods for Derivatives with Early Exercise Features. In Schmedders K, Judd KL, editors, Handbook of Computational Economics. Vol. 3. Elsevier. 2014. p. 225-275 https://doi.org/10.1016/B978-0-444-52980-0.00005-0

Author

Chiarella, Carl ; Kang, Boda ; Meyer, G.H. ; Ziogas, A. / Computational Methods for Derivatives with Early Exercise Features. Handbook of Computational Economics. editor / Karl Schmedders ; Kenneth L. Judd. Vol. 3 Elsevier, 2014. pp. 225-275

Bibtex - Download

@inbook{8677fefbff9f469ab8db69c2a75bf117,
title = "Computational Methods for Derivatives with Early Exercise Features",
abstract = "In this paper we consider various computational methods for pricing American style derivatives. We do so under both jump diffusion and stochastic volatility processes. We consider integral transform methods, the method of lines, operator-splitting, and the Crank-Nicolson scheme, the latter being used to generate the benchmark solution. Overall, we find that the method of lines approach is quite competitive with other methods for the problems considered in this paper. As one goes to higher dimensions it may be necessary to use methods such as the sparse grid approach.",
author = "Carl Chiarella and Boda Kang and G.H. Meyer and A. Ziogas",
year = "2014",
month = jan,
doi = "10.1016/B978-0-444-52980-0.00005-0",
language = "English",
isbn = " 978-0-444-52980-0",
volume = "3",
pages = "225--275",
editor = "Karl Schmedders and Judd, {Kenneth L.}",
booktitle = "Handbook of Computational Economics",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Download

TY - CHAP

T1 - Computational Methods for Derivatives with Early Exercise Features

AU - Chiarella, Carl

AU - Kang, Boda

AU - Meyer, G.H.

AU - Ziogas, A.

PY - 2014/1

Y1 - 2014/1

N2 - In this paper we consider various computational methods for pricing American style derivatives. We do so under both jump diffusion and stochastic volatility processes. We consider integral transform methods, the method of lines, operator-splitting, and the Crank-Nicolson scheme, the latter being used to generate the benchmark solution. Overall, we find that the method of lines approach is quite competitive with other methods for the problems considered in this paper. As one goes to higher dimensions it may be necessary to use methods such as the sparse grid approach.

AB - In this paper we consider various computational methods for pricing American style derivatives. We do so under both jump diffusion and stochastic volatility processes. We consider integral transform methods, the method of lines, operator-splitting, and the Crank-Nicolson scheme, the latter being used to generate the benchmark solution. Overall, we find that the method of lines approach is quite competitive with other methods for the problems considered in this paper. As one goes to higher dimensions it may be necessary to use methods such as the sparse grid approach.

U2 - 10.1016/B978-0-444-52980-0.00005-0

DO - 10.1016/B978-0-444-52980-0.00005-0

M3 - Chapter

SN - 978-0-444-52980-0

VL - 3

SP - 225

EP - 275

BT - Handbook of Computational Economics

A2 - Schmedders, Karl

A2 - Judd, Kenneth L.

PB - Elsevier

ER -