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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Kravchenko, I., Kravchenko, V. V., Torba, S. M. & Dias, J. C. (2019). Pricing double barrier options on homogeneous diffusions: a Neumann series of Bessel functions representation. International Journal of Theoretical and Applied Finance. 22 (6)
Exportar Referência (IEEE)
I. V. Kravchenko et al.,  "Pricing double barrier options on homogeneous diffusions: a Neumann series of Bessel functions representation", in Int. Journal of Theoretical and Applied Finance, vol. 22, no. 6, 2019
Exportar BibTeX
@article{kravchenko2019_1734976405115,
	author = "Kravchenko, I. and Kravchenko, V. V. and Torba, S. M. and Dias, J. C.",
	title = "Pricing double barrier options on homogeneous diffusions: a Neumann series of Bessel functions representation",
	journal = "International Journal of Theoretical and Applied Finance",
	year = "2019",
	volume = "22",
	number = "6",
	doi = "10.1142/S0219024919500304",
	url = "https://doi.org/10.1142/S0219024919500304"
}
Exportar RIS
TY  - JOUR
TI  - Pricing double barrier options on homogeneous diffusions: a Neumann series of Bessel functions representation
T2  - International Journal of Theoretical and Applied Finance
VL  - 22
IS  - 6
AU  - Kravchenko, I.
AU  - Kravchenko, V. V.
AU  - Torba, S. M.
AU  - Dias, J. C.
PY  - 2019
SN  - 0219-0249
DO  - 10.1142/S0219024919500304
UR  - https://doi.org/10.1142/S0219024919500304
AB  - This paper develops a novel analytically tractable Neumann series of Bessel functions representation for pricing (and hedging) European-style double barrier knock-out options, which can be applied to the whole class of one-dimensional time-homogeneous diffusions, even for the cases where the corresponding transition density is not known. The proposed numerical method is shown to be efficient and simple to implement. To illustrate the flexibility and computational power of the algorithm, we develop an extended jump to default model that is able to capture several empirical regularities commonly observed in the literature. 
ER  -