Barrier option pricing: modelling with neural nets

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Persistent URL	http://purl.org/net/epubs/work/34410
Record Status	Checked
Record Id	34410
Title	Barrier option pricing: modelling with neural nets
Contributors	L Xu (London Metropolitan University), M Dixon (London Metropolitan University), BA Eales (London Metropolitan University), FF Cai (London Metropolitan University), BJ Read (London Metropolitan University), JV Healy (London Metropolitan University)
Abstract	We report call option pricing for up-and-out style barrier options through the use of a neural net model. A synthetic data set was constructed from the real LIFFE standard option price data by use of the Rubenstein and Reiner analytic model (Risk September (1991) 28). Unbiased estimates at the 95% confidence level were achieved for realistic barriers (barrier 4% or more above max(S0;X) ).
Organisation	CCLRC , BITD
Keywords	Engineering , Financial Engineering , Neural net , Up-out call option
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Language	English (EN)

Type	Details	URI(s)	Local file(s)	Year
Journal Article	Physica A 344 (2004): 289-293.	doi:10.1016/j.physa.2004.06.134	PhysicaA344p289-293.pdf	2004