Estimating State Price Densities via Local Polynomials

This master thesis aims at estimating state price densities (SPD) via a nonparametric fit of the implied volatility smile and of its derivatives. To achieve this task, we use the local polynomial estimators and apply the empirical bias-bandwidth selector (EBBS) algorithm to determine both global and local optimal bandwidths. The accuracy of the nonparametric estimates is then studied from the statistical and financial points of view. Afterwards, the resulting SPD estimates are presented as well as their bootstrap confidence bands. In a last part, we compare our semiparametric method with the implied binomial trees.

Grantor dc:publisher

Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät

Year dc:date.issued

2002

Author dc:creator

• Kervella, Pierre

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

eng

DOI

https://doi.org/10.18452/14041

OAI record oai:identifier

https://edoc.hu-berlin.de/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aedoc.hu-berlin.de%3A18452%2F14693