{"id":{"repo_id":"humboldt-diss","oai_identifier":"oai:edoc.hu-berlin.de:18452/14693"},"canonical_url":"https://search.dev.ndltd.org/etd/humboldt-diss/oai:edoc.hu-berlin.de:18452/14693","repository":{"repo_id":"humboldt-diss","name":"Humboldt Universität zu Berlin","base_url":"https://edoc.hu-berlin.de/server/oai/request"},"display":{"title":"Estimating State Price Densities via Local Polynomials","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Kervella, Pierre"],"institution":"Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2002,"date_issued":"2002-03-11","date_published":"2002-03-11","updated_at":"2026-08-21T16:45:17Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.18452/14041"],"render_values":[{"text":"https://doi.org/10.18452/14041","href":"https://doi.org/10.18452/14041","code":true}]}]},"links":{"outbound_url":"https://edoc.hu-berlin.de/18452/14693","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"source_record":{"url":"https://edoc.hu-berlin.de/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aedoc.hu-berlin.de%3A18452%2F14693","prefix":"dim"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Kervella, Pierre"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-06-18T02:07:52Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-06-18T02:07:52Z"]},{"key":"dc:date.issued","label":"Date","values":["2002-03-11"]},{"key":"dc:publisher","label":"Institution","values":["Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät"]},{"key":"dc:type","label":"Dc Type","values":["masterThesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.18452/14041"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://edoc.hu-berlin.de/18452/14693"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Estimating State Price Densities via Local Polynomials"]}]}],"canonical_facts":{"dc:creator":["Kervella, Pierre"],"dc:date.accessioned":["2017-06-18T02:07:52Z"],"dc:date.available":["2017-06-18T02:07:52Z"],"dc:date.issued":["2002-03-11"],"dc:description.abstract":["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."],"dc:identifier.doi":["https://doi.org/10.18452/14041"],"dc:identifier.uri":["https://edoc.hu-berlin.de/18452/14693"],"dc:language.iso":["eng"],"dc:publisher":["Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Estimating State Price Densities via Local Polynomials"],"dc:type":["masterThesis"]},"updated_at":"2026-08-21T16:45:17Z"}