{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/85513"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/85513","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Density Estimation for Robust Financial Econometrics","abstract":"Chapter 3 introduces an efficient and robust parametric inference which minimizes the Hellinger distance between two nonparametrically smoothed density estimates: the simulated model density and corresponding observed density. This approach generalizes work of Beran (1977) and Basu and Lindsay (1994) so that dependent data and simulated model densities are allowed, enabling the estimation without simple analytical criterion functions. In application to the lognormal stochastic volatility model, the proposed estimator is found to be competitive with the Markov-chain Monte Carlo approach of Jacquier, Polson, and Rossi (1994).","abstract_html":"Chapter 3 introduces an efficient and robust parametric inference which minimizes the Hellinger distance between two nonparametrically smoothed density estimates: the simulated model density and corresponding observed density. This approach generalizes work of Beran (1977) and Basu and Lindsay (1994) so that dependent data and simulated model densities are allowed, enabling the estimation without simple analytical criterion functions. In application to the lognormal stochastic volatility model, the proposed estimator is found to be competitive with the Markov-chain Monte Carlo approach of Jacquier, Polson, and Rossi (1994).","abstract_has_math":false,"creators":["Takada, Teruko"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Koenker, Roger W."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T22:47:12Z","date_published":"2015-09-25T22:47:12Z","updated_at":"2026-07-22T22:26:25Z","subjects":["Economics, Theory"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3023210"],"render_values":[{"text":"(MiAaPQ)AAI3023210","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/85513","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Koenker, Roger W."]},{"key":"dc:creator","label":"Author","values":["Takada, Teruko"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T22:47:12Z","10000-01-01","2001"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Economics, Theory"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/85513","(MiAaPQ)AAI3023210"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Chapter 3 introduces an efficient and robust parametric inference which minimizes the Hellinger distance between two nonparametrically smoothed density estimates: the simulated model density and corresponding observed density. This approach generalizes work of Beran (1977) and Basu and Lindsay (1994) so that dependent data and simulated model densities are allowed, enabling the estimation without simple analytical criterion functions. In application to the lognormal stochastic volatility model, the proposed estimator is found to be competitive with the Markov-chain Monte Carlo approach of Jacquier, Polson, and Rossi (1994).","Made available in DSpace on 2015-09-25T22:47:12Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3023210.pdf: 9134778 bytes, checksum: d3f21f12e9ecbe4ee1146aa25502b41b (MD5) Previous issue date: 2001","Embargo set by: Seth Robbins for item 86794 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","186 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2001."]},{"key":"dc:title","label":"Title","values":["Density Estimation for Robust Financial Econometrics"]}]}],"canonical_facts":{"dc:contributor":["Koenker, Roger W."],"dc:creator":["Takada, Teruko"],"dc:date":["2015-09-25T22:47:12Z","10000-01-01","2001"],"dc:description":["Chapter 3 introduces an efficient and robust parametric inference which minimizes the Hellinger distance between two nonparametrically smoothed density estimates: the simulated model density and corresponding observed density. This approach generalizes work of Beran (1977) and Basu and Lindsay (1994) so that dependent data and simulated model densities are allowed, enabling the estimation without simple analytical criterion functions. In application to the lognormal stochastic volatility model, the proposed estimator is found to be competitive with the Markov-chain Monte Carlo approach of Jacquier, Polson, and Rossi (1994).","Made available in DSpace on 2015-09-25T22:47:12Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3023210.pdf: 9134778 bytes, checksum: d3f21f12e9ecbe4ee1146aa25502b41b (MD5) Previous issue date: 2001","Embargo set by: Seth Robbins for item 86794 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","186 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2001."],"dc:identifier":["http://hdl.handle.net/2142/85513","(MiAaPQ)AAI3023210"],"dc:language":["eng"],"dc:subject":["Economics, Theory"],"dc:title":["Density Estimation for Robust Financial Econometrics"],"dc:type":["text"],"thesis:degree_discipline":["Economics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:25Z"}