{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105056"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105056","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Inverting multivariate analytic characteristic functions with financial applications","abstract":"This dissertation is devoted to multivariate analytic characteristic functions inversion and applications in option pricing, option sensitivities estimation, and some electronic engineering problems. We will show that under certain analytic conditions for characteristic functions, the underlying pdfs and cdfs have exponential tails. The inversion from multivariate characteristic functions to the corresponding pdfs and cdfs can be approximated by the trapezoidal rule conveniently with great accuracy. Monte Carlo methods can be applied for option sensitivity analysis. Under multi-dimensional models, acceptance-rejection method is desirable. Simulating from a distribution without explicit pdf or CDF is then transformed to sampling from an easy-to-simulate distribution. Detailed algorithms are provided and comparisons against classical methods in terms of accuracy and efficiency are included.","abstract_html":"This dissertation is devoted to multivariate analytic characteristic functions inversion and applications in option pricing, option sensitivities estimation, and some electronic engineering problems. We will show that under certain analytic conditions for characteristic functions, the underlying pdfs and cdfs have exponential tails. The inversion from multivariate characteristic functions to the corresponding pdfs and cdfs can be approximated by the trapezoidal rule conveniently with great accuracy. Monte Carlo methods can be applied for option sensitivity analysis. Under multi-dimensional models, acceptance-rejection method is desirable. Simulating from a distribution without explicit pdf or CDF is then transformed to sampling from an easy-to-simulate distribution. Detailed algorithms are provided and comparisons against classical methods in terms of accuracy and efficiency are included.","abstract_has_math":false,"creators":["Hu, Runqi"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Industrial Engineering","degree_department":null,"school":null,"contributors":["Feng, Liming","Feng, Runhuan","Sirignano, Justin","Chronopoulou, Alexandra"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T20:36:02Z","date_published":"2019-08-23T20:36:02Z","updated_at":"2026-07-22T22:24:44Z","subjects":["Multivariate analytic characteristic function","inversion"],"languages":["en"],"rights":["Copyright 2019 Runqi Hu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105056","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Feng, Liming","Feng, Runhuan","Sirignano, Justin","Chronopoulou, Alexandra"]},{"key":"dc:creator","label":"Author","values":["Hu, Runqi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-08-23T20:36:02Z","2021-08-24T09:15:20Z","2019-04-19","2019-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial Engineering"]},{"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":["Multivariate analytic characteristic function","inversion"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Runqi Hu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105056"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This dissertation is devoted to multivariate analytic characteristic functions inversion and applications in option pricing, option sensitivities estimation, and some electronic engineering problems. We will show that under certain analytic conditions for characteristic functions, the underlying pdfs and cdfs have exponential tails. The inversion from multivariate characteristic functions to the corresponding pdfs and cdfs can be approximated by the trapezoidal rule conveniently with great accuracy. Monte Carlo methods can be applied for option sensitivity analysis. Under multi-dimensional models, acceptance-rejection method is desirable. Simulating from a distribution without explicit pdf or CDF is then transformed to sampling from an easy-to-simulate distribution. 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We will show that under certain analytic conditions for characteristic functions, the underlying pdfs and cdfs have exponential tails. The inversion from multivariate characteristic functions to the corresponding pdfs and cdfs can be approximated by the trapezoidal rule conveniently with great accuracy. Monte Carlo methods can be applied for option sensitivity analysis. Under multi-dimensional models, acceptance-rejection method is desirable. Simulating from a distribution without explicit pdf or CDF is then transformed to sampling from an easy-to-simulate distribution. Detailed algorithms are provided and comparisons against classical methods in terms of accuracy and efficiency are included.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-05-01","The student, Runqi Hu, accepted the attached license on 2019-04-19 at 10:23.","The student, Runqi Hu, submitted this Dissertation for approval on 2019-04-19 at 10:32.","This Dissertation was approved for publication on 2019-04-19 at 14:25.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13740 on 2019-08-22 at 15:07:23","Made available in DSpace on 2019-08-23T20:36:02Z (GMT). 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