{"id":{"repo_id":"calgary","oai_identifier":"oai:ucalgary.scholaris.ca:11023/745"},"canonical_url":"https://search.dev.ndltd.org/etd/calgary/oai:ucalgary.scholaris.ca:11023/745","repository":{"repo_id":"calgary","name":"University of Calgary","base_url":"https://ucalgary.scholaris.ca/server/oai/request"},"display":{"title":"Monte Carlo Methods for Derivative Pricing of Stochastic Volatility Models Driven by Fractional Brownian Motion","abstract":"We model asset prices with stochastic volatilities driven by fractional Brownian motion. Price paths and their endpoints are used to obtain a Monte Carlo value estimate of vanilla european options, lookback options as well as variance swaps. Underlying models for price movements are driven by stochastic volatility models driven by fractional Brownian motion with H > 1/2 . These models exhibit a strong autocorrelation in volatility evolution. The models considered are fractional Ornstein Uhlenbeck, fractional Cox-Ingersoll-Ross, fractional Continuous GARCH(1,1) and fractional Heston.","abstract_html":"We model asset prices with stochastic volatilities driven by fractional Brownian motion. Price paths and their endpoints are used to obtain a Monte Carlo value estimate of vanilla european options, lookback options as well as variance swaps. Underlying models for price movements are driven by stochastic volatility models driven by fractional Brownian motion with H > 1/2 . These models exhibit a strong autocorrelation in volatility evolution. The models considered are fractional Ornstein Uhlenbeck, fractional Cox-Ingersoll-Ross, fractional Continuous GARCH(1,1) and fractional Heston.","abstract_has_math":false,"creators":["Devauld, Wesley"],"institution":"Graduate Studies","degree_name":"Master of Science (MSc)","degree_level":null,"degree_discipline":"Mathematics and Statistics","degree_department":null,"school":null,"contributors":[],"advisors":["Swishchuk, Anatoliy"],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-05-30","date_published":"2013-05-30","updated_at":"2026-07-24T01:30:44Z","subjects":["Mathematics"],"languages":["eng"],"rights":["University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["http://dx.doi.org/10.11575/PRISM/27003"],"render_values":[{"text":"http://dx.doi.org/10.11575/PRISM/27003","href":"http://dx.doi.org/10.11575/PRISM/27003","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/11023/745","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Swishchuk, Anatoliy"]},{"key":"dc:creator","label":"Author","values":["Devauld, Wesley"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2013-05-30T17:25:40Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2013-11-12T08:00:12Z"]},{"key":"dc:date.issued","label":"Date","values":["2013-05-30"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Calgary"]},{"key":"dc:type","label":"Dc Type","values":["master thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics and Statistics"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MSc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Calgary"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Mathematics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["http://dx.doi.org/10.11575/PRISM/27003"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11023/745"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["We model asset prices with stochastic volatilities driven by fractional Brownian motion. Price paths and their endpoints are used to obtain a Monte Carlo value estimate of vanilla european options, lookback options as well as variance swaps. Underlying models for price movements are driven by stochastic volatility models driven by fractional Brownian motion with H > 1/2 . These models exhibit a strong autocorrelation in volatility evolution. The models considered are fractional Ornstein Uhlenbeck, fractional Cox-Ingersoll-Ross, fractional Continuous GARCH(1,1) and fractional Heston."]},{"key":"dc:title","label":"Title","values":["Monte Carlo Methods for Derivative Pricing of Stochastic Volatility Models Driven by Fractional Brownian Motion"]}]}],"canonical_facts":{"dc:contributor.advisor":["Swishchuk, Anatoliy"],"dc:creator":["Devauld, Wesley"],"dc:date.accessioned":["2013-05-30T17:25:40Z"],"dc:date.available":["2013-11-12T08:00:12Z"],"dc:date.issued":["2013-05-30"],"dc:description.abstract":["We model asset prices with stochastic volatilities driven by fractional Brownian motion. Price paths and their endpoints are used to obtain a Monte Carlo value estimate of vanilla european options, lookback options as well as variance swaps. Underlying models for price movements are driven by stochastic volatility models driven by fractional Brownian motion with H > 1/2 . These models exhibit a strong autocorrelation in volatility evolution. The models considered are fractional Ornstein Uhlenbeck, fractional Cox-Ingersoll-Ross, fractional Continuous GARCH(1,1) and fractional Heston."],"dc:identifier.doi":["http://dx.doi.org/10.11575/PRISM/27003"],"dc:identifier.uri":["http://hdl.handle.net/11023/745"],"dc:language.iso":["eng"],"dc:publisher.institution":["University of Calgary"],"dc:rights":["University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission."],"dc:subject":["Mathematics"],"dc:title":["Monte Carlo Methods for Derivative Pricing of Stochastic Volatility Models Driven by Fractional Brownian Motion"],"dc:type":["master thesis"],"thesis:degree_discipline":["Mathematics and Statistics"],"thesis:degree_name":["Master of Science (MSc)"],"thesis:institution_name":["University of Calgary"]},"updated_at":"2026-07-24T01:30:44Z"}