{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/117665"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/117665","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Can intraday data improve commodity hedging performance?","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01","abstract_has_math":false,"creators":["Wu, Shujie"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Agricultural & Applied Econ","degree_department":null,"school":null,"contributors":["Serra Devesa, Maria Teresa","Garcia, Phillip","Irwin, Scott"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-12","date_published":"2022-12","updated_at":"2026-07-22T22:24:56Z","subjects":["High Frequency Data","Hedging","Har Model","Crack Spread","Crush Spread"],"languages":["en","eng"],"rights":["Copyright 2022 Shujie Wu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/117665","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Serra Devesa, Maria Teresa","Garcia, Phillip","Irwin, Scott"]},{"key":"dc:creator","label":"Author","values":["Wu, Shujie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-12","2022-12-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural & Applied Econ"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["High Frequency Data","Hedging","Har Model","Crack Spread","Crush Spread"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Shujie Wu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/117665"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01","The student, Shujie Wu, accepted the attached license on 2022-11-29 at 10:22.","The student, Shujie Wu, submitted this Thesis for approval on 2022-11-29 at 10:29.","This Thesis was approved for publication on 2022-12-08 at 15:57.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18663 on 2023-04-12 at 08:12:35","We examine if there is economic value in using intraday data to hedge commodity spot prices in the futures market using the realized minimum-variance hedging ratio (RMVHR) framework. The latter depends on the forecast of the realized futures-cash covariance matrix. We consider both multiple and single commodity portfolios that relate to the crude oil crack and soybean crush industries, as well as different forecast strategies. Forecasts are built based on the heterogeneous autoregressive (HAR) model and range from a direct forecast of the RMVHR, a forecast of the futures-spot covariance for a single commodity to then build the RMVHR, to a multi-commodity portfolio where inter-commodity spillovers are also forecast. We use the Naïve hedging ratio as the benchmark to investigate the performance of intraday data-based hedging models. Our results suggest that for each portfolio considered, there is at least one intraday data-based hedging strategy that outperforms the Naïve in the soybean crush complex. In the crude oil crush complex, the superiority of using intraday data is not always statistically significant. Forecasting RMVHR directly is generally considered the best strategy, which suggests that simpler is better. Our estimates place the advantage of using intraday data between USD7,305 and USD250 per contract and year on average, with these values representing the decline in the portfolio’s standard deviation achieved through hedging."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Can intraday data improve commodity hedging performance?"]}]}],"canonical_facts":{"dc:contributor":["Serra Devesa, Maria Teresa","Garcia, Phillip","Irwin, Scott"],"dc:creator":["Wu, Shujie"],"dc:date":["2022-12","2022-12-08"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01","The student, Shujie Wu, accepted the attached license on 2022-11-29 at 10:22.","The student, Shujie Wu, submitted this Thesis for approval on 2022-11-29 at 10:29.","This Thesis was approved for publication on 2022-12-08 at 15:57.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18663 on 2023-04-12 at 08:12:35","We examine if there is economic value in using intraday data to hedge commodity spot prices in the futures market using the realized minimum-variance hedging ratio (RMVHR) framework. The latter depends on the forecast of the realized futures-cash covariance matrix. We consider both multiple and single commodity portfolios that relate to the crude oil crack and soybean crush industries, as well as different forecast strategies. Forecasts are built based on the heterogeneous autoregressive (HAR) model and range from a direct forecast of the RMVHR, a forecast of the futures-spot covariance for a single commodity to then build the RMVHR, to a multi-commodity portfolio where inter-commodity spillovers are also forecast. We use the Naïve hedging ratio as the benchmark to investigate the performance of intraday data-based hedging models. Our results suggest that for each portfolio considered, there is at least one intraday data-based hedging strategy that outperforms the Naïve in the soybean crush complex. In the crude oil crush complex, the superiority of using intraday data is not always statistically significant. Forecasting RMVHR directly is generally considered the best strategy, which suggests that simpler is better. Our estimates place the advantage of using intraday data between USD7,305 and USD250 per contract and year on average, with these values representing the decline in the portfolio’s standard deviation achieved through hedging."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/117665"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Shujie Wu"],"dc:subject":["High Frequency Data","Hedging","Har Model","Crack Spread","Crush Spread"],"dc:title":["Can intraday data improve commodity hedging performance?"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Agricultural & Applied Econ"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:56Z"}