{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/83498"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/83498","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"How Well Do Commodity Based ETFs Track Underlying Assets?","abstract":"Exchange Traded Funds are growing in popularity and volume, however academic literature related to their performance is limited. This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Tracking error in this study is evaluated through 4 approaches to measure error, bias, systematic risk, and error magnitude. Additionally, a mispricing analysis is conducted as an alternative form of error measurement Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN ETF is returning a smaller positive value compared to the asset basket when asset basket returns are greater than zero and a larger negative value compared to the asset basket when asset basket returns are less than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors were found to be impacted by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium.","abstract_html":"Exchange Traded Funds are growing in popularity and volume, however academic literature related to their performance is limited. This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Tracking error in this study is evaluated through 4 approaches to measure error, bias, systematic risk, and error magnitude. Additionally, a mispricing analysis is conducted as an alternative form of error measurement Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN ETF is returning a smaller positive value compared to the asset basket when asset basket returns are greater than zero and a larger negative value compared to the asset basket when asset basket returns are less than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors were found to be impacted by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium.","abstract_has_math":false,"creators":["Neff, Tyler Wesley"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Agricultural and Applied Economics","degree_department":"Agricultural and Applied Economics","school":null,"contributors":[],"advisors":[],"committee_chairs":["Isengildina-Massa, Olga"],"committee_members":["Spicer, Cara Anne","Ramsey, A. Ford"],"year":2018,"date_issued":"2018-06-08","date_published":"2018-06-08","updated_at":"2026-07-22T22:20:12Z","subjects":["Exchange Traded Funds","Tracking Performance","Agriculture","Energy","CORN","SOYB","WEAT","USO","UGA"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:15487"],"render_values":[{"text":"vt_gsexam:15487","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/83498","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Isengildina-Massa, Olga"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Spicer, Cara Anne","Ramsey, A. 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This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Tracking error in this study is evaluated through 4 approaches to measure error, bias, systematic risk, and error magnitude. Additionally, a mispricing analysis is conducted as an alternative form of error measurement Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN ETF is returning a smaller positive value compared to the asset basket when asset basket returns are greater than zero and a larger negative value compared to the asset basket when asset basket returns are less than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors were found to be impacted by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Exchange Traded Funds are growing in popularity and volume, however academic literature related to their performance is limited. This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Tracking error in this study is evaluated through 4 approaches to measure error, bias, systematic risk, and error magnitude. Additionally, a mispricing analysis is conducted as an alternative form of error measurement. Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN ETF is returning a smaller positive value compared to the asset basket when asset basket returns are greater than zero and a larger negative value compared to the asset basket when asset basket returns are less than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors were found to be impacted by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["How Well Do Commodity Based ETFs Track Underlying Assets?"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Isengildina-Massa, Olga"],"dc:contributor.committeemember":["Spicer, Cara Anne","Ramsey, A. Ford"],"dc:contributor.department":["Agricultural and Applied Economics"],"dc:creator":["Neff, Tyler Wesley"],"dc:date.accessioned":["2018-06-09T08:00:24Z"],"dc:date.available":["2018-06-09T08:00:24Z"],"dc:date.issued":["2018-06-08"],"dc:description.abstract":["Exchange Traded Funds are growing in popularity and volume, however academic literature related to their performance is limited. This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Tracking error in this study is evaluated through 4 approaches to measure error, bias, systematic risk, and error magnitude. Additionally, a mispricing analysis is conducted as an alternative form of error measurement Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN ETF is returning a smaller positive value compared to the asset basket when asset basket returns are greater than zero and a larger negative value compared to the asset basket when asset basket returns are less than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors were found to be impacted by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium."],"dc:description.abstractgeneral":["Exchange Traded Funds are growing in popularity and volume, however academic literature related to their performance is limited. This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Tracking error in this study is evaluated through 4 approaches to measure error, bias, systematic risk, and error magnitude. Additionally, a mispricing analysis is conducted as an alternative form of error measurement. Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN ETF is returning a smaller positive value compared to the asset basket when asset basket returns are greater than zero and a larger negative value compared to the asset basket when asset basket returns are less than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors were found to be impacted by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:15487"],"dc:identifier.uri":["http://hdl.handle.net/10919/83498"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Exchange Traded Funds","Tracking Performance","Agriculture","Energy","CORN","SOYB","WEAT","USO","UGA"],"dc:title":["How Well Do Commodity Based ETFs Track Underlying Assets?"],"dc:type":["Thesis"],"thesis:degree_discipline":["Agricultural and Applied Economics"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:20:12Z"}