{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/65809"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/65809","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"A quantitative equity strategy based on factors formed by industries in the S&P500","abstract":"This paper presents and simulates a long-short market-neutral quantitative equity trading strategy for US stocks. First, economic intuition and academic researches for which this trading strategy is based upon will be explained. Second, to ensure that the trading strategy simulation would be as realistic as possible, I will introduce some trading constraints, investment guidelines, and other assumptions/ restrictions about the strategy's backtest setting. Third, I will put in detail how the trading model is built and how the strategy is executed. Fourth, the strategy's backtest result will be presented. Fifth, I will use some risk factors to analyze the strategy's performance as well as compare the strategy's results against these risk factors. Lastly, I conclude with several insights drawn from this research on quantitative investment.","abstract_html":"This paper presents and simulates a long-short market-neutral quantitative equity trading strategy for US stocks. First, economic intuition and academic researches for which this trading strategy is based upon will be explained. Second, to ensure that the trading strategy simulation would be as realistic as possible, I will introduce some trading constraints, investment guidelines, and other assumptions/ restrictions about the strategy's backtest setting. Third, I will put in detail how the trading model is built and how the strategy is executed. Fourth, the strategy's backtest result will be presented. Fifth, I will use some risk factors to analyze the strategy's performance as well as compare the strategy's results against these risk factors. Lastly, I conclude with several insights drawn from this research on quantitative investment.","abstract_has_math":false,"creators":["Liu, Jack Wen-Hao"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Sloan School of Management.","school":null,"contributors":[],"advisors":["John DeTore."],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011","date_published":"2011","updated_at":"2026-07-22T22:21:30Z","subjects":["Sloan School of Management."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/65809","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["John DeTore."]},{"key":"dc:contributor.department","label":"Department","values":["Sloan School of Management."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Sloan School of Management."]},{"key":"dc:creator","label":"Author","values":["Liu, Jack Wen-Hao"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2011-09-13T17:55:34Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2011-09-13T17:55:34Z"]},{"key":"dc:date.issued","label":"Date","values":["2011"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Sloan School of Management."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["M.I.T. theses are protected by copyright. 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First, economic intuition and academic researches for which this trading strategy is based upon will be explained. Second, to ensure that the trading strategy simulation would be as realistic as possible, I will introduce some trading constraints, investment guidelines, and other assumptions/ restrictions about the strategy's backtest setting. Third, I will put in detail how the trading model is built and how the strategy is executed. Fourth, the strategy's backtest result will be presented. Fifth, I will use some risk factors to analyze the strategy's performance as well as compare the strategy's results against these risk factors. Lastly, I conclude with several insights drawn from this research on quantitative investment."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["A quantitative equity strategy based on factors formed by industries in the S&P500"]}]}],"canonical_facts":{"dc:contributor.advisor":["John DeTore."],"dc:contributor.department":["Sloan School of Management."],"dc:contributor.other":["Sloan School of Management."],"dc:creator":["Liu, Jack Wen-Hao"],"dc:date.accessioned":["2011-09-13T17:55:34Z"],"dc:date.available":["2011-09-13T17:55:34Z"],"dc:date.issued":["2011"],"dc:description":["Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2011.","Cataloged from PDF version of thesis.","Includes bibliographical references (p. 25)."],"dc:description.abstract":["This paper presents and simulates a long-short market-neutral quantitative equity trading strategy for US stocks. First, economic intuition and academic researches for which this trading strategy is based upon will be explained. Second, to ensure that the trading strategy simulation would be as realistic as possible, I will introduce some trading constraints, investment guidelines, and other assumptions/ restrictions about the strategy's backtest setting. Third, I will put in detail how the trading model is built and how the strategy is executed. Fourth, the strategy's backtest result will be presented. Fifth, I will use some risk factors to analyze the strategy's performance as well as compare the strategy's results against these risk factors. Lastly, I conclude with several insights drawn from this research on quantitative investment."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/65809"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Sloan School of Management."],"dc:title":["A quantitative equity strategy based on factors formed by industries in the S&P500"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:30Z"}