2026-09-18T19:10:16Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/658092022-01-13T07:54:52Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
John DeTore.
Liu, Jack Wen-Hao
Sloan School of Management.
Sloan School of Management
2011-09-13T17:55:34Z
2011-09-13T17:55:34Z
2011
2011
http://hdl.handle.net/1721.1/65809
750498676
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 25).
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.
by Jack Wen-Hao Liu.
S.M.
31 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Sloan School of Management.
A quantitative equity strategy based on factors formed by industries in the S&P500
Thesis
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<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>
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