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Massachusetts Institute of Technology

A quantitative equity strategy based on factors formed by industries in the S&P500

Abstract

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.

Degree

thesis:*
Department dc:contributor.department
Sloan School of Management.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Liu, Jack Wen-Hao
Advisor dc:contributor.advisor
  • John DeTore.

Subjects

dc:subject × 1

Rights

dc:rights
Statement 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/65809
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/65809

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Liu, Jack Wen-Hao. A quantitative equity strategy based on factors formed by industries in the S&P500. Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65809