Application of machine learning : automated trading informed by event driven data
Name
965785890-MIT.pdf
Description
Full printable version
Size
1.04 MB
Format
Adobe PDF
Checksum (MD5)
ce4ae7a478fad04219682519d86cd102
Author(s)
Leung, Jason W
Advisor(s)
Jacob K. White.
Alternative Title
Automated trading informed by event driven data
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
Models of stock price prediction have traditionally used technical indicators alone to generate trading signals. In this paper, we build trading strategies by applying machine-learning techniques to both technical analysis indicators and market sentiment data. The resulting prediction models can be employed as an artificial trader used to trade on any given stock exchange. The performance of the model is evaluated using the S&P 500 index.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 61-65).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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.
Persistent DSpace Link
