A Survey of Systems for Predicting Stock Market Movements, Combining Market Indicators and Machine Learning Classifiers

Author

Jeffrey Allan Caley, Portland State UniversityFollow

Sponsor

Portland State University. Electrical and Computer Engineering

First Advisor

Richard Tymerski

Date of Publication

Winter 3-14-2013

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Electrical and Computer Engineering

Department

Electrical and Computer Engineering

Language

English

Subjects

Stock exchanges -- Computer simulation, Financial engineering, Stock price forecasting, Machine learning -- Mathematical models, Support vector machines

DOI

10.15760/etd.2000

Physical Description

1 online resource (ix, 110 pages)

Abstract

In this work, we propose and investigate a series of methods to predict stock market movements. These methods use stock market technical and macroeconomic indicators as inputs into different machine learning classifiers. The objective is to survey existing domain knowledge, and combine multiple techniques into one method to predict daily market movements for stocks. Approaches using nearest neighbor classification, support vector machine classification, K-means classification, principal component analysis and genetic algorithms for feature reduction and redefining the classification rule were explored. Ten stocks, 9 companies and 1 index, were used to evaluate each iteration of the trading method. The classification rate, modified Sharpe ratio and profit gained over the test period is used to evaluate each strategy. The findings showed nearest neighbor classification using genetic algorithm input feature reduction produced the best results, achieving higher profits than buy-and-hold for a majority of the companies.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Comments

The code used to run simulations is available for download and is located below in Additional Files.

Persistent Identifier

http://archives.pdx.edu/ds/psu/12733

Recommended Citation

Caley, Jeffrey Allan, "A Survey of Systems for Predicting Stock Market Movements, Combining Market Indicators and Machine Learning Classifiers" (2013). Dissertations and Theses. Paper 2001.
https://doi.org/10.15760/etd.2000