IJPAM: Volume 115, No. 1 (2017)

Title

PRINCIPAL COMPONENT ANALYSIS
FOR STOCK PORTFOLIO MANAGEMENT

Authors

Giorgia Pasini
Department of Computer Science
University of Verona
Strada le Grazie, 15-37134, Verona, ITALY

Abstract

In this paper the method of Principal Component Analysis is applied to three subgroups of stocks of the american index Down Jones Industrial (DJI) Average. While, the first and second group, are homogeneus, the third one contains heterogeneous stocks. Cumulative Variance and Kaiser's Rule are used to get the principal risk directions. The obtained results show how to optimize portfolios investments to derive the best returns and financial control.

History

Received: May 9, 2017
Revised: June 10, 2017
Published: June 29, 2017

AMS Classification, Key Words

AMS Subject Classification: 62H25, 62M10, 62P05, 62P20, 91B30, 91B84
Key Words and Phrases: principal component analysis, cumulative variance, Kaiser's rule, portfolio management, stocks management, financial engineering

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How to Cite?

DOI: 10.12732/ijpam.v115i1.12 How to cite this paper?

Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2017
Volume: 115
Issue: 1
Pages: 153 - 167


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