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ISSN: 1549-3644 (Print)
ISSN: 1558-6359 (Online)
Research Article Open Access

FORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSIS

Nop Sopipan1
  • 1 Nakhon Ratchasima Rajabhat University, Thailand

Abstract

The aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive order p (AR (p)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Results showed that the multiple regressions based on PCA, has the best performance.

Journal of Mathematics and Statistics
Volume 9 No. 1, 2013, 65-71

DOI: https://doi.org/10.3844/jmssp.2013.65.71

Submitted On: 17 January 2013 Published On: 17 April 2013

How to Cite: Sopipan, N. (2013). FORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSIS. Journal of Mathematics and Statistics, 9(1), 65-71. https://doi.org/10.3844/jmssp.2013.65.71

Open AccessCopyright: © 2013 Nop Sopipan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • SET Index
  • Forecasting
  • Principal Component Analysis
  • Multicollinearity