@article {10.3844/jmssp.2013.65.71,
article_type = {journal},
title = {FORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSIS},
author = {Sopipan, Nop},
volume = {9},
year = {2013},
month = {Apr},
pages = {65-71},
doi = {10.3844/jmssp.2013.65.71},
url = {https://thescipub.com/abstract/jmssp.2013.65.71},
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 = {Journal of Mathematics and Statistics},
publisher = {Science Publications}
}