Application of principal component analysis on equity valuation multiples: Evidence from Malaysian firms

Abstract

Investment analysts often used equity valuation multiples to assess the performance of stocks in relation to likely future return to shareholders. Valuation multiples used by analysts are price to earnings, price to book value, price to cash flow and price to sales multiples. However, researchers have argued that correlation exists between the multiples hence assessing them individually and later merging them to one multiple results to reduplication.This study employed the principal component analysis (PCA) method to condense the four equity valuation multiples (EVM) of 223 randomly selected listed firms in Malaysia for the period of 2008-2013. The PCA result reveals that three (3) components explained 99% of the total variables variance. Suggesting that, the three components (price to earnings, price to book value and price to cash flow multiples) can satisfactorily explain all the EVMs.The implication is that strong correlation exists between EVMs of Malaysian firms.Therefore, the study recommends the application of principal component analysis methodology in the analysis of the equity valuation multiples because of correlation that exists between the valuation multiples. The study is limited to EVMs, entity valuations are not covered in the study.Applying PCA to equity valuation multiples ensures accuracy and reliability of result interpretation due to absence of multicolearity in the decomposed principal component