VALUE DRIVERS OF PRICE-EARNINGS MULTIPLES OF UNIVERSAL BANKS IN THE PHILIPPINES: A PANEL REGRESSION APPROACH

Authors

  • Antonio Dayag The Graduate School, University of Santo Tomas, España, Philippines
  • Fernando Trinidad Graduate School, University of Santo Tomas, España

DOI:

https://doi.org/10.15282/jgi.2.2.2019.5463

Keywords:

P/E ratio, Bank valuation, Panel regression, P/E multiples

Abstract

Valuation using P/E multiples has been done mostly in developed countries and some   developing countries including the Philippines. However, variables that impact sound P/E multiples valuation has yet to be determined. The purpose of the study is to develop a valuation model using P/E multiples by using variables that will lead to sound valuation of firms. The application would be in the banking sector, specifically universal banks since these institutions are significant economic drivers in the Philippines. Utilizing data from the top ten [10] universal banks in the Philippines in terms of assets and capitalization from 2010 to 2017, selected macroeconomic variables, stock market index, and firm-specific variables were used in the proposed valuation model using panel data regression analysis. These variables are GDP growth rate, inflation rate, interest rate, return on equity [ROE], ROE growth rate, net income growth rate, earnings per share [EPS] growth rate, dividend payout ratio, Philippine Stock Exchange [PSE] index, and price-to-book [P/B] value ratio. Panel regression results showed that among the independent variables, ROE, EPS growth rate, P/B ratio, net income growth rate, and PSE index are statistically significant. Among the significant variables, ROE reduces P/E ratio by 51 times. This implies that an increasing ROE reduces the price per stock investors are willing to pay. Goodness of fit [R2] of the model is 74.83%, which is relatively good

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Published

2019-02-04

How to Cite

Dayag, A., & Trinidad, F. (2019). VALUE DRIVERS OF PRICE-EARNINGS MULTIPLES OF UNIVERSAL BANKS IN THE PHILIPPINES: A PANEL REGRESSION APPROACH. Journal of Governance and Integrity, 2(2), 3–13. https://doi.org/10.15282/jgi.2.2.2019.5463

Issue

Section

JGI Vol. 2, Issue 2, July 2019