Determinants and Prediction Accuracy of Price Multiples for South East Asia: Conventional and Machine Learning Analysis
The present study evaluates determinants of price multiples and their prediction accuracy using ordinary least square (OLS) regression and machine learning based shrinkage methods for the South East Asian markets. Price multiples examined in the research are price to earnings (P/Es) price to book (P/B) and price to sales (P/S) Data has been collected from Thomson Reuters Eikon. The study recommends that the P/B ratio is the best price multiple for developing a price based valuation model. Beside fundamental determinants of the multiple, various firm level control variables, namely, firm size, cash holding, strategic holding, stock price volatility, firms' engagement in Environment, Social, and Governance (ESG) activities, dividend yield, and net profit margin impact firm's P/B multiple. Positive coefficients of consumer non cyclical and healthcare dummies indicate a preference for defensive stocks by the investors. Application of machine learning based shrinkage methods ensures the accuracy of prediction even with out of sample forecasting.