Equity valuation using benchmark multiples: An improved approach using regression-based weights

Abstract

This paper examine the improvement in multiple-based valuations from using a composite of price to earnings (P/E) and price to book (P/B) ratios and firm-specific regression-based weights. The results support that composite benchmark multiples lead to improved valuations over single multiples and further improvement is achieved by incorporating firm characteristics to derive firm-specific regression-based weights. The unrestricted regression-weighted composite multiples perform better than other approaches in predicting year one to year three share prices. Our results remain unchanged when the analysis is conducted using different estimation regressions, different sample periods and subsamples based on firm size, age and the book to market ratio. This research provides a comprehensive comparison between single, equal-weighted and regression-weighted composite multiples that reflect cross-sectional variations in firm growth, profitability and cost-of-capital in equity valuation. The results highlight the usefulness of composite multiple-based valuation in settings where current market prices are not readily available.