Academic journal article Asian Social Science

Multiples for Valuation Estimates of Companies in the Technology Sector of Emerging Markets

Academic journal article Asian Social Science

Multiples for Valuation Estimates of Companies in the Technology Sector of Emerging Markets

Article excerpt


Market multiples are a tool for estimation corporate value. These tools are expressed as temporal dynamics and differences in the markets, sectors, industries, firms. Despite their great practical application, a number of problems remains which continue to be debated. This article examines the explanatory power of multiples, and makes a comparison of multiples for the technology sector with the market as a whole, and multiples for the technology sector of Emerging Markets are established within the ranking, most fully explaining the value of stocks using an approach that ensures mitigating the differences in multiples from basic variables.

Keywords: valuation, valuation multiples, ratio analysis

JEL: G12, M41

1. Introduction

Valuation multiples are widely used for comparative valuation of company assets. However, despite the ease of use, a false investment decision can be easily made. In this regard, an ongoing debate about the principles and certain aspects of the multiple applications continues in the financial literature. Issues on which research continues and the understanding of this problem extends are: what factors determine the level of multiples; which multiples achieve better results; valuation accuracy of multipliers; how to select comparable firms; how differences in the variables determining the multiple are mitigated, and which multiples are better for each type of industry.

Many studies focus on the question of which revenue multiples achieve the best results and the valuation accuracy of various types of multiples. Liu, Nissim, and Thomas (2002) examined the properties of valuation multiples of an entire list of multiples and showed that the historical earnings are valuated in the second place after forward earnings, cash flow and book value of equity are on the third, and multiples based on earnings show worse results. Liu, Nissim, and Thomas in the study (2007) expanded the analysis and found that the multiples based on earnings have an advantage compared to multiples based on operating cash flow.

Lie & Lie (2002) examined the accuracy of a common list of multiples for firms within the database of North America. They reported that the multiples that use the indicators of equity and invested capital tend to outweigh the revenue-based multiples.

Studies such as Cheng and McNamara (2000), Yee (2004) and Yoo (2006) have focus on linear combinations of differences of estimations of the values and offer averaging (valuation estimates) in order to improve the level of the valuation.

In particular, these studies have found that that book value and earnings multiples lead to a reduction of errors in comparison with any multiple, on average. Yee (2008) suggests Bayesian framework for combining valuation estimates.

Using a different approach, Bhojraj & Lee (2002) show that the accuracy of forecasting of multiples can be improved by closely selected set of comparable firms. They believe that their method of selecting comparable firms provides improved accuracy compared with the selection of comparable firms on the basis of industry. Their approach includes two components: (1) regression analysis of multiples using the standard value-drivers as independent variables, and (2) the selection of closely comparable firms on the basis of their valuated relations.

According to the European data, Schreiner & Spremann (2007) examined the accuracy of various multiples. They argue that the equity valuation multiples (P/E, P/BV) outweigh in accuracy the enterprise value multiples (EV) - the EV/EBITDA and EV/EBIT multiples.

Cheng and McNamara (2000) suggested to combine the P/E and P/BV multiples for the most accurate valuation results.

Which factor determines the level of valuation multiples - this issue continues to be in the focus of attention of many researchers. Among them, Cheng & McNamara (2000) reported that the use of earnings per share - the relevant criterion for selecting the appropriate P/E and P/BV multiples. …

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