Abstract
Traditionally, company valuation methods are based on discounted cash flows, market prices, comparable sales and even liquidation values, but these are known to have a number of shortcomings. The application of data envelopment analysis (DEA) to finding companies comparable to the one under examination and there by predicting the market values of such companies can be considered to be an extension of the market-based approaches. As a result of using DEA, companies are classified into either an or group, for each of which we assume that a corresponding upper or lower bound of its market value exists, respectively. Furthermore, the market value of an inefficient company is expressed in a form of a range of values, which are calculated by utilizing firm's reference set defined by DEA. As the validation to the modelling part, inefficient companies correctly classified their market values into the evaluated variation range up to 36.93%, and 66.20% of the actual market values are below their upper bounds. On the other hand, 41.67% of the time DEA can find alower bound of their market values for efficient companies based on inefficient peer comparisons. The results show that using DEA in valuing private companies is a relatively advanced method, and could prospectively play an active role in company valuation.
Highlights
Business valuation in North America is a multi-billion-dollar business
Another way of representing Discounted Cash Flow (DCF) is to show that the DCF formulation values only the assets that give rise to the free cash flow
The variable returns to scale (VRS) SBM model rather than constant returns to scale form (CRS) SBM or other radial data envelopment analysis (DEA) models is selected in this research for the reasons that we will explain in Section 4 after we introduce the company valuation method
Summary
Business valuation in North America is a multi-billion-dollar business. There are many reasons for evaluating a business, but in most cases it is required to obtain an impartial value of the business. The basic underlying methodology of DEA is a fractional linear programming technique based comparison of a group of DMUs (decision making units) under analysis, be the DMUs banks, hospitals, and many other entities or in this case companies. DEA is a non-biased method which incorporates a cluster of relevant factors in a single model and none of them is given preference. It treats the DMUs with unrestricted weights which make a rather fair judgment on the importance of such variables
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