Laura Martin Case

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Multiples versus DCF analysis
Multiples analysis is simple to understand and apply. The inputs for the multiple arepublicly available, though are vulnerable to accounting manipulation. Also, it isdifficult to obtain a truly comparable large sample of firms. Multiples analysis isbackward-looking, reliant on historical/current data to obtain multiples. It reflectsrelative value rather than the intrinsic value which DCF valuation produces.DCF analysis generates an intrinsic value as it relies on data specific to the firm. DCFanalysis factors in time value of money, and thus is a forward-looking measure.However, there is uncertainty in forecasting future revenues, especially for privatefirms and those firms that produce little or no cash flows.
Assumptions of multiples analysis
General assumptions of multiples analysis are that the other firms in the industry arecomparable to the firm being valued. The market, on average, prices these firmscorrectly, but makes errors on the pricing of individual stocks. Exhibit 2 shows aselection of comparable firms, assuming that these firms have the same growth, riskand return as Cox Communications. There is also the assumption that financialfundamentals such as EBITDA are defined identically in all firms, with the sameaccounting methods and reporting periods. Exhibit 5 assumes a positive linearrelationship between ROIC and the multiple Adjusted Enterprise Value/AverageInvested Capital.
Regression analysis and traditional multiples analysis – similarities anddifferences The two analyses both predict the underlying value of the firm. Also, both regression and multiples analyses reflect the past. The future value of the firm is obtained usinghistorical inputs. Both analyses assume that firms in the same industry arecomparable. Traditional multiples analysis is more arithmetic in its approach. It is based on findingthe average multiple among comparable firms, and then applying it to the firm’sfundamentals. How accurate the

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