# Laura Martin: Case Study

In reality, a firm with high return but bad management or bad public perception will result in low value. 3. How is Martin’s regression analysis different from/similar to traditional multiples analysis? The traditional multiples analysis utilized a more arithmetic approach. This is done through the averaging of comparable firm’s multiples. The differences between the regression analysis and traditional multiple analysis are that in a traditional multiples analysis we start off with an average multiple being calculated and from that we multiply to the target firm’s forecasted EBITDA.

In contrast, for regression we rely on a regression line produced from a scattering of comparable firms on the ROCCO vs. adjusted enterprise value/average invested capital rap. ROCCO is returns on invested capital and is calculated by dividing net operating profit after taxes by the average invested capital for the period. Invested capital is the sum of fixed assets and net working capital. Using regression we start with allocating a target multiple by aligning the ROCCO to the regression line. From the target multiple we adjust for the factors given (see Q) to arrive at an implied equity value.

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Dividing this by the shares outstanding we arrive at a target price. (See Q) However the ultimate difference with regression is that we are relying on the value of squared wanly Is a sultanate’s Tactic affecting ten accuracy AT ten results Ana the appropriateness in using the regression analysis. Under this approach we require a high correlation, which is given by a high r squared. So the upside to this approach may easily be flawed and in turn we may have to turn to other methods such as the traditional multiples analysis for better results.

The similarities are quite basic and straightforward.

Both approaches rely on comparable firms and ultimately an analysis using this multiples concept is the basis of how they work. 4. Discuss her interpretation of the regression results. Martin’s regression shows the relationship between ROCCO and the valuation of cable and entertainment companies as defined by the ratio of enterprise value to average invested capital. From a different viewpoint it determines the statistical relationship between these variables of interest.

The regression line was used to estimate the target enterprise value to average invested capital multiple, where enterprise value was calculated by summing the market capitalization (share price times no. Outstanding shares = what its worth) of the equity with book value of debt. Martin projected that Cox would improve its ROCCO by 0. % from the 4% on the graph. Aligning it to the regression line she arrived at a target multiple of 1. 594.

From this she multiplied this to the average invested capital of \$12,136 to arrive at an implied enterprise value of \$19,345.

It is then adjusted non-consolidated assets of plus \$12,292, other assets of plus \$400, cash and proceeds of \$23, and debt less (\$3,800). This gives an implied equity value of \$28,260. Dividing this by the shares outstanding (millions) of 565. 2 we get a target price of \$50.

The regression is a line of best fit and here there is a high correlation of 70% between valuation and returns on invested capital. This implies that Rocs are predictive of value[l]. 100% described a perfect correlation whereas 0%, as the other extreme, describes total random and uncorrelated relationship between the variables. 