Crocs Analysis

1872 Words Apr 8th, 2011 8 Pages
Crocs Financial Analysis

This case looks at analyzing Crocs, Inc. and the tremendous growth they started off with as a new company in the apparel market. We also analyze Crocs competitors based upon three different ratios (PE, EV to EBITDA and EV to Sales) in order to gain an understanding of where Crocs stands in the market at the time of this case (2007). Using the growth rate estimates, we also value the company’s stock value. Certain assumptions are made regarding the sales and revenues for future years which in turn lead to assumed profit margins.
There are three multiples in the case that can be taken into consideration to compare Crocs with other companies based upon.
 Price Earnings
 EV to Sales
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Using ES ratio for 2011, Crocs’ ES can be calculated using Yeung’s cash flow model as follows:
ES= EV (2011)/ Sales (2011) = 7154/3367=2.12
Companies that compared with this ratio are Volcom at 2.66 and Nike at 1.90. In five years, peer companies that compare to Crocs are Van Heusen, Columbia, Volcom and Nike.
The current multiple used to provide additional estimates for the value of crocs was the EV to EBITDA valuation with the given discount rate of 10.96%. We took the net profit at the projected 5 year period which was $519 million and multiplied it by the average of the three most comparable companies which was Under Armour, Zumiez and Deckers and found the average value of their EV to EBITA then projected that value by the interest rate to the 5th year and was given 7557.58. The formula is below:
[Net profit in 2011 x (32+21.27+20.21)/3]/ (1.10965)
= [519*(32+21.27+20.21)/3]/(1.10965) =7557.584479
Therefore, we assumed the fifth year terminal enterprise value based on Yeung’s cash-flow model was $7557.60.
In order to obtain growth estimates for each year from 2003 to 2012, the data given in Exhibit 1 and Exhibit 6 of the case was used. The growth rate (%) was calculated by looking at the change in revenue from one year to the next starting with year
2003. Functions from Microsoft Excel were used in order to calculate the “high” and “low” growth estimates. Figure 1 shows the growth percentages from 2004 through 2012.
The function to calculate the percentile is

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