Tesla Motors Case Study

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The capital structure of Tesla is financed mostly by debt, being the total debt ratio reasonably stable between 2009-2013. The increase in assets needed to support the sales growth in the past years was done by the same way; we can observe a sudden increase in the debt to equity ratio and in the equity multiplier in 2012 because the company’s equity figure even decreased[2].

2. Percentage of sales method [3]

The percentage of sales method (POS) is based on the premise that the items in the Balance Sheet and the Income Statement vary proportionally with the change in sales. Starting with the sales forecasts for 2014-2017 provided by finanzen.net, we obtained the change in sales for each period; we then constructed the Income Statement and Balance Sheet, and finally identified the external financing need for each period (EFN). It is important to state that we developed our calculations according to the following assumptions:

- Existence of economies of scale in calculating cost expenses, financial feedback was ignored when calculating long-term debt and tax rate = 40% (as stated in the assignment questions).

- The case explains the existence of a no-dividend policy for the current period, it mentions also that Tesla has no intention of changing this in the near future, therefore p = 0.

- Since EFN was financed through long-term debt only, the long-term liabilities in year t include the EFN identified in year t-1.

- The item “other income (expense), net” in the Income Statement refers to changes in the fair value of the DOE common stock warrant liability and foreign exchange gains and losses related to currency changes, it is therefore independent from a change in sales.

The following table illustrates our results from our POS method analysis:

2013

2014

2015

2016

2017

Change in sales

1.81 %

1.44 %

1.31 %

1.36 %

Net income (loss)

-74,014.00

126,238.99

448,285.74

923,438.23

1,696,056.77

Total assets

2,416,930.00

4,366,675.57

6,278,304.74

8,216,918.12

11,170,908.20

Total liabilities

1,749,810.00

2,294,463.84

4,107,322.75

5,578,204.12

6,877,020.81

Total stockholder's equity

667,120.00

793,358.99

1,241,644.73

2,165,082.96

3,861,139.73

EFN

0.00

1,278,852.73

929,337.25

473,631.04

432,747.66

If we compare the years in the table above we can conclude that because the firm initially incurs in losses, a large amount of EFN is needed to support the growth in sales. Because of the no pay-out policy, the income the firm starts to generate on year 2014 goes completely to retained earnings, this leading to a decreasing EFN over the following years.

3. Valuation [4]

i. Growth rate determination for the terminal value period

In order to calculate the growth rate for the terminal value period we used the GDP by industry (in gross output billions) provided. Since an arithmetic mean was not suitable for growth rates we calculated the growth rate mean by using the geometric mean formula. Finally, as it was suggested, we subtracted the FED’s expected long-term inflation (1.7%) and we obtained a growth rate (real) value of : 4.3035366%. We can also state that this value might not be very reliable, since we only used the data accounting for four years. Moreover, during this period the economic crisis took place, strongly affecting the automotive industry.

ii. Pay-out determination for the terminal value period

From the original formula to calculate the SRE : g = ROE * (1 - pay-out ratio) we reached the following identity : pay-out ratio = 1 - (g / ROE) . We calculated the ROE of year 2017 by using the information obtained in Question 2 and applying the formula : ROEt = NIt / EQt, and we arrived to a result of : pay-out ratio = 0.902028302.

In the years 2013-2017 we assumed a company policy of no dividend pay-out and the earnings were entirely invested in assets, therefore Tesla could afford an average change in sales in this period of 47.81%. For the terminal value the growth rate is much smaller, this would imply a very high payout ratio, which was confirmed by our results.

iii. Market risk premium and risk free rate determination

In this section we calculated the annualized geometric mean of the monthly market risk premium and risk free rates provided by the data in the homepage of Kenneth French. We obtained the following results : Mkt-Rf = 0.052325935, Rf = 0.033339662.

iv. Equity beta determination

We performed an OLS-regression of Tesla’s daily returns (dependent variable Y) on Nasdaq Composite’s (independent variable X) in the year 2013 to find the equity beta (regression’s slope parameter). With this process we expected to obtain the effect of a change of the independent variable on the dependent variable.

We selected our