The cost of equity

The Capital Asset Pricing Model (CAPM) is the most recognized method most financial literature suggests using when calculating the required return on equity (Petersen & Plenborg, 2012). CAPM

β_0 β_1 β_2 t_1 t_2

0,02335 -0,00904 0,0305 0,43151 17,64442

80 consists of three components; the risk-free rate(𝑟_y), the equity beta(𝛽_x), and the market risk

premium(𝑟_m− 𝑟_y). Based on the CAPM, cost of equity is calculated as;

𝑟_x = 𝑟_y+ 𝛽_x∗ 𝑟_m− 𝑟_y

In addition, firm-specific measures can be added. The analysis will include a small firm premium on the estimation, which later will be justified. The cost of equity will be modified as;

𝑟_x = 𝑟_y+ 𝛽_x∗ 𝑟_m− 𝑟_y + 𝑠𝑚𝑎𝑙𝑙 𝑓𝑖𝑟𝑚 𝑝𝑟𝑒𝑚𝑖𝑢𝑚

12.1.1. Risk-free rate

The risk-free rate expresses the return an investor can earn without taking any risk. The best estimate of the risk-free rate would be a zero-beta portfolio, tough due to the unpracticality and cost of constructing such a portfolio, Petersen & Plenborg (2012) favor the use of government bonds as a proxy. As

mentioned earlier, the analysis uses a risk-free rate based on a US government bond, which is a good estimation as it has the highest possible rating from rating agencies and therefore reflects a risk-free rate. The risk-free rate is calculated as 2.34%, which can be defined as the long-term risk-free rate.

12.1.2. Systematic risk

The equity beta (𝛽_x) measures the covariance between the returns on a stock or portfolio, and the return on the market portfolio. In CAPM theory the stock’s expected return is driven by the beta, which captures how aligned stock and market movements are (Koller et al., 2010). Damodaran (2012)

expresses the beta by standardizing the covariance as following;

𝛽 =𝐶𝑜𝑣 𝑟_c, 𝑟_m 𝑉𝑎𝑟 (𝑟_m)

Where a beta greater than 1 tends to be more sensitive than the market. On the other hand, a beta below 1 will be less volatile than the market. Both a high and low beta have advantages and disadvantages in terms of risk. A high beta gives the opportunity of higher returns, and a lower beta reduces the

volatility during downturns.

81 There are different methods to estimate the beta for CAPM. One common way is to base it on historical returns, where a regression between the stock and an index reflecting the market portfolio are

conducted. The measurement is estimated through regressions of SSO’s excess return against the market premium. The choice of excess returns instead of raw returns is due to the consideration of spot interest rates varying over the estimated maturity. Furthermore, the analysis will use USD LIBOR 3M to ensure consistency with the risk-free rate above. LIBOR 3M is the interest rate that banks are

charging or receiving when lending or borrowing money to each other for the duration of three months.

Even though SSO is listed on Oslo Stock Exchange (OSE) and three of the largest investors are Norwegian companies, the thesis will not include OSEBX in the regression model. This is mainly due to two factors; the fact that SSO is an international company operating in several countries, and OSEBX to a large degree being dominated by the oil industry. The regression will be based on other international indexes. MSCI World, MSCI Europe and STOXX 600 have been chosen as proxies to the market portfolio. S&P 500 has been excluded from the regression as the index has a correlation of 95,8% with MSCI World (Koller et al., 2010). Daily, weekly and monthly observations on a

measurement period of 4 years will be considered. The reason is that public data is limited as SSO was listed on OSE in 2014. The regressed beta parameters are illustrated below;

Table 6: Regressed Beta Parameters

Source: Datastream / Own creation

In order to test CAPM´s assumption of betas being constant, the analysis will further estimate rolling betas for the different measurement periods. In the search for any patterns or systematic changes in a stock’s return, rolling betas should be graphed (Koller et al., 2010). Koller et al. (2010) recommend including at least 60 data points on the basis of monthly observations in the regression. SSO’s monthly observations are 41 and do not satisfy this requirement. Thus, monthly will be excluded from the

Beta Values Daily Weekly Monthly

Proxy 4 Years 4 Years 4 Years

MSCI World 0,60 0,89 1,16

MSCI Europe 0,56 0,72 0,82

STOXX Europe 0,57 0,73 0,80

Average 0,58 0,78 0,93

Total Average 0,76

82 rolling beta calculations. Daily and weekly observations are respectively 890 and 179 between 2014 and 2018.

Figure 30: Daily Rolling Beta Figure 31: Weekly Rolling Beta

Source: Datastream / Own creation Source: Datastream / Own creation

Figure 30 and 31 interpret that the betas are not constant. In fact, the beta fluctuates from

approximately -0.7 to 1.8, showing no sign of stability. The rolling beta shows that the three indexes follow the same trend. Using an average of all betas in the chosen time-period gives an estimation of;

Table 7: Average Rolling Beta

Source: Datastream / Own creation

Koller, et. al (2010) believes that regressions should be based on monthly returns, and that daily and weekly can lead to systematic biases. However, as mentioned before SSO does not have enough monthly data points, therefore the second-best alternative is using the weekly rolling beta of 0.61. The choice of beta is clearly affected by estimation choices of time-period, return interval and indexes.

Improvement of the estimation can be done through Bloomberg’s smoothening technique, which adjusts the beta regression estimates towards the market beta of one. Smoothening moderate volatile observations towards the overall average (Koller et al., 2010).

𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑 𝑏𝑒𝑡𝑎 =1

3∗ 1 + 0,61 ∗2

3= 0,74

ROLLING BETA

Daily Weekly

Total average 0,55Total average 0,61

83 The final adjusted beta equals 0.74, which defines SSO with less systematic risk than the market

portfolio. The justification of a low beta might be SSO´s business model, where contracts secure revenue streams on a 20-25 years’ basis, independent of marked movements. This is supported by the weekly regression statistics which suggests a <10% R-Squared of SSO and the different indexes. In other words, less than 10% of SSO´s risk is attributable to the market, while the rest is firm-specific.

For a comprehensive regression beta summary see appendix 23 and 24.

12.1.3. Market Risk Premium

The market risk premium is defined as the spread between the market’s expected return and returns from risk-free investments, (𝑟_m− 𝑟_y) (Petersen & Plenborg, 2012). Since, the expected return cannot be observed as a specific number in the market, Petersen & Plenborg (2012) propose two ways of estimating the market risk premium; ex-post and ex-ante approach. The first approach is based on historical excess returns on stock market 50 to 100 years back in time. The intention is that the historical risk premium can be used as an indicator for the future. The second approach uses implied equity premiums as proxy for the market risk premium, assuming the market is correctly priced.

Considering no single model for sizing the market risk premium has gained universal acceptance, the thesis will follow Damodaran’s ex-ante estimates which is one of the five most used in the justification of the risk premium (Petersen & Plenborg, 2012). As mentioned, SSO is operating on an international level with a corresponding peer group. Hence, a suitable market risk premium is the one for United States. Damodaran (2018) lists an implied equity premium of 5.08%. Thus, the thesis will use a market risk premium of 5.08%.

12.1.4. Small Firm Premium

The thesis chooses to include a small firm premium to SSO’s cost of equity. The adjustment is based on the idea of small capitalized stocks yielding higher risk, but also providing greater returns than large capitalized stocks. PWC (2017) conducted a survey in 2017 asking participants if small firm premium should be taken into account when calculating cost of equity. The result indicated that 80% of

Norwegian analysts and economists with experience from the financial and stock market agreed on including such premium (PWC, 2017). Including such a small firm premium will have a significant impact on the WACC, and accordingly be of big importance in the final valuation. As of the cut-off date, SSO had a market cap below NOK 5bn which is the limit to add a small firm premium. A

84 common practice is to add a 3-3.5% premium for small capitalized stocks in emerging markets.

However, as SSO have good contractual terms with customers which secure long-term revenues, the suitable small firm premium falls on 3%.