Orange DRC. Assessing the value of telecommunication investments in the Democratic Republic of Congo

Table of Contents

Executive Summary

1. Introduction

2. Background

3. Discussion
3.1 After-Tax Weighted Average Cost of Capital
3.2 Using CAPM to Measure the Cost of Capital
3.2.1 Airtel’s Equity Beta
3.2.2 Airtel’s Asset Beta
3.2.3 CCT’s Equity Beta
3.2.4 CCT’s Cost of Capital
3.3 CCT’s after-tax Weighted Average Cost of Capital

4. Net Present Value
4.1 Present Value of CCT’s Future Cash Flows
4.2 The Horizon Value
4.3 Investment’s Net Present Value

5. Conclusion

References

Executive Summary

Due to the cost structure of their services, brick-and-mortar branches of traditional financial institutions have been unable to provide financial services to low-income customers, especially those living in remote areas. In the Democratic Republic of Congo (DRC), only 4% of the population has an account at a formal financial institution while mobile penetration in the country is estimated at 17.5% and growing at an average rate of 18% per year (GSMA, 2013).

Therefore, making financial services accessible to the general population through mobile networks in DRC provides enormous financial opportunities for many firms including mobile operators. In fact, revenues from mobile money transactions in the world are estimated to reach $265 billion by 2015, and DRC is one of the most promising mobile money markets in Sub-Saharan Africa (Osikena, 2012, and GSMA, 2013).

In October 2011, France Telecom-Orange (Orange) announced the acquisition of 100 percent of the privately owned DRC mobile operator, Congo-China Telecom (CCT). By investing $273 million, Orange established “Orange DRC”, the fourth major mobile operator in the country with 8.7% of the market share.

Although Orange’s decision to enter the Congolese mobile market was most likely based on massive potential opportunities in the country’s mobile money market, due to an uncertain legal framework, corruption, and lack of transparency in government policies, Orange still needed to ascertain that its investment would be profitable, even if revenues were limited to those generated from standard voice services (Business Wire, 2011).

In this paper, we analyze Orange’s decision of acquiring CCT by estimating the investment’s Net Present Value (NPV) taking into account only the anticipated free cash flows from the voice services in the ten-year period following the acquisition.

Despite CCT’s higher systematic risk and expected cost of capital, the present value of the future cash flows as of October 2011 was estimated as $351 million which alone was sufficient to make the investment a profitable one. Taking into account the investment’s horizon value, we estimate the NPV at $2.06 billion and therefore conclude that the acquisition of CCT was a sound financial decision, one that could substantially increase Orange’s shareholder value in the long run.

1. Introduction

In October 2011, as part of the company’s international strategy to stimulate growth by entering high potential emerging markets, France Telecom-Orange (Orange) announced the acquisition of 100% of the privately owned mobile operator “Congo-China Telecom (CCT)” in the Democratic Republic of Congo (DRC) (Orange Press Release, 2011).

It is likely that Orange’s main motivation for this acquisition was to become involved in DRC’s significantly promising mobile money market from its infancy. However, due to the risks involved, the company needed to build its business case taking into account a worse case scenario where anticipated revenues would be limited to those generated from the standard voice services.

The aim of this paper is to evaluate Orange’s decision of acquiring CCT to determine whether, even on a worse case scenario basis, the anticipated revenues would be sufficient to increase shareholders’ value and justify this investment. This is achieved by estimating the investment’s Net Present Value (NPV), taking solely into account the anticipated free cash flows from the voice services during the ten-year period following the transaction.

Our evaluation will entail that we first estimate CCT’s equity beta and weighted average cost of capital (WACC) and then estimate the present values of the free cash flows as well as the “horizon value” through discounting them by the estimated WACC.

2. Background

This section aims to familiarize the reader with some of the details of the acquisition.

The acquisition resulted from two main transactions:

(1) Under the terms of a share purchase agreement signed with ZTE, Orange paid $10 million for ZTE’s 51% share of CCT equity.

(2) Under the terms of a share purchase agreement signed with the government of DRC, Orange paid $7 million for the government’s 49% share of CCT equity.

In addition, Orange paid $71 million to the government of the DRC for a 10-year extension of CCT’s 2G and 3G licenses. Finally, Orange contributed $185 million to assume liabilities of CCT and improve its operations (Orange Press Release, 2011).

Therefore, Orange made a total investment of $273 million to establish “Orange RDC”, the fourth major DRC mobile operator (Index Mundi, 2014).

3. Discussion

3.1 After-Tax Weighted Average Cost of Capital

In order to measure the opportunity cost of investing in CCT’s assets, one needs to calculate the after-tax cost of debt as well as the cost of capital for the investment. Combining the two values results in the after-tax WACC that can be used to discount CCT’s future cash flows.

It is important to note that since the target firm (CCT) becomes a wholly owned subsidiary of the acquirer (Orange), we are in a position to use Orange’s cost of debt in the calculation of the WACC. In other words, by using Orange’s excess debt capacity, we are not subsidizing CCT’s stockholders since in this case there are no other shareholders than Orange’s itself.

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Since there is no available information on debt and equity ratios in financing the CCT acquisition, we have made assumptions to calculate these ratios. Nonetheless, these assumptions are based on other available information, such as: Orange’s net financial debt of $39.7 billion as of the end of 2011 (Orange Financial Statements, 2012), its low share price of $18 in October 2011, and the company’s 87% of gross debt in bonds as of the end of 2012 (Orange Presentation, 2013). On this basis, it appears that the least expensive way for Orange to raise capital for the acquisition was through the issuance of bonds. For the purpose of this paper, we have assumed that the financing raised for the acquisition of CCT comprised a 70:30 capital structure, therefore:

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However, the acquisition of CCT and operating in the DRC entail a different risk level than Orange’s existing business, which is diversified between both mature and emerging markets. Therefore, we rely on the value-additivity principle and assess the investment at its own opportunity cost of capital rather than at Orange’s cost of capital (Brealey et al., 2014).

3.2 Using CAPM to Measure the Cost of Capital

In order to estimate CCT’s cost of capital, we need to measure the firm’s market risk or “equity beta”. However, since CCT was a private company we have based ourselves on the equity beta of a comparable public firm that specializes in the mobile telecommunications industry in the DRC.

Ranked as the first mobile operator of that country, “Airtel” is traded on both NYSE and BSE and specializes in mobile communications in Africa and other emerging markets and would serve as a suitable pure-play company for estimating the CCT’s equity beta.

3.2.1 Airtel’s Equity Beta

Equity beta or systematic risk is a measure of sensitivity of a security to market movements (Brealey et al., 2014), and is an important component of event studies since it enables us to isolate firm-specific effects from market-wide effects (Hong and Sarkar, 2007).

Table-1 lists investment return data for Airtel and S&P BSE 200 Index Fund, which includes Airtel as one of its holdings.

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Table1- Investment Return Data (Source: Yahoo Finance)

By running a linear regression of Airtel’s monthly returns against the S&P BSE 200 Index Fund’s we can measure the company’s equity beta. Figure-1 shows the result of the performed regression.

Figure 1- Result of the Linear Regression. Author’s own illustration.

By taking into account the value of the coefficient of determination (R²), one can observe that the model explains 24% of the variability of the response data around its mean. The value of R² indicates positive relationship between the predictor (market return) and response (Airtel return) variables, and describes 76% of the risk associated with Airtel’s stock as being idiosyncratic and unrelated to the overall market risk (Frost, 2013).

Table-2 shows the model parameters for the performed linear regression.

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Table2- Regression Model Parameters. Author’s own table.

As shown in Table-2, the performed regression resulted in an equity beta of 1.1 which indicates that Airtel’s stock tends to closely follow the market and is therefore exposed to possible negative and positive black swans hitting the market. Nevertheless, this value also suggests that the stock is not over-sensitive to market fluctuations (Estrada and Vargas, 2012).

The low value of “P” (< 0.05) indicates that changes in the predictor variable are in fact related to the changes in the response variable. The “t” and “P” values suggest that 98.5% of the t-distribution is closer to the mean than t=2.64. In other words, there is 95% probability that the value of beta falls between 0.248 and 2.040. Therefore, we can suggest that our predictor is meaningful in our regression model, and we can rely on the value of beta (Princeton, 2013).

3.2.2 Airtel’s Asset Beta

In order to measure the average risk of Airtel’s business, we need to measure its asset beta:

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Asset beta measures the overall risk of the business taking into account the risk of debt as well as equity. However, in practice debt is assumed to be riskless since the value of debt beta is very small.

Assuming debt to be riskless , we will have the following de-leveraged relationship between asset beta and equity beta:

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Since (Source: EquityMaster) we can calculate the equity ratio as , therefore:

3.2.3 CCT’s Equity Beta

Assuming equal asset betas for CCT and Airtel:

CCT’s equity beta can be calculated by re-levering the asset beta at CCT’s capital structure:

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Assuming debt to be riskless :

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Although we assumed asset beta to be the same for CCT and Airtel, the equity beta for CCT is higher than Airtel’s equity beta since the capital structures of the two firms are quite different. CCT’s higher financial leverage results in an increase of its equity beta, which makes its shares over-sensitive to market fluctuations.

3.2.4 CCT’s Cost of Capital

Since Treasury bills (T-bills) are considered the least risky short-term investments due to their fixed return and insensitivity to market fluctuations , their rate of return can be used as the risk-free interest rate.

Although CAPM is a short-term model and calls for a short-term risk-free rate, one needs to estimate the expected long-term return from investing in T-bills in order to obtain the right discount rate for cash flows many years in the future. In order to get this estimate, we need to subtract the extra return expected from long-term bonds versus T-bills (risk premium) from the yield on long-term bonds (Brealey et al., 2014).

We know that in the United States investors expect an average additional return (average risk premium) of 1.4% from long-term government bonds versus T-bills (Brealey et al., 2014). We also know that the rate of return for the US government’s long-term bonds for the month of October 2011 averaged 2.79% (Source: US Department of The Treasury), therefore we can calculate as:

Given an average market risk premium of 5.5% in the United States (Fernandez et al., 2011), the cost of capital for CCT can be calculated as:

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3.3 CCT’s after-tax Weighted Average Cost of Capital

Having all the necessary information available, we are now in a position to calculate the after-tax WACC for CCT:

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4. Net Present Value

NPV is defined as the difference between an investment’s present value and its cost. Therefore, any investment with positive NPV is considered financially sound, and in theory profitable to the investor (Brealey et al., 2014).

NPV = Present Value of the Investment (PV) – Investment’s Cost

Where

PV of the Investment = PV of cash flows + PV of horizon value

To estimate the NPV, we need to estimate the investment’s free cash flows for the specified period, find the horizon value, and then use the discounted cash flow formula to estimate the present value (PV) of the investment.

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4.1 Present Value of CCT’s Future Cash Flows

Free cash flow is the amount of cash that the firm can pay out to investors after making all investments necessary for growth and is calculated assuming the firm is all-equity financed (Brealey et al., 2014).

The number of mobile subscribers in Sub-Saharan Africa has shown an average yearly growth of 18% between 2008 and 2013 (GSMA, 2013), and the Average Revenue Per User (ARPU) in DRC is approximated as $72 per year. With nearly 1.35 million subscribers as of October 2011, CCT’s market share in DRC was estimated at 8.7% (Index Mundi, 2014).

Assuming a constant mobile subscriber growth of at least 18% until 2021, a fixed ARPU, an average capital expenditure of 13%, and average Orange EBITDA of 31.54% of revenue (Orange Financial Results, 2013), we can estimate the free cash flows for CCT provided that the company maintains the same market share.

Discounting the cash flows by a discount factor of 1.0584 (1+ after-tax WACC) will result in the total present value of CCT’s future cash flows. Table-3 shows the CCT’s estimated cash flows and their present values between 2012 and 2021.

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Table3- CCT's Cash Flow Analysis (Source: Index Mundi, Orange's Financial Statements, and Panda.org)

4.2 The Horizon Value

To estimate the horizon value of the investment in 2021, we assume a long-run subscriber market growth of 3% per year. Therefore, with free cash flow of $98 million in 2022, the horizon value of the investment in 2021 can be estimated as:

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As a result, the present value of the horizon value at year 0 can be calculated as:

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4.3 Investment’s Net Present Value

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We can observe that the present value of the cash flows between 2012 and 2021 ($351.1 million) is alone sufficient to make the investment profitable.

5. Conclusion

The resulting positive NPV indicates that Orange’s acquisition of CCT was in fact a sound financial decision. This is in part based on the fact that even if limited to voice services, anticipated revenues are likely not only to allow Orange to recover its initial investment by the year 2021, but also to generate profits.

That being said, it is reasonable to believe that Orange’s decision to enter the DRC mobile market was principally motivated by plans to penetrate the mobile money market where anticipated revenues and profits are even more significant. However, the fact that the forecasted cash flows from the voice services led to a positive NPV for the investment was definitely regarded as a safety cushion in case plans to implement massive revenue generating services such as “Mobile Money” do not progress as anticipated.

References

Brealey, R. A., Myers, S. C., and Allen, F., 2014. Principles of Corporate Finance. Maidenhead: McGraw-Hill Education.

Business Wire, 2011. Research and Markets: Democratic Republic of Congo – Telecoms, Mobile and Broadband – 2011. Available at: < http://www.businesswire.com/news/home/20110321005779/en/Research-Markets-Democratic-Republic-Congo---Telecoms#.UyIL3VFdX6Z> [Accessed 18 March 2014].

Estrada, J., and Vargas, M., 2012. Black Swans, Beta, Risk, and Return. Journal of Applied Finance. Available through: University of Warwick Library Website: < http://encore.lib.warwick.ac.uk> [Accessed 6 March 2014].

Fernandez, P., Aguirreamalloa, J., and Corres, L., 2011. Market Risk Premium Used in 56 Countries in 2011: A Survey with 6014 Answers. [pdf] IESE Business School-University of Navarra. Available at: < http://www.iese.edu/research/pdfs/di-0920-e.pdf> [Accessed 10 March 2014].

Frost, J., 2013. Regression Analysis: How do I Interpret R-squared and Assess the Goodness- of-Fit? [blog] 30 May. Available at: < http://blog.minitab.com/blog/adventures-in-statistics/regression-analysis-how-do-i-interpret-r-squared-and-assess-the-goodness-of-fit > [Accessed 6 March 2014].

GSMA, 2013. Mobile Money in the Democratic Republic of Congo: Market insights on consumer needs and opportunities in payments and financial services . [pdf] GSMA. Available at: < http://www.gsma.com/mobilefordevelopment/wp-content/uploads/2013/07/Mobile-Money-in-the-DRC_July-2013.pdf> [Accessed 14 March 2014].

GSMA, 2013. Sub-Saharan Africa Mobile Economy 2013. [pdf] GSMA. Available at: < http://www.gsmamobileeconomyafrica.com/Sub-Saharan%20Africa_ME_Report_English_2013.pdf> [Accessed 20 March 2014].

Hong, G., and Sarkar, S., 2007. Equity Systematic Risk (Beta) and Its Determinants. Contemporary Accounting Research, Vol.24, No. 2. Available through: University of Warwick Library Website: < http://encore.lib.warwick.ac.uk> [Accessed 10 March 2014].

Index Mundi, 2014. Cellphone Companies in Democratic Republic of the Congo. Available at: < http://www.indexmundi.com/democratic_republic_of_the_congo/cell-phone-companies-in-democratic-republic-of-the-congo.html> [Accessed 5 March 2014].

KPMG, 2011. Democratic Republic of Congo Fiscsal Guide 2011. Available at: < http://www.kpmg.com/Africa/en/Documents/DRC Fiscal Guide 2011.pdf> [Accesses 6 March 2014].

Orange Financial Statements, 2012. Consolidated Financial Statements, Year ended December 31, 2012. Available at: < http://www.orange.com/en/finance/nbsp2/investors-and-analysts/all-consolidated-results > [Accessed 6 March 2014].

Orange Presentation, 2013. France Telecom-Orange FY 2012 Results, 20 February 2013 Presentation. Available at < http://www.orange.com/en/finance/nbsp2/investors-and-analysts/all-consolidated-results> [Accesses 6 March 2014].

Orange Presentation, 2014. France Telecom-Orange FY 2013 Results, 6 March 2014 Presentation. Available at < http://www.orange.com/en/finance/nbsp2/investors-and-analysts/all-consolidated-results> [Accessed 14 March 2014].

Orange Press Release, 2011. France Telecom-Orange to acquire 100% of Congo Chine Telecom (CCT), a mobile operator in the Democratic Republic of the Congo. [press release] 20 October 2011. Available at: <http://www.orange.com/en/press/press-releases/press-releases-2011/France-Telecom-Orange-to-acquire-100-of-Congo-Chine-Telecom-CCT-a-mobile-operator-in-the-Democratic-Republic-of-the-Congo> [Accessed 4 March 2014].

Osikena, J., 2012. The Financial revolution in Africa: Mobile Payment Services in a New Global Age. [pdf] The Foreign Policy Center, Foreign and Commonwealth Office. Available at: < http://fpc.org.uk/fsblob/1518.pdf> [Accessed 14 March 2014].

Princeton University: Data and Statistical Services, 2013. Interpreting Regression Output. Available at: < http://dss.princeton.edu/online_help/analysis/interpreting_regression.htm> [Accessed 9 March 2014].