Valuing Emerging Markets Companies: New Approaches to Determine the Effective Exposure to Country Risk

Transcription

1 Valuing Emerging Markets Companies: New Approaches to Determine the Effective Exposure to Country Risk Oliviero Roggi, Alessandro Giannozzi and Tommaso Baglioni #03/2016 February 2016 Apoio:

2 FGV/EAESP Working Papers Series Valuing Emerging Markets Companies: New Approaches to Determine the Effective Exposure to Country Risk Version 1.0 February 2016 Oliviero Roggi Dipartimento di Scienze per l'economia e l'impresa/università Degli Studi Firenze Alessandro Giannozzi Dipartimento di Scienze per l'economia e l'impresa/università Degli Studi Firenze Tommaso Baglioni FGV/EAESP Abstract: The aim of this paper is to propose new methods to measure the effective exposure to country risk of emerging-market companies. Starting from Damodaran (2003), we propose seven new approaches and a revised CAPM for emerging markets companies. The Prospective Lambda represents the effective exposure according to analysts estimates of growth. The Relative Lambda relies on the firm value estimated through a relative valuation. The Retrospective Lambda represents the ex-post effective exposure to country risk. The Company Effective Risk Premium is a generalization of the Retrospective Lambda, and expresses the premium effectively requested by investors to invest in that specific company in the past year. The Actual Lambda and the Company Actual Risk Premium represent, respectively, the actual exposure to country risk of a company and the actual premium requested by investors to invest in that specific company. The Industry Lambda reflects the median exposure to country risk of the industry in which the company belongs. We tested our new measures of exposure to country risk on the Latin American emerging markets companies according to the classification of the MSCI Emerging Markets Latin America Index. The results confirm that the new approaches can be effectively applied by financial analysts to stable-growth companies that operate in emerging markets and to mature markets companies that operate in emerging markets, providing with a more reliable estimate of both the premium effectively requested by investors in the past and the actual premium. Applying the new approaches, the cost of equity reflects the effective exposure of a company to country risk without being over- or underestimated, as is the case with other existing approaches. Oliviero Roggi, Alessandro Giannozzi and Tommaso Baglioni.

3 Valuing Emerging Markets Companies. New Approaches to Determine the Effective Exposure to Country Risk. Oliviero Roggi, Alessandro Giannozzi and Tommaso Baglioni. ABSTRACT The aim of this paper is to propose new methods to measure the effective exposure to country risk of emerging-market companies. Starting from Damodaran (2003), we propose seven new approaches and a revised CAPM for emerging markets companies. The Prospective Lambda represents the effective exposure according to analysts estimates of growth. The Relative Lambda relies on the firm value estimated through a relative valuation. The Retrospective Lambda represents the ex-post effective exposure to country risk. The Company Effective Risk Premium is a generalization of the Retrospective Lambda, and expresses the premium effectively requested by investors to invest in that specific company in the past year. The Actual Lambda and the Company Actual Risk Premium represent, respectively, the actual exposure to country risk of a company and the actual premium requested by investors to invest in that specific company. The Industry Lambda reflects the median exposure to country risk of the industry in which the company belongs. We tested our new measures of exposure to country risk on the Latin American emerging markets companies according to the classification of the MSCI Emerging Markets Latin America Index. The results confirm that the new approaches can be effectively applied by financial analysts to stable-growth companies that operate in emerging markets and to mature markets companies that operate in emerging markets, providing with a more reliable estimate of both the premium effectively requested by investors in the past and the actual premium. Applying the new approaches, the cost of equity reflects the effective exposure of a company to country risk without being over- or underestimated, as is the case with other existing approaches. KEYWORDS: Emerging markets, cost of equity, country risk premium, lambda, stablegrowth firms, Company Effective Risk Premium, Company Actual Risk Premium. 1

4 1. INTRODUCTION. Valuation in emerging markets is a topic that is extensively discussed in the literature. Companies that operate in emerging markets are exposed to a series of risks that are not faced by mature-market companies. Consequently, investors require a higher return than that requested in a mature market, and hence the cost of equity needs to be adjusted to reflect the additional risk perceived, taking into account a country risk premium. The majority of the models of country risk proposed in the literature do not consider the fact that a firm incorporated in an emerging market might operate mainly in mature markets and vice versa, i.e., a firm incorporated in a developed market may have a significant amount of operations in undeveloped markets. Therefore, each company has a different exposure to country risk, depending on where it operates, and the adjusted cost of equity needs to reflect this exposure. The main literature in this field (Damodaran, 2003) proposes three methods, called lambda, to estimate companies effective exposure to country risk. The first method is based on the percentage of revenues that the company earns in the local market, compared with the revenues that the average company earns in the local market. The second approach is based on a comparison of the change in earnings per share of the company, denominated in the country s currency, and the change in the country sovereign bond denominated in US dollars. The last method (regression approach) considers the sensitivity of the company stock returns to the returns of the country sovereign bond denominated in US dollars. The aim of this paper is to propose new methods to measure the effective exposure to country risk of emerging-market companies. The first method, called the Prospective Lambda, represents the effective exposure according to analysts estimates of growth. The second method, called the Relative Lambda, relies on the firm value estimated through a relative valuation. The third method, called the Industry Lambda, reflects the median exposure to country risk of the companies that belong to a specific industry. The fourth method, called the Retrospective Lambda, represents the ex-post effective exposure to country risk; hence, it refers to historical data, while the Company Effective Risk Premium is a generalization of the Retrospective Lambda and expresses the premium effectively requested by investors to invest in that specific company. The last two methods are called Actual Lambda and Company Actual Risk Premium. They represent, respectively, the actual exposure to country risk of a company, and the actual premium effectively requested by investors at the time of the valuation. The country risk premium model implemented in our analysis is the one proposed by Damodaran (2003), which is called the melded approach. This model considers both the country bond default spread and the volatility of equity markets in a country relative to the volatility of the country bond denominated in US dollars. The empirical analysis is based on 58 companies listed on the main market-capitalization weighted index (including the most liquid stocks) of Brazil, Chile, Colombia, Mexico and Peru for the years 2013 and First, we tested existing measures of a company s exposure to country risk with Brazilian companies. In particular, to test the effectiveness of the existing measures, we regressed companies stock returns against the 10-year Brazilian sovereign bond denominated in US dollars. Second, we tested the new measures of a company s exposure to country proposed in this study 1, the Retrospective Lambda, the Company Effective Risk 1 The first three methods were not tested because are based on analyst estimates of growth, which are not very reliable, especially for emerging markets. For the implementation of the Industry Lambda, a significant number of peers for each company is needed as well. 2

5 Premium, the Actual Lambda and the Company Actual Risk Premium, on the companies of Brazil, Chile, Colombia, Mexico and Peru 2. The results demonstrate that both in 2013 and 2014, the extra return asked to invest in Latin American emerging markets was on average greater than the value of the country risk premium obtained from existing measures. This result confirms that the approaches to measure the exposure to country risk proposed in this study can be effectively applied by financial analysts to stable-growth companies that operate in emerging markets. We improve upon the existing literature in several aspects: first, we propose new approaches to measure the effective exposure to country risk that yield estimates of the premium effectively requested by investors in the past, the actual premium requested by investors and the premium linked to future growth estimates; second, we propose a revised CAPM for emerging markets companies. Moreover, the latter approach can be generalized to allow for a first period of high growth. In contrast with the previous literature, we developed an approach to estimate the lambda through the relative valuation price and an approach to consider the exposure to country risk of the industry in which the company belongs. We suggest using the Relative Lambda if the company is actually considered to be under- or overvalued by the market, and to use the Industry Lamba for high-growth companies, in order to estimate the potential exposure to country risk in the stable-growth phase (Terminal value). The paper is structured as follows: Section 2 presents a literature review. Section 3 reports the results obtained using the regression approach. Section 4 is dedicated to the new approaches to measure companies exposure to country risk. Section 5 presents the results of the empirical analysis. Conclusions are offered in Section THE COST OF EQUITY IN EMERGING MARKETS AND A COMPANY S EXPOSURE TO COUNTRY RISK: A LITERATURE REVIEW. Estimating the cost of equity in emerging markets Estimation of the discount rate for an investment project under conditions of risk relies upon two crucial assumptions: market completeness and well-diversified investors. Although these two assumptions are tenable in developed capital markets, they are not suitable in emerging markets (Mongrut and Ramírez, 2006). In this section, we review the main models proposed in the literature for estimation of the cost of equity in emerging markets. Whereas in mature markets the cost of equity is mostly estimated through the standard CAPM, its implementation for valuation in emerging markets leads to several problems. In emerging markets, betas tend to be very low (Harvey, 1995) and not correlated with stock returns (Estrada, 2001), thus leading to low required returns when applied in the CAPM. Consequently, over the past decades, many alternative methods to estimate the cost of equity in emerging markets have been proposed; examples include Estrada (2000, 2001, 2002), Lessard (1996), Damodaran (2003), and Godfrey and Espinosa (1996). The main models developed have been classified according to their nature and to the investor s nature and amount of diversification. In particular, Pereiro (2001) classified the 2 The analysis excludes preferred stocks and units that are comprised of different equities, e.g., a mix common and preferred stock. Because of the impossibility of having a reliable estimate of their free cash flows, banks and insurance companies have also been excluded from the analysis. 3

6 models as CAPM-based and non-capm-based, whereas Fuenzalida and Mongrut (2010) classified them according to the whether the investor is a globally well-diversified investor, an imperfectly diversified local institutional investor or a non-diversified entrepreneur. We classified the models according both to the investor s nature and the nature of the model, with the latter factor reflecting whether the model is based on the CAPM. Table 1 reports our classification. MODELS CLASSIFICATION CAPM-BASED MODEL NON CAPM-BASED MODEL GLOBAL WELL-DIVERSIFIED INVESTOR Global CAPM (Stulz 1995) D-CAPM model (Estrada 2002) Damodaran model (2003) Adjusted Local CAPM (Pereiro 2001) Adjusted Hybrid CAPM (Pereiro 2001) Goldman Sachs model (Mariscal and Hargis 1999) Hybrid model (Bodnar, Dumas and Marston 2003) Lessard model (Lessard 1996) Local CAPM (Stulz 1995) Salomon Smith Barney model (Zenner and Akaydin 2002) Soenen and Johnson Model (2008) IMPERFECTLY DIVERSIFIED LOCAL Damodaran total beta (2003) INSTITUTIONAL INVESTOR Godfrey and Espinosa model (1996) NON-DIVERSIFIED ENTREPRENEUR Erb-Harvey-Viskanta model (1995) Table 1. Classification of the main models developed for estimation of the cost of equity in emerging markets. Three types of investors operate in emerging markets: globally well-diversified investors (such as foreign mutual funds), imperfectly diversified local institutional investors and nondiversified entrepreneurs. The majority of local investors are local institutional investors, which are imperfectly diversified because of legal restrictions regarding investing abroad, as in the case of Peru, where pension funds are the biggest institutional investors and have an investment limit for foreign investments of 12.5%. The majority of firms are either small or medium enterprises owned by a single entrepreneur or a group of non-diversified entrepreneurs, who usually invest all of their money in the enterprise without being concerned with diversification. These small or medium enterprises are fully exposed to country risk. The majority of the models proposed in the literature are CAPM-based models, which can be applied to estimate the cost of equity in emerging markets in the case of a globally welldiversified investor. The most widely known models are the Global CAPM and the Local CAPM (Stulz, 1995). The former model views the company as part of a global portfolio of stocks and could be applied to an emerging market when the investor believes in market integration. In fact, the assumption underlying the model is that unsystematic risk disappears because of geographical diversification. The formula is the same as that of the standard CAPM, but the global CAPM is implemented by using a global risk-free rate, calculating beta with a regression against a global index and using a global market return (MSCI). In contrast, the Local CAPM is determined by using both the risk-free rate and the market return of the emerging market country and computing beta by regressing the emerging market company returns against returns on the emerging market index. Finally, a country risk premium is added to take into account the additional risks that arise from the fact that the company is incorporated and operates in a non-mature market. Bodnar, Dumas and Marston (2003) state that both local and global factors are important for the pricing of securities in emerging markets and propose a model, called the Hybrid model, in which beta is estimated both in respect to the global and local markets through a multiple regression model: Ri Rg = αi + βg (Rg rg ) + βem (Rem rl) + ei. The global and local market risk premiums (Rg and Rem) are estimated with respect to their risk-free rates (rg and rl). The MSCI World Index is used to calculate the global equity risk premium, and the local MSCI Emerging Markets Index is used to estimate the local equity risk premium. 4 Estrada Downside Risk model (2000, 2001)

7 A modification of the Local CAPM is the Adjusted Local CAPM, which was proposed by Pereiro (2001) to correct the systematic risk premium. In fact, Erb et al. (1995) demonstrated that 40% of the variation in the market return volatility is explained, on average, by country risk, which already includes a component of macroeconomic risk, whereas pure stock market risk explains the remaining 60%. In the Adjusted Local CAPM, beta is multiplied by (1-40%) to avoid overestimating the cost of equity because of double-counting risk. Lessard (1996) believes that formulation of a risk-adjusted discount rate may be useful as an initial screening approach when dealing with offshore investments. He includes in the cost of equity the risk premium that investors would require for a comparable project located in the US by multiplying the beta of the company (computed against the emerging market equity index) by the beta of the emerging market (computed relative to the US). A modification of Lessard s model is the Adjusted Hybrid model, which was proposed by Pereiro (2001). Global data (instead of US data) are used for the computation of the risk-free rate, beta, which is calculated against the global market index, and the market premium. The product of beta and the market premium is multiplied by both the average beta of the comparables and by (1 40%) to take into account only the portion of the variation in the market return volatility explained by the country risk. Lessard s model is not applicable when the firm subject to valuation is located in certain emerging markets. In fact, Godfrey and Espinosa (1996) demonstrated that if it is computed against the US market, the beta of countries such as Venezuela and Argentina might be negative. Hence, if Lessard s model is implemented, the risk premium for investing in such countries would be negative. Godfrey and Espinosa (1996) proposed a model for the computation of the cost of equity that takes into account the country risk premium and adjusts beta, which is calculated as the ratio of the standard deviations of the local country equity market and the US equity market, by multiplying it by (1 40%) to (again) avoid overestimating the country risk. Godfrey and Espinosa s (1996) ideas clearly inspired Mariscal and Hargis (1999), who developed a model for the investment bank Goldman Sachs. They introduced the concept of company-specific risk factor, which can be positive or negative depending on the company s characteristics. A country risk premium is also added to the cost of equity, whereas beta is multiplied by both the ratio of the volatility of the local equity market to that of the US market and the reciprocal of the correlation of the dollar returns of the local stock market and those of the sovereign bond used to measure country risk. Instead of using volatility as a risk measure, Estrada (2000, 2001) suggested a non CAPMbased model that considers only the downside risk. Beta is substituted by the ratio of the semi-standard deviations of returns with respect to the mean of the emerging market and the world market (US market). A revised version of the downside risk model is the D-CAPM model (Estrada, 2002). The author argued that the use of a measure of total systematic risk (i.e., beta) is not adequate because it does not reflect investors real concern: the risk of loss. In the Downside Risk CAPM (D-CAPM), beta, which is called the Downside Beta (D-Beta), is computed as the product of the semi-standard deviation of security i and the semi-standard deviation of the global market (global index of MSCI) divided by the market s semi-variance of returns. Soenen and Johnson (2008) proposed a model to determine the cost of equity in emerging markets, adjusting both for the lack of integration of the local equity market with the US stock market and country risk. The CAPM was modified to incorporate both an estimate of political risk and a measure of the co-movement between the foreign equity market and the US stock market. The spread between the yield of the US dollar-denominated sovereign bonds issued by the foreign government and the yield of the US sovereign bond (with the same maturity) reflects political risks, which include expropriation, currency inconvertibility, unrest and civil war. An additional risk factor, which accounts for the differences in the equity markets of the 5

8 US and the target emerging market, was proposed. In this model, the equity market risk is calculated by regressing US stock returns (independent variable) against the emerging market stock return. Zenner and Akaydin (2002) developed an approach for the U.S. investment bank Salomon Smith Barney. They argue that different industries are affected differently by the emerging market risk and developed a model that adds to the traditional CAPM a country risk premium that is adjusted for the industry s impact. Estimation of the cost of equity of non-diversified entrepreneurs is a topic that has been rarely explored in the literature. The most appropriate model was proposed by Erb, Harvey and Viskanta (1995) and is useful for economies with no stock market. The model is based on the country credit risk ratings and is implemented by regressing semiannual return in US dollars for emerging market country i (CSi) against country i credit rating (CCR), where t is measured in half-years. Damodaran (2003) states that the increase in the correlation across markets has resulted in a portion of country risk (or market risk) that is non-diversifiable and proposes three approaches to measure the country risk premium. The first approach relies on default spreads on country bonds and calculates the country risk premium as the difference among the yield of the sovereign US dollar-denominated bond of the emerging country and the US sovereign bond with same maturity. The second approach is based on the equity market volatility and computes the country risk premium by subtracting the US equity risk premium from the emerging country equity risk premium. The emerging country equity risk premium is obtained by multiplying a measure of the relative standard deviation (the ratio of the standard deviation of the emerging market to the standard deviation of the US market) and the US equity risk premium. The last approach is a blended approach that uses both default spreads and equity market volatility: the country risk premium is computed as the product of the default spread and the ratio of the standard deviation of the country equity market to the standard deviation of the US dollar-denominated sovereign bond. The cost of equity for the emerging market firm is computed by adding the country risk premium to the standard CAPM. Damodaran proposed three approaches for estimation of asset exposure to country risk, which result in three different methods to add the country risk premium to the standard CAPM. In fact, assuming that the exposure to country risk is equal for all of the companies in a country, the country risk premium is added to the standard CAPM formula. If a company s exposure to country risk is proportional to its exposure to market risk, the country risk premium is added to the equity risk premium. The third approach allows for each company to have an exposure to country risk that is different from that of all other market risk and thus adds a portion of the country risk to the cost of equity of a mature-market firm. Damodaran (2012) also proposed a model for estimating the cost of equity in the case of an imperfectly diversified investor. He proposed modifying beta by dividing it by the correlation between the firm and the market to arrive at a measure of the total beta. In this manner, the more diversified the buyer, the higher the correlation with the market and the smaller the total beta adjustment. For instance, if the reason for the valuation is an IPO, the beta of the company does not need to be adjusted for non-diversification because stock market investors are the potential buyers. All of the models presented in this section are reported in Table 2 with their respective formulas. 6

9 Table 2. Main models for computation of the cost of equity (K e) in emerging markets. 7

10 Each of the models presented in this section leads to a different estimate of the cost of equity, thus making the choice among them a critical decision for analysts. However, not all firms are equally exposed to country risk; thus, the effective exposure to country risk is needed in company valuation. Moreover, the cost of equity might be over or under-estimated, thereby leading to under- or over-estimation, respectively, of the firm value. As previously asserted, Damodaran (2003) was the first one to address this problem, and he proposed the three models described in following paragraph. Measuring a company s exposure to country risk In our opinion, none of the models described in the previous section lead to a correct estimate of the cost of equity: it might be over- or under-estimated if the company operates or has production facilities in countries different from the one in which it is incorporated. To correctly estimate the adjusted discount rate, we need to consider the portion of country risk that affects the company. In other words, we need to determine how much the company is exposed to the risks, such as political and economic risks, that affect the country in which it is incorporated and are reflected in the country risk premium. Thus, the cost of equity can be overestimated if a firm is incorporated in an emerging market but has a significant amount of operations in mature markets. In contrast, it can be underestimated when considering a developed-market company with a significant amount of operations in undeveloped markets. When a firm is exposed to riskier countries, we need to separately consider the portion of each country risk that affects the company and add all of them to the cost of equity of a mature-market firm that operates in mature markets only. As previously stated, Damodaran (2003) proposed a measure of a company s exposure to country risk, called lambda (λ), and the following approaches for its estimation: The revenues approach The accounting earnings approach The regression approach The first approach takes into consideration only where the revenues are generated, stating that a company that derives a small percentage of revenues in the country should be less exposed to country risk than the average company should. Thus, lambda is estimated by dividing the percentage of revenues that the company earns in the country in which it is incorporated by the percentage of revenues that the average company in the market earns in that country: λx = % % (2.1) Because it might not be possible to obtain an estimate of the denominator, this value can be approximated by the percentage of GDP that is domestically directed, which is calculated as the reciprocal of the percentage of GDP that comes from exports, which can be easily obtained. The second approach proposed by Damodaran expresses the sensitivity to country risk by comparing the change in earnings per share, denominated in the country s currency, with the change in the sovereign bond denominated in US dollars with 10-year maturity. The many problems concerning the use of accounting earnings, such as manipulation, make this method unreliable. 8

11 The last approach is the regression method. It consists of estimation of lambda through a regression of company stock returns against the return of the 10-year sovereign US dollardenominated bond issued by the emerging country. The slope of the regression indicates the sensitivity of the stock prices to country risk and is taken as a measure of lambda. Both of these approaches can be used only when the risk exposure is concentrated in just one emerging market. To solve the problem concerning risk exposure in many countries, Damodaran proposed estimation of a country-specific lambda for each of the countries in which the company operates. In the first two approaches, lambda is calculated by separately considering the portion of revenues or earnings that come from each risky market, whereas in the third approach, the returns of the sovereign US dollar-denominated bond issued by the other emerging markets are used as the regressor in a multiple regression. In our study, we decided to test only the regression approach in order to have a significant number of observations. In particular, we regressed the stock returns of Brazilian companies listed on the Ibovespa against the 10-year Brazilian sovereign bond denominated in US dollars. The idea was to calculate lambda to check how the effective exposure to Brazil s country risk of each company of the Brazilian equity index changed over the period of as Brazil s country risk premium changed. The results of the regression analysis are presented in the next section. Starting from Damodaran (2003), we propose new methods to determine the effective exposure to country risk of emerging-market companies, and we test them with the companies of the leading indicators of the Brazilian, Chilean, Colombian, Mexican and Peruvian stock market's average performance: the Bovespa, Ipsa, Colcap, Mexbol, and Igbvl Index. 3. TESTING EXISTING MEASURES OF COMPANY EXPOSURE TO COUNTRY RISK USING BRAZILIAN FIRMS. To test the effectiveness of Damodaran s regression approach for lambda estimation, we regressed the stock returns of the companies listed on Ibovespa against C-Bond returns (the 10-year Brazilian US dollar-denominated sovereign bond). The companies used in the analysis and the results are reported in Appendix A. The results of the regression analysis indicate very low R-squared values and high p-values. The value of each slope was meaningless and, consequently, cannot be used as a proxy of the companies exposure to country risk. This result could be mainly due to problems regarding the use of a fixed-maturity bond, the 10-year one. In fact, the benchmark of the tenor on the curve usually changes from one year to another, but the analysis needs to be implemented with data that span many years to have a sufficient number of data points for the linear regression to be sensible. The prices of different bonds, with different characteristics, comprise a time series that represents the price of the 10-year-maturity sovereign bond at different times. The time series is thus composed at each time by the bond that has a ten-year maturity at that time; then, one year after, for example, when that bond has a maturity of nine years, another bond with a 10- year maturity becomes the benchmark of the tenor. Hence, the value of the lambda obtained with the regression approach using a ten-year curve composed of multiple bonds will certainly be skewed. We encountered this problem using the C-bond: over the period of , two different bonds were part of the ten-year curve: EC Corp until November 2013 and EJ Corp afterwards. When the benchmark changed, the price of the curve 9

12 also changed (from to 94.75), thus making the value of the obtained lambda unreliable even if the statistics of the regression did not turn out to be meaningless. Moreover, for many periods, the 10-year benchmark does not even exist, as can be observed from Figure 1. C-Bond Weekly Closing Prices Dates Figure 1. C-BOND historical price from May 1998 until January We therefore decided to perform the analysis with other sovereign US dollar-denominated bonds issued by the Brazilian government with different maturities (2021, 2024, 2025 and 2041) to check whether we would have obtained a better result. The companies and bonds used for this analysis are listed in Appendix A. The results of the regression analysis were again unacceptable in terms of the p-value for the majority of the times and, even when they were acceptable, the R-squared value was close to zero. These negative results may be related to the different characteristics and liquidity of bonds with different maturities. As countries become less risky over time, as Brazil did over the last decade, the country bonds may no longer carry the risk connotations that they used to carry. Therefore, the lambda obtained using returns on a government bond that will mature in 2040 is linked to investors expectations and beliefs that are completely different from the ones that investors have for a sovereign bond that will mature in Moreover, the price of a bond moves closer to its face value as it approaches its maturity date, making the choice difficult. Finally, we regressed the companies stock returns against the returns on the sovereign CDS spread, implementing the approach proposed by Damodaran (2009b). The uncertainty regarding the choice of the CDS was again related to the maturity: in the market, sovereign CDSs with several different maturities are traded, and their returns are highly correlated, as shown in Figure 2. 10

13 CBRZ1U1.CBIL.Curncy CBRZ1U2.CBIL.Curncy CBRZ1U3.CBIL.Curncy CBRZ1U5.CBIL.Curncy CBRZ1U7.CBIL.Curncy CBRZ1U10.CBIL.Curncy 1 CBRZ1U1.CBIL.Curncy CBRZ1U2.CBIL.Curncy CBRZ1U3.CBIL.Curncy CBRZ1U5.CBIL.Curncy CBRZ1U7.CBIL.Curncy CBRZ1U10.CBIL.Curncy Figure 2. Brazilian sovereign CDS spread return correlation, with maturity from 1 (CBRZ1U1) to 10 years (CBRZ1U10), over the period We performed an analysis to check whether there was a significant relationship between the returns on the Brazilian CDS spread and the returns on the Ibovespa companies stock price, but the results were again unacceptable. A significant value was obtained only when we performed the analysis against the Bovespa Index, which is the main indicator of the average performance of the Brazilian stock market. The R-squared value was on average near 20%, and the p-value was approximately zero, but lambda had a negative value. The negative slope obtained reflects the fact that as the returns on the Brazilian CDS spread increase, the returns on the Bovespa Index usually decrease. When investors perception of the country risk increases, the average return for the whole market decreases. Moreover, a negative slope cannot be used as a measure of lambda because it would mean decreasing the cost of equity instead of augmenting it because of the additional risks that affect an emerging country. Moreover, as clearly shown in Figure 3, the sovereign CDS spread is highly volatile and thus should not be used to estimate lambda. 11

14 Daily 5 and 10 Years Brazil CDS Spread Mid Price (in basis points) Y CDS 5Y CDS 11/1/04 10/31/08 10/31/12 10/31/14 Dates Figure 3. Plot of daily prices of the five- and ten-year maturity Brazilian CDS spreads. We believe that Damodaran s regression approach does not work because the majority of investors do not consider historical prices for government bonds in the market, what they normally consider is the yield. The reason for this difference is that benchmark bonds issued at different times have different characteristics, such as the terms of maturity and coupon. Because of the differences in these characteristics, a bond may be priced very differently between two benchmarks for the same tenor. For instance, if a 20-year-maturity bond issued 10 years ago that bears a coupon of 7.5% is now rolled up to become the current 10-year benchmark bond because of its reduced maturity, the bond still pays the same 7.5% coupon. This coupon may be very different from the coupon of a 10-year benchmark bond issued today, which may have, for example, only a 5% coupon. Differences such as these will have an impact on the price of the bonds; therefore, a comparison between them is not meaningful. 4. NEW APPROACHES TO MEASURE A COMPANY S EXPOSURE TO COUNTRY RISK. The impossibility of determining a reliable measure of a company s exposure to country risk using existing approaches inspired us to develop the following new measures: The Prospective Lambda The Relative LambdaThe Retrospective Lambda 12

15 The Company Effective Risk Premium The Actual Lambda The Company Actual Risk Premium The Industry Lambda All of these new measures of a company s exposure to country risk are indirectly implemented from the implied equity risk premium approach (Lee, Ng, and Swaminathan (2005) and Damodaran (2009a)). Given the value of the S&P 500 Index today, the expected growth rate of dividends for next year and the stable growth rate, the implied cost of equity is calculated by substituting the values of the given variables and solving for Ke in the following formula: Index price today = #$% %%% $ % & (4.1) where Ke is the required return on equity, that is, the mature-market equity risk premium, and g is the expected growth rate. The Prospective Lambda We called the first of the seven new approaches the Prospective Lambda because it is based on future expected growth rates. The formula is a variant of the implied equity risk premium formula and can be implemented for each company. Lambda is estimated breaking the cost of equity down into the sum of the risk-free rate, the product of beta and the mature market equity risk premium (ERP), and the portion of country risk premium that affects the company. The last is the product of lambda and the country risk premium (CRP), where lambda is the only unknown parameter. Company $ Market Cap t =,%% - #$%,%% / -01 & (4.2) So, Ke g =,%% - #$%,%% / t (4.2.a) Breaking the cost of equity down, rf +Beta ERP +λ CRP g =,%% - #$%,%% / t (4.2.b) Assuming that the company grows at the risk-free rate, λ CRP = Beta ERP +,%% - #$%,%% / t (4.2.c) Thus, 13

16 λ = [ Beta ERP +,%% - #$%,%% / -01 ] C CRP (4.2.d) t where Betat is the company Beta at time t; ERPt is the mature market equity risk premium calculated at t; rft is the risk-free rate at time t, which is assumed to be equal to the company s stable growth rate, and Market Cap is the Market Capitalization of the company. This approach can be generalized to allow for a first period of high growth, in case the company is not in the stable-growth period already, but the assumption that the risk-free rate is equal to the stable-growth rate would not be valid anymore and every parameter would need to be estimated for both the stable- and the high-growth periods. Analyst estimates could be used to estimate the expected growth rate of dividends or free cash flows for the highgrowth period, but the bias would be significant because we are not considering maturemarket firms. The Relative Lambda The Relative Lambda is based on the same assumptions and formula of the Prospective Lambda, with the difference that the price used in formula 4.2 is obtained by implementing a relative valuation: λ = [ Beta ERP +,%% - #$%,%% / -01 ] C CRP DE E (4.3) t This approach should be preferred to the previous one when the relative valuation price reflects a fair estimate and the company is currently considered under- or overvalued relative to comparables. The Retrospective Lambda As previously asserted, the Prospective and Relative Lambdas, like the implied equity risk premium, rely on future growth estimates. To avoid this uncertainty and bias, we propose a new measure, which we call the Retrospective Lambda. The Retrospective Lambda is an ex-post measure of the effective exposure to country risk over the past year. In fact, it relies only on past data for estimation of lambda: λ = [ Beta ERP + FEG%,%% -01 ] C CRP (4.4) t Or, if a free cash flow-to-equity model is implemented, λ = [ Beta ERP + FEG% H6H# -01 ] C CRP (4.5) t λt indicates the portion of country risk that has been attributed to companyx at time t, considering the effective growth in dividends or FCFE from time t to time t+1. 14

17 Because the model is suitable for stable-growth firms only, we suggest normalizing the dividends and free cash flows to equity to yield a measure that is not skewed by the economic cycle and the company performance of the past year alone. The Company Effective Risk Premium The idea behind the Company Effective Risk Premium is simple. Although the Retrospective Lambda approach would lead to a correct estimate of lambda, there will always be uncertainty about whether the model for the country risk premium is correct. Therefore, we decided to no longer substitute the value of the country risk in equations 4.4 and 4.5 but rather to directly obtain the product of the two of them. The product indicates the rate of return effectively requested by investors over the past year to invest in that specific company. Company Effective Risk Premium = [ Beta ERP + FEG%,%% t ] (4.6) Or, if a free cash flow to equity model is used, Company Effective Risk Premium = [ Beta ERP + FEG% H6H# t ] (4.7) The Company Effective Risk Premium can be used also for mature-market companies that operate in emerging markets and are thus exposed to a portion of country risk of each of the risky countries where they operate. All of these portions of risk get summarized into just one premium that must be added to the cost of equity to correctly estimate the adjusted discount rate: the company effective risk premium. The Actual Lambda When a company is in the stable growth phase, the cost of equity at time t should be equal to the cost of equity at time t+1. Hence, instead of computing the retrospective lambda (at time t using only the dividends of FCFE at time t+1), we can derive the lambda at time t+1 by solving formula 4.4 and 4.5 for the cost of equity at time t+1. λ LM = [ Beta LM ERP LM + FEG%,%% -01 ] C CRP LM (4.8) t Or, if a free cash flow-to-equity model is implemented, λ LM = [ Beta LM ERP LM + FEG% H6H# -01 ] C CRP LM (4.9) t The valuation is thus computed at time t+1 and the only input at time t is the company market capitalization. 15

18 The Company Actual Risk Premium As is the case of the Company Effective Risk Premium, to avoid the uncertainty related to the model of the country risk premium chosen, we can no longer substitute the value of the country risk in equations 4.8 and 4.9 and directly obtain the product of the two of them. The product indicates the actual rate of return requested by investors to invest in that specific company. Company Actual Risk Premium LM = [ Beta LM ERP LM + FEG%,%% t ] (4.10) Or, if a free cash flow to equity model is used, Company Actual Risk Premium LM = [ Beta LM ERP LM + FEG% H6H# t ] (4.11) Also the Company Actual Risk Premium can be used also for mature-market companies that have operations and/or production facilities in emerging markets and are thus exposed to a portion of country risk of each of the risky countries where they operate. All of these portions of risk get summarized into just one premium that must be added to the cost of equity in order to correctly estimate the discount rate. The Industry Lambda The Industry Lambda reflects the Lambda of the Industry in which the company belongs. It is a generalization of the models previously proposed: instead of using the company-specific values, the median value of the peers incorporated in the same country and belonging to the same industry of the firm is used. Hence, the company price, its beta and the dividends or FCFE, depending on the chosen valuation model, are substituted to obtain an estimate of the exposure to country risk of the industry in which the company belongs. The Industry Lambda can be implemented with the Retrospective, the Prospective and the Actual method. Industry Effective Risk Premium and Industry Actual Risk Premium can be computed as well by not substituting for the value of the country risk premium in the formula. We suggest using this approach to calculate the portion of country risk to be added to the cost of equity used to discount the terminal value for companies that are not in the stable-growth phase or not listed, and using peers in the stable-growth phase. Implications and suggestions for valuation in Emerging Markets. A revised CAPM for Emerging Markets companies The assumptions that underlie the Retrospective Lambda, the Company Effective Risk Premium, the Actual Lambda and the Company Actual Risk Premium are that the stable growth rate g is equal to the risk-free rate, and that the firm is in the stable-growth phase. The choice among the Actual and the Retrospective Lambda is critical: we suggest using the Actual Lambda only when the cost of equity at time t+1 is believed to reflect the cost of equity that the company will have in the future. The Industry Lambda is suitable for firms that are in the high-growth phase, or that are not listed, and can be used to estimate the lambda for discounting the terminal value. The Industry Lambda can be computed with the Prospective, the Retrospective and the Actual method. 16

19 Furthermore, in some cases, it is possible for lambda to have a negative value, for instance when the company Beta is high and/or the company dividends or FCFE are too low. In these cases the company is not in stable growth and we suggest to implement one of the three methods that allow for a first period of high growth. The Prospective and Relative Lambdas can be generalized to allow for a first period of high growth, and in this case the former assumption does not hold. We suggest calculating lambda for various weeks and taking the average value among all of the weeks of the time period chosen, one year for instance. If this value turns out to be negative (or too high to be feasible), we suggest using Damodaran s revenues approach, even though only a few observations per year would be available. For the Company Effective/Actual/Industry Risk Premium, we suggest to use an average of the past years, for instance, five, if the past year only is not believed to reflect the company exposure to country risk because the company is cyclical, or the economic scenario was unfavorable. Using the Retrospective Lambda, the cost of equity for a specific company can now be computed as: K = r + Beta PERP Q+{[ Beta ERP + FEG% H6H# -01 ] CCRP } CRP (4.12) t In the revised CAPM proposed in equation 4.12, lambda can be estimated with all the methods presented in this paragraph. 5. TESTING THE RETROSPECTIVE LAMBDA, THE COMPANY EFFECTIVE RISK PREMIUM, THE ACTUAL LAMBDA AND THE COMPANY ACTUAL RISK PREMIUM USING LATIN AMERICAN COMPANIES. To check the reliability of the models proposed in the previous section, we calculated the Retrospective Lambda, the Company Effective Risk Premium, the Actual Lambda and the Company Actual Risk Premium for 58 companies listed on the Bovespa, Ipsa, Colcap, Mexbol, and Igbvl Index. Preferred stocks and units were excluded because of the infeasibility of the approach when not considering common stocks. We also decided to exclude banks and insurance companies because of the impossibility of having a reliable estimate of the free cash flows of the firms in these industries. Companies reporting negative FCFE were excluded from the analysis as well 3. For the purpose of our analysis, we calculated the Retrospective Lambda, the Company Effective Risk Premium, the Actual Lambda Lambda and the Company Actual Risk Premium using a free cash flow-to-equity model in which the normalized free cash flows to equity of the year t+1 were replaced with the trailing 12-months free cash flows to equity of the year t+1. 3 Because of the assumptions related to stable growth of our models. 17

20 Hence, for the calculation of the Retrospective Lambda, λ = [ Beta ERP + TE MU H6H# -01 ] C CRP EG (5.1) - for the calculation of the Company Effective Risk Premium, TE MU H6H# -01 Company Effective Risk Premium = [ Beta ERP + ] (5.2) 6 7 Market Capitalization - for the calculation of the Actual Lambda, λ LM = [ Beta LM ERP LM + TE MU H6H# -01 ] C CRP EG LM (5.3) - and for the calculation of the Company Actual Risk Premium, TE MU H6H# -01 Company Actual Risk Premium LM = [ Beta LM ERP LM + ] (5.4) 6 7 Market Capitalization - where, Betat is the company beta, which is calculated as the ratio of the covariance between the Index returns and the company stock returns to the variance of the Index returns. Two years of weekly returns were used for the calculation of both the numerator and the denominator. Each beta was adjusted in the same manner as Bloomberg beta is adjusted, that is, by multiplying beta by 0.67 and adding We decided to adjust the betas because the values previously calculated were very low and stable-growth companies betas tend to be close to one. ERPt is the mature-market equity risk premium 4. For each week, we used the value of the mature market equity risk premium that referred to the month of the week in which we estimated lambda. CRPt is the country risk premium. For the purpose of the analysis, we used Damodaran s melded approach because in our opinion, it yields a more reasonable estimate of the country risk by accounting for both the sovereign bond spread with the mature market and the ratio of the emerging country s equity and bond standard deviations: Country Risk Premium = Default spread X #Y X 6 Z% (5.3) The default spread was calculated as the difference between the yield of the 10 years country bond denominated in US dollars and the US 10 years T.bond yield. The standard deviation of the previous two years of the emerging country equity index returns was used as the country equity standard deviation. For the country bond standard deviation, we used the two years past returns of the bond with 10 years maturity or, if unavailable, with maturity as close as possible to 10 years. 4 We used the value calculated by Damodaran each month. 18

21 Trailing 12m FCFEt+1 are the trailing twelve months free cash flows to equity, which were obtained from Bloomberg Professional Database and used instead of the free cash flows to equity of year t+1 in the numerator of formula 4.5, 4.7, 4.9 and For each week, the value of the FCFEt+1 that referred to one year later, i.e., fifty-two weeks after the week of interest, was used. The company stock price was obtained from Bloomberg Professional Database. Each lambda was calculated for every week of 2013; the values obtained are reported in the table below and represent the averages of the values for the fifty-two weeks of The following table presents the Retrospective Lambda, the Company Effective Risk Premium, the Actual Lambda and the Company Actual Risk Premium of the companies of the five Latin American emerging markets. Country Risk Premium 2013 Retrospective Lambda Company Effective Risk Premium Country Risk Premium 2014 Actual Lambda Company Actual Risk Premium Average Brazil 4.53% % 4.57% % Average Chile 2.21% % 1.23% % Average Colombia 1.89% % 1.59% % Average Mexico 2.84% % 1.82% % Average Peru 3.59% % 2.70% % Table 3. Average Country Risk Premium, Retrospective Lambda, Company Effective Risk Premium, Actual Lambda and Company Actual Risk Premium of the Latin America Emerging Markets. The results for each of the 58 companies used for the analysis are reported in table 4. 19