Capital Asset Pricing Model for Investment in Emerging Countries
In the financial world, the term “expected returns” is mainly used in reference to the rate of returns that an investor should acquire from certain investments made given their risk profiles. The relative return philosophy is mainly based upon these theories: Eugene Fama’s Efficient Marketing Hypothesis (EMH), Harry Markowitz’s Modern Portfolio Theory (MPT) and finally William Sharpe’s Capital Asset Pricing Model (CAPM) (Pereiro, 2010). The Capital Asset Pricing Model (CAPM) largely provides a framework for the construction of portfolios with and optimal risk-rewarding relationship. Investment opportunities place a significant impact on a firm’s value placing the need for the management find a method that enables them to make investment decisions that are appropriate with a focus on value maximization given the fragmented shareholders base (Pereiro, 2010). Investment analysts are often faced with both practical and conceptual challenges while applying traditional valuation methods that have been conceived for the developed markets (DMs) to the peculiar economic context for emerging markets (Ems) (Pereiro, 2010). This paper, therefore, shall explore the applicability of CAPM in emerging markets with a primary focus on the stock market on industry betas.
The backwardness of information infrastructure raises further challenges when applying CAPM in emerging markets. According to Pereiro (2010), statistical evidence has been found to provide a significant difference between the median of emerging markets and the U.S. derived industry betas which confirms that there is a need to tailor traditional valuation models to the irregular economic context of emerging markets (Pereiro, 2010). To provide a way that can easily make the information available on the DMs to the peculiar economic context of EMs adaptable, there is a need to identify the linkage between cross-country differences in industry betas (Pereiro, 2010).
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CAPM and Enterprise Evaluation in Emerging Markets
There are both practical and theoretical challenges that are usually faced by analysts when they are evaluating the value of an enterprise in emerging markets due to the peculiarities found in their economic contexts (Faboozi, 2006). For the valuation techniques that are largely based on DCF (Discounted Cash Flows), the additional risk provided for in EMs must be accounted for in the estimation of both the opportunity cost of capital as well as the cash flows (Faboozi, 2006). Factors such as poor governance mechanisms, inefficient information infrastructure, and widespread corruption are some of the factors that differentiate emerging and developed markets. According to Teti et al. (2012), the financial assets that are found in Ems are usually priced at discounted rates because of the highest levels of corruption and weak corporate governance of the environment that firms operate in. The discounted prices for financial securities are also negatively affected by the level of competition on product markets, the degree of diffusion of the press as well as the rate of tax compliance (Teti, 2012). Thus, the barriers to investments from a macroeconomic point of view in emerging markets is mainly represented by the poor quality of accounting and regulatory frameworks, poor credit ratings, governmental control over exchange rates and high inflation. (Teti, 2012)
The meaningfulness of an evaluation process is highly dependent on the availability of efficient communication infrastructure and the quality of information as they play a vital role in the applicability enterprise valuation techniques in emerging markets (Faboozi, 2006). Corporate management, therefore, should be used as the primary source of information for the market about the securities and assets of a firm (Faboozi, 2006). Therefore, the regulatory bodies and legal mechanisms affecting the timeliness and quality of the management’s reporting mechanisms play a vital role in lowering transparent environments in emerging markets (Faboozi, 2006).
The peculiar characteristics that are experienced in the economic contexts in emerging markets have made some researchers try to provide alternative models to the CAPM, while others have placed their focus on adapting the traditional valuation techniques to the characteristics found in emerging markets (Faboozi, 2006). Research has found out that the variables that affect risk and return measures in developed markets are also experienced in emerging markets, and these variables include company size, momentum, and market-to-book value (Kewalramani, 2008). Country-specific sources of economic risk, political and financial are also relevant in emerging markets and are strongly associated with equity returns which means that country-specific risks are of traditional importance to international diversification purposes (Kewalramani, 2008).
Although emerging markets are riskier than developed markets, finding a measure of risk that reasonably clarifies expected returns has proved to be a challenge to both practitioners and academics (Kewalramani, 2008). Research has however shown that emerging markets fail to substantiate the expected returns (50minutes.com, 2015). There are few emerging market betas that have shown betas that are higher than 1 which are calculated against the world stock market which does not support the idea that emerging markets are riskier when compared to developed markets instead they support the notion that emerging markets are a bit integrated with global capital markets (50minutes.com, 2015). According to Estrada (2001), many country betas have significantly increased for emerging markets, but their relation to the expected returns is still weak. Due to little transparency and the lack of data in emerging markets, researchers have been forced to look for alternative ways to find measures or risk that are closely related with the expected returns since the available local betas have failed in capturing the risks of emerging markets (Estrada, 2001). Practical and theoretical approaches to CAPM have been proposed, but the backwardness of Ems in terms of governance mechanisms as well as information infrastructure poses a great challenge to the applicability of CAPM (Estrada, 2001). The main barrier to the adoption of CAPM is the lack of integration in capital markets as it magnifies country-specific challenges and risks (Estrada, 2001).
For CAPM to be efficiently applicable, it would require a perfectly single capital market that reflects the risks associated with human economic activities (Estrada, 2001). International diversification has proved to be of great importance as its benefits significantly outweigh the costs in terms of regulatory, cultural and higher trading costs differences. Industry factors only appear to only prevail in developed markets while country related differences remain to be of importance between developed and emerging markets (Estrada, 2001). Cross-country diversification in developed markets is believed to yield more benefits that cross-country diversification in emerging markers taking into consideration that the industrial composition of stocks indexes is also relevant (Hammour, 2014). Investors are therefore supposed to take into account the first set of countries that are represented in their portfolios and then make a decision on the weight that they should give each industry (Hammour, 2014).
Industry betas have been found to be different between emerging and developed capital markets. For risks associated with international diversification purposes, country-specific factors play a great role in emerging markets which means that country-specific factors many at times carry more information when compared to industry-specific factors (Hammour, 2014). To adopt CAPM in emerging markets analysts and investors need to pay close attention to country-related than industry related factors (Hammour, 2014). Differences in the industrial composition of stock markets are of relevance as changes in the industry weights are violent and frequent in emerging markets and many at times they affect the volatility of returns (Hammour, 2014). If analysts are to find that the differences in industry weights are found to explain the differences in cross-country betas, then in their analysis they will be forced to only consider cross-country differences in the industrial composition in their application of CAPM from one country to another.
References
Estrada, J. (2001). The Cost of Equity in Emerging Markets: A Downside Risk Approach, Emerging Markets Quarterly , 63-72
Faboozi, J. (2006). Financial Modeling of the Equity Market: From CAPM to Cointegration . New Jersey: Wiley & Sons.
Hammour, K. (2014). T he Efficiency of CAPM and APT Models in Predicting Expected Returns . Saarbrucken: LAP LAMBERT Academic Publishing.
Kewalramani, E. (2008, December 3). Application of CAPM Model to Emerging Economies . Emerging Economies. Retrieved from http://capm-emergingeconomies.blogspot.co.ke/ .
Pereiro, L.E. (2010). “The Beta Dilemma in Emerging Markets. The Journal of Applied Corporate Finance , 22(4): 110-122.
Teti E., Dell’Acqua, A. and Zocchi, F. (2012). UN PRI and private equity returns. Empirical evidence from the US market, Investment Management and Financial Innovations , Vol. 3, pp. 60-67.
50Minutes.com. (2015). Capital Asset Pricing Model: Make smart investment decisions to build a strong portfolio . New York: 50Minutes.com.
