ERP Comparison of Developed and Emerging Markets

Chapter 1: Introduction

1.1 Research Topic

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The investment dilemma hits when individuals earn more than their consumption needs. Considering the fast rising inflation globally, saving the surplus earnings for future consumption is not sufficient anymore. Hence, making an investment such that the surplus earnings grow or even multiply over time is almost imperative. Such an investment can be made in many ways for instance commodities, stocks, bonds, pension funds, real estate etc. This study is concerned with individuals’ investment in stocks.

When an individual invests, he/she expects a certain rate of return in the future from the investment which should ideally compensate future consumption needs, future increase in inflation and uncertainty of return if any. Therefore, investments with higher returns are preferred. A number of studies find evidence of stocks giving higher return than government bonds, although the relative uncertainty of return from stocks being much higher than from bonds (Dimson et al, 2002; Ibbotson & Senquefield, 1976). Consequently, the more uncertain the future return gets, the riskier it is to invest. Hence, when an individual invests in stocks, he/she expects added compensation for added risk which leads to the concept of Equity Risk Premium (ERP). ERP is the surplus return from stocks/equities over the return from nearly risk-free (here on mentioned as risk-free) asset such as government bonds.It is the premium that individuals demand for bearing the additional risk in equity investments (Reilly & Brown, 1999).

ERP is calculated using equation-1. Stock returns can be the returns from a benchmark index (market returns) such as FTSE 100 and the returns from risk-free asset (risk-free returns) can be those from UK gilts.

(Reilly & Brown, 1999)

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ERP is an important consideration from an investor’s point of view for building and analysing a domestic equity portfolio or an entire equity market especially for an investor looking to diversify globally (here on mentioned as global investor). Therefore, it is a widely researched topic, however yet the existing literature is inadequate, considering there are numerous debates and puzzles pertaining to various aspects of ERP. Hence, looking at its significance in theoretical & practical finance, ERP is chosen as the central topic to be researched in this study.

1.2 Research Background

Individuals (retail investors) use ERP to forecast the expected growth of their equity portfolios over long-term and for portfolio allocation decisions. Corporations (here on mentioned as organisations) need ERP as an input to determine the cost of equity i.e. the annual expected rate of return from investment in stocks and for capital budgeting decisions. Overall, ERP is a significant factor in most risk-return models of corporate finance and investment management. Hence, estimating future ERP and identifying possible reasons for the results found, is an important financial and economic research topic for academia and practitioners alike. Although historical data is most popularly used to estimate future ERP, there exist financial, economic & asset pricing models developed over the years which predict an implied ERP based on companies’, macroeconomic & equity market data. Evidence from the relevant literature suggests that every ERP estimation method has a distinct set of assumptions and underlying ideas therefore exuding both merits and demerits when compared to another estimation method.

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Rapid economic growth of emerging countries has been apparent especially because of industrialisation. Consequently the performance of emerging equity markets has been remarkable in the past decade. The big 4 i.e. Brazil, Russia, India & China (BRIC) alone, accounted for more than 50% of the world GDP in 2006 (RICS, 2008). Due to saturation in developed countries and growing avenues for investment in those emerging, the ERP of emerging markets has risen due to growing investor confidence. Although perceived social, economic & political risks are equally high, financial systems have strengthened and macro-economic conditions have improved drastically for most emerging countries. Barry et al (1997) argues that investing in emerging markets is more than just profitable, considering the risk-return trade-off. Hence, gauging the future of emerging equity markets has become a vital research topic for economists, finance professionals and global investors alike.

In a discussion of emerging markets, India cannot be left out. Post liberalisation (i.e. post 1991) India is definitely the secondmost preferred emerging economy by global investors after China. Although Foreign Direct Investment (FDI) flows have been average compared to other emerging countries, Foreign Institutional Investment (FII) flows increased almost 10 times, from United States Dollar (USD) 739million in 2002 to a record USD 7.59billion in 2003. CALPERS, the world’s biggest pension fund with a base of USD 165billion has recently included India in their list of countries for investment (BSE India, 2008). The noteworthy rise to the position of the sixth largest emerging equity market with a total market capitalisation of USD 818billion and 8% p.a. average economic growth (CIA Fact-book, 2008) over past decade accentuates the importance of India’s ERP estimation and analysis.

1.3 Research Gap, Objective & Questions

Most of the research on ERP has focussed on developed markets clearly because of their sound history and stable fundamentals. Within limited research conducted on ERP in emerging markets, Salomons & Grootveld (2003) demonstrate the evident differences in ERPs of developed and emerging markets and claim that global business cycle influences these differences. Claessens (1995) argues through his empirical research that investment in emerging markets can be fruitful in long-term considering that high ERP compensates for high risk. Although these and similar related researches vaguely guide investors wanting to explore emerging markets, there lacks a clear evidence of the possible risks attached and whether those risks can be tackled to earn complete benefit of the high ERP. Bernartzi & Thaler (1995) and Campbell & Cochrane (1999) claim that the reason for increase in investors’ interest in U.S. markets was the high ERP it offered. Hence if the same rule is applied to emerging markets then investments should be made without any prior estimation of possible risks, especially considering the success of U.S. markets. However it is not the case, as investors are still sceptical about getting confirmed high returns from emerging markets. Therefore, the precise reasons for the difference in ERPs of developed and emerging markets have not been clearly identified as yet, hence constituting the first research gap.

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There exists considerable evidence on how political, social and especially macroeconomic factors affect the equity market returns of developed countries, especially U.S. (Chen et al, 1986). Considering the limited work done on ERP of emerging markets on the whole, negligible contribution has been made to analysing ERP in India with respect to its growing economy, Mehra (2006) being the most notable, hence constituting the second research gap.

Considering the importance of ERP it is interesting to note that in-spite of there being many ways to calculate ERP; there exists no consensus on the best approach. Financial market analysis is performed based on historical data and the ERP measured from past performance of equity markets is most commonly used as an estimate of future ERP. For instance Ibbotson & Sinquefield (1976) exemplified first accurate calculations of annual rate of return on equity investments in U.S. and ERP. Since then, Siegel (1992) & Dimson et al (2002) are two of the most notable researches on ERP estimations using the historical method. However, there exist models developed for instance by Fama & French (2002) and Arnott & Bernstein (2002) that determine future ERP entirely based on forward-looking information through estimation of future investors’ & markets’ expectations. This variation of approaches to ERP estimation has only widened the range of results and complicated the unresolved debate, hence constituting the third research gap.

The 3 research gaps identified above lead to the overall Research Objective of this study, which is:

Comparative analysis of ERP in the leading developed & emerging markets; determine the macroeconomic influence on ERP and examine the ERP estimation methods; all from a global investor’s point of view.

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It is not realistically possible to fill the research gaps entirely through this study considering time, knowledge and relevant experience constraints. However, this study aims to fulfil the above objective through the accomplishment of satisfying solutions to the following 3 Research Questions:

1. After estimating future ex-post ERP in the chosen sample index of developed and emerging markets, what is the impact of risk responsible for the differences found through the comparison of their risk-return trade-off?
2. What effect do the country specific macroeconomic factors have on the ERP in India, if any?
3. After estimating future ex-ante ERP in India using a supply-side method and comparing it with the estimated ex-post ERP, what is the most suitable method for global investors, if at all, and why?

Research Contribution

As this study is predominantly aimed at analysing the ERP of leading emerging markets and particularly India, it is hoped that this study contributes to simplify the decision making of global investors regarding their equity investments in emerging markets & India. Furthermore, it is hoped that this study provides guidance to the global investors regarding the macroeconomic situation in India and its influence on the ERP, for sound portfolio management. Moreover, it is hoped that this study adds a small brick to the large edifice of ERP analysis/measurement/estimation on the whole. Finally, if this study motivates the eminent researchers and consequently triggers some ground breaking academic scholarship regarding the ERP of emerging markets, then the worthiness of this study will be truly identified.

1.4 Research Structure

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The following is the chronology and brief content of the chapters in this study here on:

Chapter 2: Literature Review: This chapter aims to explain the historical development of ERP through empirical researches and relevant theoretical background. Furthermore, it examines important research literature on ERP estimation methods and emerging equity markets.

Chapter 3: Overview of Research Methodology: This chapter aims to briefly explain the chosen research methodology for this study and justify its appropriateness. It also describes the chosen data collection method and clarifies how the data will be collected & used for achieving the research objective.

Chapter 4: Data Analysis, Findings & Interpretative Analysis: This chapter aims to identify the collected data, explain the data analysis technique/model/method in detail, analyse the data that is collected by using the chosen methods & models; and finally, interpret, examine & evaluate the results/findings from the analysis to identify justifiable solutions to the research questions. The chapter is divided into 3 parts, each part pertaining to each research question and the procedure is conducted separately for each.

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Chapter 5: Discussion & Conclusion: This chapter aims to summarise the results from chapter 4, recapitulate the entire paper and testifies the level of fulfilment of the research objective. Also, it plausibly links the past literature & results from this study to check the level of accomplishment in filling the research gap and to identify the need for future study.

Chapter 2: Literature Review

2.1 Chapter Introduction

ERP is a vital numerical figure in practical modern finance as it is considered by financial analysts, business managers and economists for the purpose of decision-making; perhaps best testified by Welch (2000, p.501) wherein he calls ERP “the single most important number in financial economics…”. Consequently, it is and has been one of the most fascinating topics for academic scholarship leading to vast amount of literature.

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This Chapter discusses the various significant perspectives about ERP generated from the literature. The literature reviewed in this chapter is primarily related to the research questions that this paper aims to answer; having said that, other theoretical developments and empirical researches in the field of portfolio management and corporate finance that are significantly relevant to the research topic, are also discussed. Broadly speaking, the content matter in this chapter is organised in chronological order beginning from the earliest.

Here on this chapter is divided into 5 sections. The historical advancements in productive assessment of the relationship between equity risk and return resulting from empirical researches which lead to the conceptualisation of ERP is discussed in section-2. The next section-3 highlights the important theoretical developments which laid the foundation for the large edifice of researches on investment management. Section-4 focuses on the models/methods that were formulated based on the theories, with an aim to calculate expected returns and measure & estimate ERP. It also looks at the important contemporary researches in the field of ERP with a brief backdrop of macroeconomic factors. The following section-5 highlights the important literature with respect to the ‘ERP Puzzle’. It discusses the significant attempts by researchers to solve the puzzle. The next section-6 follows which briefly looks at the important literature on emerging equity markets overall. Finally, section-7 summarises the entire discussion.

2.2 Historical Conceptualisation of ERP

The apt risk-return trade-off sought by investors worldwide augmented the importance of ERP evaluation and forecasting. Consequently, vast theoretical & empirical research under various objectives has been conducted till date since the early 20thcentury on measuring, estimating and analysing ERP, most of which has concentrated on the developed markets, especially U.S. Furthermore, eminent financial economists have been engaged in empirical analysis of past investment results to gauge future investment strategies.

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In the late 19th and early 20thcenturies, most economists did not endorse the importance of risk in evaluating and justifying excess returns. The conception of the fact that incremental profit on equity investments is a result of the higher risk attached, was a gradual process. For instance, Clark (1892), professor at university of Columbia, claims that investments in some organisations give higher returns than risk-free rate & some other organisations because those organisations have an advantage of monopoly in the market. Furthermore, modernisation and development in technology lead to comparatively higher competitive advantage which in turn gives excess returns.

However, renowned author of the book Risk, Uncertainty and Profit, Knight (1921), does not endorse Clark’s view but instead criticises him for inadequately exploring the association of risk and return in the models used in his economic research. Knight analyses the importance of risk in equity investments through past performance of U.S. markets and aimed at relating it to the concept of profit in the basic economic theory. He argues that any kind of risk deserves a premium (i.e. excess returns), even if the risk is unquantifiable (which he later termed as uncertainty), although, he could not suggest any solid and foolproof way of measuring the premium that he justified.

As a cumulative result, the debate on equity risk and the attached premium flared up which necessitated ground breaking empirical researches based on historical data of past performance. Hence, many scholars developed stock price indices in early 20thcentury in order to measure long-term investment performance and estimate future returns; For instance, Mitchell (1910, 1916), Persons (1916, 1919), Cole & Frickey (1928) in the U.S. and Smith & Horne (1934) and Bowley et al (1931) in the U.K. However, Hautcoeur et al (2005) in their analyses of early stock market indices; argue that the main motive in development of these indices was forgotten in no time and instead they were used to gauge the influence of macroeconomic cycles on equity markets and as an easier way to estimate macroeconomic fluctuations. The popular index of 30 stocks developed by Charles Dow was never aimed at estimating future long-term returns but instead to measure daily returns on the market.

Consequently, the relevance of the returns from risk-free assets like government bonds to comparatively risky equity returns was tested. The difference in their rate & magnitude of returns solidified the so far debated idea of returns being a compensation of the risk attached to the investments made. Smith (1924) advocates through empirical research and later through his book that; equities give higher returns than bonds because they carry higher risk. He collected historical data on stock prices, dividends and corporate bonds from the stock exchanges at Boston and New York spanning 1866-1923. Furthermore, he divided this period into 4 sub-periods to recognise the economic development. After creating separate portfolios for each asset class (10 securities in each portfolio), he measured cash income and capital gains from both. Equity investments give higher appreciation and returns than bonds in the long-term in-spite of economic changes in the sub-periods, was his conclusion. Further in his book, he suggested a mechanical way of calculating ERP by paying out the equivalent amount of bond returns from the total equity returns and re-investing the remaining in the same equity portfolio. In this way, the relative growth rate of the equity portfolio is the ERP over the bond portfolio.

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Smith’s estimation and method of ERP calculation attracted many retail investors towards the equity markets in 1920s. Later, Smith’s attempt to assess equity investment returns over bonds; was improvised by Cowles (1938). He collected historical data on most of the stocks of NYSE instead of only 10 for the period 1872-1937 and notably created the first nearly-accurate index of total returns from common stock investments. Furthermore, he suggested of re-investing the dividend yields into the equity portfolio to save from measuring cash returns and value appreciation separately, the way Smith did. However, he made no concluding remarks such as equity investments can be more profitable than bonds, unlike Smith.

By then, although the idea of an ERP was making financial & economic sense, a solid way of estimating future ERP could not be developed yet; the two main reasons being the unavailability of adequate historical equity market data and the ignorance about the possibility of a forward looking method. However later, John Williams (1938) wrote the first book that defined; modelled and estimated forward looking ERP. Although he estimated future ERP in U.S. using Dividend Discount Model (DDM), he argued that ERP estimates based on Historical Method are equally precise. He believed that the most suitable way to calculate the riskiness of a security is by appending a premium to the risk. Later, he also became the first researcher to numerically estimate a forward looking ERP for U.S. By then, the concept of ERP had been clearly understood and its importance had been recognised.

Nearing late 1940s economists and researchers had realised the importance of risk and conceptualised ERP as an essential ingredient to calculate future returns on equity investments. Moreover, enough historical data of U.S. equity markets was also available for past performance analyses and empirical researches. Even so, there was no method/measure that could quantify future risk and returns for any given portfolio of investments, as most experts and investors believed in calculating risk-return trade-off individually for equities and other securities. However, that did not serve the purpose of optimal risk-return trade-off as far as entire portfolio of investments was concerned, until 1952 when crucial theoretical developments began.

2.3 Theoretical Developments

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This section summarises the important theoretical developments which built models to quantify future risk and returns of equities and related vital researches in portfolio & investment management and corporate finance, with a backdrop of their implications on ERP. The 4 most important theories/models reviewed in this section are Portfolio Theory, Capital Market Theory, Capital Asset Pricing Model and Arbitrage Pricing Theory.

2.3.1 Markowitz’s Portfolio Theory

Harry Markowitz (1952) introduced the Portfolio Theory or now what is called the Modern Portfolio Theory (MPT). It provides a formalised method to diversify the portfolio of all investments (not just equity) with an aim to achieve highest possible returns for lowest possible risk. MPT records expected returns, volatility or risk (standard deviation) for each investment and correlation of one investment to another to create the best combination. Therefore, risk is minimised while maintaining the expected returns, if investments are diversified based on the risk of each individual investment.

However, Markowitz (1952) assumed that investors are naturally risk averse, i.e. they tend to choose the investment with highest returns for a given level of risk and refrain from investing if risk is higher than acceptable/favourable levels. Hence, by applying MPT, investors can choose less risky and highly risky investments at the same time in such a way that cumulative expected returns are unharmed and optimised.

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The risk appetite, although, of each investor differs from the other. Therefore, based on the above assumption, Markowitz (1952) believed that depending on the risk appetite, every investor aims at attaining highest possible returns for the level of risk that he/she is ready to bear. In other words, aims to build an Efficient Portfolio. Consequently, all the portfolios, ranging from high-risk to low-risk, which give optimal returns lie on the Efficient Frontier, as termed by Markowitz.

Although Markowitz’s MPT is still followed by many experts and investors, it also faces criticism on its unreal assumptions.

MPT’s assumption of volatility with figures of standard deviation or variance of an investment as its risk measurement may not always be true, especially for equities. It speaks about only a single period when actually volatility changes over time. Therefore, even if a portfolio is efficient today, it may be not be the same tomorrow. For instance, in an economic crisis or equity market crash, there is a high possibility of correlation of two assets in an efficient portfolio increasing than average. Malkiel & Xu (1997) empirically prove that volatility of stocks increases with an increase in institutional ownership in the organisations. Similarly Campbell (2000) shows results of increased volatility with reduction in number of conglomerates as organisations started to narrow their focus.

Lofthouse (2001) criticises MPT on the fact that it bases its calculation of expected returns, volatility and correlation on past historical figures which is inadequate especially when the aim is to build the most efficient portfolio possible. Furthermore, Bernstein (2002) notes that; MPT assumes that there is a possibility that some investments absolutely do not correlate with any of the other investments which is untrue, as each investment at some point in time correlates with one or the other investment in the portfolio.

Hence, although MPT model enables investors to optimally gauge the future risk to gain highest possible returns, it is based on idealistic, theoretically decorative and practically unreal assumptions.

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2.3.2 Capital Market Theory

After MPT was developed, many researchers worked on the most important missing link in MPT, the inclusion of risk-free asset with zero volatility, zero correlation with risky assets and certain future returns. Tobin (1958) was the first to extend Markowitz’s Portfolio Theory by introducing risk-free asset to the Efficient Portfolio. Later, Sharpe (1964), Lintner (1965) and Mossin (1966) contributed to his idea as they independently worked on similar theories. The final development is known as Capital Market Theory (CMT).

It is important to note that CMT shares 3 assumptions with those made by Markowitz (1952) for MPT, as follows:

• Investors are always risk averse

• Investors’ decisions are solely based on expected returns and their volatility

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• There exist no transaction costs and taxes

However following are the new assumptions that CMT makes as extracted from Lofthouse (2001):

• All the investors have the exact same time-horizon for their investments

• Borrowing and lending at the risk-free rate is not restricted

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• All the investors have the exact same expectations for correlation, risk and returns

CMT states that the volatility for Efficient Portfolios that include risk-free asset; is actually the linear equivalent of volatility (risk) for the portfolios before risk-free asset inclusion. Hence these combined Efficient Portfolios lie on the straight line graph of risk and return, joining the risky and risk-free assets. This way, the optimal combined portfolio i.e. point-M in Figure.2.2, is identified at the tangency point formed by the ray starting from point-F in Figure.2.2 i.e. expected return of risk-free asset and the Efficient Frontier. It is optimal because it gives the highest possible returns for any level of risk. Therefore, it is known as Market Portfolio as it has all risky assets and the ray is known as Capital Market Line (CML). CMT advocates that all the investors should aim to build their portfolios on CML depending on their risk appetite. They could invest in risk-free asset by lending or borrow at risk-free rate to invest in Market Portfolio. Either way their portfolios will earn more returns than other portfolios (blue spots in Figure.2.2) on or off the Efficient Frontier, for any given risk (Brealey et al, 2007).

Therefore, under the CMT the expected returns of the equity portfolio are calculated by determining the slope of CML which is the change in return for a given change in risk and intercept which is return of risk-free asset (See Equation-2). The risk is measured by the standard deviation (Lofthouse, 2001).

The development of CMT was ground-breaking in the field of investment management. It clarified the effect of including risk-free asset in an equity portfolio. It formed the first equation made of ERP, risk and returns, all together. In Equation-2, change in return is market return less the risk-free return which is actually the ERP. However, this estimation of ERP is an empirical deduction (calculated from slope of CML), as early development of CMT by Tobin (1958) was just an extension of MPT. Until it was theoretically formalised by Sharpe (1964), Lintner (1965) and Mossin (1966) independently, which then led to the gradual development of the Capital Asset Pricing Model (CAPM). Hence, the CAPM is usually referenced as SLM’s CAPM for Sharpe’s, Lintner’s and Mossin’s equal and vital contributions.

2.3.3 Capital Asset Pricing Model

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The CAPM is undoubtedly the most widely known model to calculate expected returns. It is a sophisticated improvisation of CMT, which in-turn is an extension of MPT and therefore builds on the relationship/trade-off between risk and returns. It is primarily based on the universal classification of risk into 2 broad categories namely:

• Systematic: Risk that affects almost all assets equally

• Unsystematic or Specific: Risk that affects only individual asset or asset class

(Sharpe, 1964)

The CAPM is developed through the conception of Security Market Line (SML) (See Figure.2.3) which is a ray similar to CML originating from the return of risk-free asset. However, the big difference being that SML represents the linear relationship between risk and return from individual assets and/or inefficient portfolios in respect to market portfolio, unlike CML which only represents efficient portfolios. The risk that is measured is only systematic as it is un-diversifiable and hence rewarded, unlike unsystematic risk. The standardised measure of this systematic risk is called Beta which is covariance of an asset or portfolio with market portfolio divided by variance of market portfolio. Market portfolio has Beta equal to 1. Asset with Beta higher than 1, is riskier than market portfolio and hence higher return is expected. Assets with Beta lower than 1, are less risky with lower return. The expected returns are calculated by adding return on risk-free asset to the product of ERP and systematic market risk borne by the stock (See Equation-3) (Sharpe, 1964), (Lofthouse, 2001).

However, the value of Beta for individual stocks of portfolios is not known. It needs to be estimated and is hence subject to errors.

Understanding the mechanics and application of the CAPM is imperative to the study of ERP, as the slope of SML i.e. linear relationship between risk (Beta) and return, equals the difference between market returns and risk-free returns which is ERP. The application of the CAPM is extremely vital in the context of ERP measurement methods as it uses ERP as an input to calculate the expected returns on a stock. The empirical studies and relevant literature related to the CAPM and its applicability in ERP estimation methods are discussed in section 2.4.3.

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2.3.4 Arbitrage Pricing Theory

As seen before, MPT and CMT both assess only the cumulative risk of individual assets and market risk respectively, while calculating expected future returns. Ross (1976) proposed the Arbitrage pricing Theory (APT) based on the perception that the risk of assets and their future returns vary in accordance with the risks affecting the overall economic situation.

Ross believed that unsystematic risks can be curbed/nullified through diversification as suggested by MPT & CAPM and hence will not affect expected returns. But systematic risks having influence on all assets cannot be diversified and hence can cause fluctuation in the expected returns. Although he did not suggest any particular factors that can trigger the systematic risk, empirical results of Burmeister et al (1997) implied the following 5 factors:

• Inflation

• Business cycle

• Investor confidence

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• Time horizon

• Market timing

APT states that; the sensitivity of assets to the unanticipated instability in the above factors varies due to which one of them can get mispriced therefore creating an arbitrage opportunity. Consequently, by selling the highly-priced asset to buy the low-priced asset, the investor can ensure profit and nearly-perfect pricing of both assets. This arbitrage can be termed as the Risk Premium for that particular factor. However, this profit is expected and not guaranteed unlike usual arbitrage gains. Like MPT and CMT, APT also has some underlying assumptions as follows:

• No transaction costs

• Short selling i.e. selling assets that are not owned, is allowed

• Enough assets to diversify unsystematic risks

(Ross, 1976)

APT has faced many criticisms on its applicability in calcul

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