The Truth about Investing in Emerging Markets?

Transcription

1 The Truth about Investing in Emerging Markets? Authors: Edward Hili, Rukshila Gooneratne, Blaise Laupretre, Wee Ling Phua and Laurent Zarruk This work has been undertaken as part of a student educational project and the material should be viewed in this context. The work does not constitute professional advice and no warranties are made regarding the information presented. The Authors, Judge Business School and its Faculty do not accept any liability for the consequences of any action taken as a result of the work or any recommendations made or inferred. Abstract We seek to evaluate the widely held belief that emerging markets offer superior long-run investment returns due to higher economic growth when compared to developed markets. We find that the correlation between growth in GDP per capita and stock returns is insignificant for both developed and emerging economies. We conclude that emerging markets do not consistently outperform developed markets either on a total return basis or a risk-adjusted basis. However not only do emerging markets provide significant diversification benefits both when added to a portfolio of developed markets assets and to a portfolio of emerging markets ones, but they can also improve returns for investors under certain circumstances; we identify factors and circumstances that are relevant for maximising diversification benefits and enhancing returns. Overview This paper is organised into 4 main sections. The first seeks to address whether superior returns are driven by high GDP growth while the second performs an analysis of emerging market investment performance and shows how performance varies over time and with different microeconomic and macroeconomic factors. The third section provides evidence on how emerging market investments could add value to the investor and the final section distils implications of the various findings for investment strategies. SECTION I: ARE RETURNS DRIVEN BY GDP GROWTH? Emerging markets equities outperformed developed markets by an impressive 10.49% (annualised) from Given the strong performance of emerging markets in the recent decade, emerging markets have grown in importance as an asset class and have attracted substantial investor interest. What is an emerging market? There is no single definition of an emerging market. In practice, index providers, in consultation with users, classify markets. MSCI, for example, uses 3 criteria to classify markets: (i) economic development, (ii) size and liquidity and (iii) market accessibility while S&P considers (i) economic and political factors, (ii) relative market size, (iii) market size and structure, and (iv) investment conditions. Dimson et al. (2010) observed that regardless of the differing criteria, the resultant classifications are often similar. They further find that a cut-off of US$25,000 GDP per capita serves as an effective boundary between developed and emerging markets. 1 Computed using MSCI Emerging Market Total Return Gross Index (USD) and MSCI World Total Return Gross Index (USD) 1

2 The widely held belief is that emerging markets offer superior long-run investment returns because underlying economic growth in emerging markets is higher than that in developed markets. The following section searches for evidence to confirm whether GDP growth drives returns. Does Growth in GDP Per Capita Drive Returns: A Review of the Empirical Evidence Given that GDP could grow as a result of population increase and/or growth in GDP per capita, growth in GDP per capita is considered a more appropriate measure of underlying economic growth as it controls for growth driven purely by population increases. Empirically, the correlation between growth in GDP per capita and stock returns has either been found to be insignificant or negative 2. Several studies confirm this relationship (or the lack thereof). Ritter (2005) found the cross-sectional correlation for the compounded real return on equities and compounded growth rate of real GDP per capita for 16 countries from 1900 to 2002 to be (pvalue = 0.16). Countries included in his study were Belgium, Italy, Germany, France, Spain, Japan, Switzerland, Ireland, Denmark, Netherlands, UK, Canada, US, South Africa, Sweden and Australia. A similar relationship was obtained when Dimson et al. (2010) updated the data to 2009 and expanded the number of countries to 19 (countries added to the 16 above were Finland, Norway and New Zealand). The correlation between real equity returns and long run real growth in GDP per capita was found to be The negative correlation becomes more apparent when one considers the post-1972 period: from 1972 to 2009, countries that have the weakest economic growth in the prior 5 years delivered the strongest stock returns (Dimson et al., 2010). Studies on emerging countries gave similar conclusions. For example, the correlation between stock returns and GDP growth was found to be for 18 emerging markets for the period from 1970 to 1997 (Siegel, 1998 cited in Ritter, 2005). Ritter (2005) found the simple correlation between geometric mean annual real stock returns and arithmetic mean real per capita annual GDP growth to be 0.02 (p value = 0.94) for 13 countries, mainly emerging markets 3, over Other measurements of economic activity similarly do not suggest a direct conclusive relationship between economic growth and stock returns. Although Tsouma (2008) found that industrial production growth was related to future stock returns in 11 out of 19 emerging markets, the effects of industrial productions on returns were mixed. In 3 emerging countries, relationships were found in multiple lags of industrial production growth whereas in the other countries, a single significant coefficient was observed. More importantly, some lags of industrial production growth show a positive relationship while other lags show a negative relationship. The relationships also differ for different countries. In addition, when trying to establish causality, the hypothesis that industrial production growth does not cause stock returns is rejected in only 6 out of 19 emerging markets. 2 It is common for researchers to focus on changes in GDP per capita when analysing long run economic growth (Dimson et al, 2010). However, in a few papers that focused on emerging markets and used overall GDP, correlations between overall GDP and equity returns, have been found to be positive (albeit not overwhelmingly high). Smimou and Karabegovic (2010) found correlation of between overall GDP growth and equity returns over for 10 emerging markets in the Middle East and North Africa plus Turkey while Saldanha (2010) found the average correlation between overall GDP growth rates and equity returns for 8 emerging countries (Taiwan, Mexico, Turkey, India, Indonesia, Brazil, China, Russia) from 1980 to 2009 to be Countries included in the study are Argentina, Chile, Finland, Jordan, Malaysia, Mexico, New Zealand, Philippines, Portugal, South Korea, Taiwan, Thailand and Turkey. 2

3 Hence, generally, industrial production growth was not found to be useful in predicting stock returns. In line with Tsouma (2008), Bilson et al. (1999) found real economic activity (measured using industrial production index or manufacturing production index when the former was unavailable) to be significant in only 2 out of 20 emerging markets while lags of economic activity were found to be insignificant in all countries. Similarly, Fifield et al. (2002) did not find consistent, statistically significant relationships between economic variables and stock returns. They performed regression analyses using global (world industrial production and world inflation) and local (GDP, inflation, money supply and short term interest rates) economic variables to explain stock returns for 13 emerging stock markets 4 over and found that local factors were relevant in explaining returns for only 6 out of 13 emerging markets. In short, the empirical evidence suggests that growth in GDP per capita does not explain returns. But why doesn t growth in GDP per capita explain returns? A number of reasons have been offered. These could be categorised into 4 main areas: 1. Expectation of high growth has already been priced in Negative correlation may be due to high growth being priced in at the start of the investment period (Siegel, 1998 cited in Ritter, 2005). Ritter (2005) believes that markets tend to assign high Price-to- Earnings and Price-to-Dividend multiples when economic growth is expected to be high. Hence, to receive the same dividend, more capital has to be committed, leading to lower realised returns. Dimson et al. (2010) share the same view that high growth is already priced in. Japan provides a good example of this effect. Growth expectations of Japan were overly optimistic during the 1980s when the markets priced in 20 years of future growth. Consequently, in the last two decades, equity returns were negative even though GDP continued to grow (MSCI, 2010a). 2. Businesses operate internationally Businesses operate globally in both strong and weak economies, thus returns cannot be clearly attributed to high versus low GDP growth economies (Dimson et al., 2010; MSCI, 2010a). For example, companies in developed countries may well be the ones benefiting from growth in emerging markets. Nearly 25% of total US profits and about 30% of sales of S&P500 companies are generated abroad (Wilmot, 2010). One case in point is the US chip industry, which recently cited strength of demand in emerging markets as a key sales booster (Nuttall, 2011): emerging markets account for more than 50% of unit volume in Intel and demand is not only isolated to lower-priced items but higher-priced PCs, smart-phones and tablets too. 3. High GDP growth is not driven by higher growth of existing firms Bernstein and Arnott (2003) believe that more than half of aggregate economic growth comes from the creation of new enterprises, as opposed to growth of established enterprises. For instance, much of the market capitalisation of U.S. companies today has come from industries (e.g. 4 Countries included in the study were Chile, Greece, Hong Kong, India, Korea, Malaysia, Mexico, Philippines, Portugal, South Africa, Singapore, Thailand and Turkey. 3

4 Information Technology and Pharmaceuticals) that barely existed 100 years ago. The beneficiary of new businesses is often venture capital rather than stock investments which participate in the growth of established businesses. 4. Investors may not be able to participate in the emerging market growth story because: a) Investment opportunities are not opened to international investors Dimson et al. (2010) observed that emerging market companies may be non-investable or have limited free-float as large holdings may be held by the government, family owners, cross-holding or domestic investors, leaving global investors unable to share in growth. b) Returns are diverted away from existing investors i) To new shareholders Bernstein and Arnott (2003) found that from 1926 to 2002, US market capitalisation grew at an annual rate of 2.3% faster than the price index suggesting that new issuance dilutes returns to investors. Emerging economies with high growth rates often attract investor interest which enables companies to raise funds through new issuance. However, this also means that existing shareholdings tend to be diluted as companies issue new shares to finance their growing capital needs. For example, while China s economy grew by 11.5% per annum from 1992 to 2002, the S&P/IFC price index of Chinese equities appreciated by only 3.5% per year. At the same time, market capitalisation grew at an annualised growth rate of 39%, suggesting share dilution from new issues. ii) To managers Returns may also be diverted away from investors to managers due to weak corporate governance and employee rent extraction in the form of sweetheart deals and additional share issuances to employees (Ritter, 2005; Arnott and Bernstein, 2002). iii) To consumers/users of new technology Siegel (2000) and Asness (2001) highlighted that in competitive economies, technological change largely benefits consumers and employees rather than shareholders. Faber (1997) illustrated this line of reasoning using the US railroad industry as an example. While the railroads industry grew significantly in the 19 th century, by 1893, 85% of all railroads in the US were either bankrupt, in reorganisation or had to be refinanced. Railroad stocks continued to perform poorly even between 1906 and 1921 when other industrial stocks were rising as regulation prevented railroad companies from raising rates. Hence, investors did not benefit from the growth in the railroad industry. Instead, railroads benefited users such as farmers in the Midwest and enabled industrialisation in different regions. c) GDP growth is not financed by the stock market Dimson et al. (2010) further cited Germany and Japan as examples of how GDP growth may be financed by banks rather than by the stock market leaving investors unable to share in the underlying economic growth. 4

5 Given that investment performance is not explained by growth in GDP per capita, the next section investigates what may possibly drive investment returns in emerging markets and analyses emerging markets performance through time. SECTION II: EMERGING MARKETS PERFORMANCE & THEIR DRIVERS How have Emerging Markets Really Performed? Long-Term Historical Performance vs. Developed Markets Dimson et al. (2010) compared emerging markets and developed markets performance from and found that contrary to common belief, emerging markets (9.5% annualised) actually underperformed developed markets (10.6% annualised). Further analysis reveals that whether emerging markets deliver superior returns depends on when emerging market investments were made. For example, while Dimson et al. (2010) found that emerging markets underperformed developed markets from , an emerging market portfolio held from would have outperformed. Similarly, Barry et al. (1997) found that emerging markets outperformed US equities during but underperformed from (Exhibit 1) and rationalised that the underperformance could be due to the Latin America debt crisis and the associated lost decade (roughly from 1979 to 1988) being included in the longer period. Exhibit 1 Historical Monthly Compounded Returns and Standard Deviation Index Arithmetic Average Standard Deviation Compound Average Sharpe Index Values Return (%) (%) Return (%) (%) December 1975 June 1995 Emerging Composite S&P June 1985 June 1995 Emerging Composite S&P June 1990 June 1995 Emerging Composite S&P Source: Barry et al. (1997) Table 4. Emerging market returns are based on a composite Barry et al. (1997) constructed. Performance on a rolling-period basis However, as market timing is extremely difficult in practice, we instead considered what investors are more likely able to control, i.e. the length of their investment horizons, and examined if relative performance varies with different lengths of holding periods. Using different monthly entry points from Jan 1988, we computed the rolling 3-year, 5-year and 10- year holding period returns (compounded, annualised) for developed markets and emerging markets 5. For example, for 3-year rolling returns, we computed returns from Jan 1988 to Dec 1990, from Feb 1988 to Jan 1991 and so on, with the final 3-year period being Apr 2008 to Mar Developed market returns are computed using the MSCI World Total Return Gross Index in USD while emerging market returns are computed using the MSCI Emerging Total Return Gross Index in USD. 5

6 Exhibit 2 shows that in none of the holding periods did emerging markets consistently outperform developed markets. However, an investor who is invested in emerging markets for a shorter period of time (3-years or 5-years) seems to stand a higher chance of outperforming developed markets than one who is invested in emerging markets for a 10-year period (Exhibit 3). One possible hypothesis is that this could be because long holding periods are more likely to include the negative effects of crises. Incidentally, such negative effects are more pronounced for emerging markets than developed markets as emerging markets crises are characterised by larger price declines and longer recovery periods (Patel and Sarkar, 1998). On average 6 though, emerging markets have outperformed developed markets. Exhibit 2: Rolling 3-year, 5-year and 10-year holding period returns of Developed and Emerging Markets Source: Bloomberg; Authors calculations 6 For each investment period (with the same start and end date), the arithmetic difference between emerging market returns and developed market return is computed (i.e. emerging market return (less) developed market return). The average of all such differences is then computed for each holding period and presented in Exhibit 3. 6

7 Exhibit 3: Proportion of times Emerging markets Outperform Developed markets and Average Out (Under) Performance % of times Emerging Markets 3 Years 5 Years 10 Years Outperform Developed Markets 74% 65% 42% Underperform Developed Markets 26% 35% 58% Total no. of data points Average Returns Difference of Emerging Over Developed 5.5% 4.3% 0.7% Source: Bloomberg; Authors calculations A similar pattern emerges when computing risk-adjusted returns (defined here as returns per unit of risk 7 ). Again, emerging markets did not consistently outperform developed markets (Exhibit 4) and an investor stood a higher chance of outperforming for shorter holding periods (Exhibit 5) on a riskadjusted basis. However, when compared to non-risk adjusted returns, the number of times when emerging markets portfolios outperformed developed markets fell across all holding periods (Exhibit 5). In addition, on average 8, emerging markets underperformed developed markets on a riskadjusted basis. Exhibit 4: Rolling 3-year, 5-year and 10-year risk-adjusted returns of Developed and Emerging Indices Source: Bloomberg; Authors calculations 7 Risk is defined as the annualised standard deviation of monthly returns during the relevant holding period. 8 For each investment period (with the same start and end date), the arithmetic difference between the risk-adjusted return of emerging market and developed market return is computed (i.e. emerging market return (less) developed market return). The average of all such differences is then computed for each holding period and presented in Exhibit 5. 7

8 Exhibit 5: Proportion of times Emerging markets outperform Developed markets on a risk-adjusted basis % of times Emerging Markets 3 Years 5 Years 10 Years Outperform Developed Markets 62% 63% 27% Underperform Developed Markets 38% 37% 73% Difference in % of times emerging markets outperform developed -11% -3% -15% markets compared to Exhibit 3 Average Risk-adjusted Returns Difference of Emerging Over -4.1% -4.6% -18.1% Developed Source: Bloomberg; Authors calculations Our observations largely tie in with Barry et al. (1997) findings and comments, in which they noted that in the first 5-year period from Dec 1975 June 1980, the emerging market composite gained 227% but lost 49% in the next subsequent 5-year period, before gaining 66% in the final 5 year period. Barry et al. (1997) also cautioned that investors should be aware that the risk [of investing in emerging markets] is not necessarily removed by commitment to a long holding period. Why then is there a common misconception that emerging markets outperform developed markets? Given the rather surprising results that emerging markets returns are not consistently higher than developed market returns, a natural question is what gave rise to the common belief that emerging markets outperform developed markets. Two possible reasons are offered: 1. Most studies on emerging market performance tended to focus on the post-1984 period which would have thus excluded the Latin America debt crisis in the 1980s because 1984 was the base year for the International Finance Corporation (IFC) value-weighted indexes (Barry et al., 1997), leading emerging market performance to appear better than they in fact are. This biased view might have been further exacerbated by the fact that crises tend to have a larger impact on emerging markets than developed markets. Patel and Sarkar (1998) studied 9 stock market crises in and found that emerging markets crises tend to experience larger price declines than developed markets (Exhibit 6). Exhibit 6: Impact of Crises in Different Markets Beginning of Crisis 9 Beginning of Crash 10 Date of Trough 11 Price Decline to Trough Developed Latin America Emerging Asia Jun-73 May-74 Sep % Oct-80 Jun-82 Jun Aug-87 Nov-87 Jan Jun-80 Jul-81 Dec Sep-87 Nov-87 Nov Sep-94 Feb-95 Feb Dec-78 Aug-80 Oct Mar-90 Sep-90 Sep Apr-96 Aug-97 Dec Source: Patel and Sarkar (1998) Table 1. 9 The beginning of the crisis is defined as the month when the index reached its historical maximum prior to the month when the crash was triggered. 10 The beginning of the crash is defined as the month when the regional price index fell by more than 20% for developed markets and more than 35% for emerging markets. 11 The trough is the month when the price index reached its minimum level during the crisis. 8

9 2. Many studies are focused on recently emerged markets. Goetzmann and Jorian (1999) found that returns soon after emergence are greater than both before emergence 12 and the period after. Empirically the difference 13 in returns was found to be the greatest for the 4-year period after emergence, followed by 3-year and then 5-year. Thus, given that studies are often focused on recently emerged markets, there tends to be a bias in favour of emerging markets. A comparison of BRIC versus other emerging markets Given that the phase of emergence seems to have a significant bearing on performance of emerging markets, we analysed if this line of reasoning might be able to explain the relative performance of BRIC (Brazil, Russia, India and China) versus other emerging markets. It might be argued that BRIC are now in the after emergence phase compared to other emerging markets. Goetzmann and Jorian (1999) identification of the point of emergence is related to when investors attention is drawn to a market. We believe that global investors attention was drawn to BRIC when Goldman issued its Oct 2003 report 14 where it projected that by 2050, BRIC s GDP would surpass that of the G6. Hence, we define Oct 2003 as the point of emergence. We then compared the performance of BRIC versus that of other emerging countries in the 3 years, 4 years and 5 years after the point of emergence. These time periods were picked as Goetzmann and Jorian (1999) found that 4-year window gave the largest difference in returns followed by 3-year and then 5-year. Indeed, the out-performance of BRIC versus other emerging countries was the greatest for the 4- year period (Exhibit 7) after Goldman s report followed by the 3-year and then the 5-year periods. Exhibit 7: Annual Returns of BRIC vs. Other Emerging Countries, following Goldman s Report Date of Goldman Report Duration Period Brazil Russia India China Average Excess over EM Index Oct-03 3 years Nov 03 - Oct 06 50% 42% 39% 27% 40% 10% Oct-03 4 years Nov 03 - Oct 07 64% 40% 48% 51% 51% 12% Oct-03 5 years Nov 03 - Oct 08 27% 7% 13% 13% 15% 5% Source: Bloomberg; Authors calculations 12 In a simulation study, Goetmann and Jorian (1999) defined emergence to have occurred when market capitalisation has grown large enough indicating that the markets have attracted the attention of global investors. In their empirical analysis, they used the first date at which IFC compiles a market index as the date of emergence as introduction of new markets into performance benchmarks is closely watched by portfolio managers. 13 Goetzmann and Jorian (1999) compared the performance during the period immediately after emergence and that of a subsequent period of the same length for 3-year, 4 year and 5-year windows. 14 Earlier in November 2001, Goldman already issued a report on BRIC but arguably the earlier report gave less new news as it re-affirmed the common belief that emerging countries (e.g. BRIC) will grow faster than developed countries. Hence, in our view the Oct 2003 report was the more significant report. 9

10 Given that the above analysis shows that emerging markets performance varies through time, we next explore what could explain the varying investment performance. What Drives Emerging Markets Performance? Local Macroeconomic Factors If we assume that emerging markets are not perfectly integrated, it then follows that local macroeconomic factors may be relevant proxies for sources of risk in emerging market returns. Hence, we now turn to local macroeconomic factors that may be useful in identifying high-and lowexpected return environments in emerging markets. 1. Trade as a proportion of GDP Bekaert and Harvey (1997) argue that the size of the trade sector as a proportion of the total economy is a good proxy for openness of both the economy and the investment sector and thereby market integration. Bekaert et al. (1997) found that trade as a proportion of GDP has the ability to distinguish between high and low expected returns in emerging markets 15. In fact, they concluded that countries with small trade sectors as proportion of GDP had higher expected returns than countries with larger trade sectors, as the former were more likely to be segmented from the world economy. Bekaert et al. (1997) believe that the size of the trade sector produced a total alpha 16 of 18.9% over the MSCI AC World Index from 1991 to using an equally-weighted portfolio of emerging markets stock indexes with quarterly rebalancing, in which lagged values of the trade as proportion of GDP variable is used to determine which countries were included in the portfolio. 2. Size of the national stock market Bekaert and Harvey (1997) also argue that the size of the national stock market is an adequate proxy for the degree of a country s financial integration. They assert the view that a larger stock market suggests that a country is more likely to be integrated into world capital markets. They use market capitalization divided by last year s GDP as a measure of market integration. Bekaert et al. (1997) study further supports the arguments of Bekaert and Harvey (1997) by concluding that the size of the equity market relative to economic activity has significant predictive power regarding future expected returns. In fact, they concluded that countries with a small market capitalization as a proportion of the previous year s GDP had higher expected returns than countries with larger market capitalization as the former were more likely to be segmented from the world economy. In fact, Bekaert et al. (1997) found an alpha of 22.3% over the MSCI AC World Index from 1991 to using an equally weighted portfolio of emerging markets stock indexes with quarterly 15 The study included the following countries: Argentina, Brazil, Chile, China, Colombia, Czech Rep., Greece, Hungary, India, Indonesia, Jordan, Malaysia, Mexico, Nigeria, Pakistan, Peru, Philippines, Poland, Portugal, South Africa, South Korea, Sri Lanka, Taiwan, Thailand, Turkey, Venezuela and Zimbabwe. 16 Alpha is a risk-adjusted measure used to calculate the return in excess of the compensation for the risk borne by the investor. 17 The 1991 to 1996 sample period is chosen so as to remove the impacts that emerging market integration have on returns. We advise the reader to consider these results with care as the regression results are likely to suffer from a small sample bias. Moreover, when future returns are regressed on lagged variables, the error terms of the regression are likely to be correlated with the regressor s innovations. Consequently, both the coefficient estimates and the significance levels are likely to be biases. 18 The 1991 to 1996 sample period is chosen so as to remove the impacts that emerging market liberalizations have on returns. Please also refer to footnotes 15 and

11 rebalancing, in which lagged values of the market capitalization as a proportion of the previous year s GDP variable was used to determine which countries were included in the portfolio. 3. Political and Economic Risk Using the International Country Risk Guide (ICRG) 19 published by Political Risk Services, which includes a political risk index (ICRGP), an economic risk index (ICRGE), a financial risk index (ICRGF), and a composite risk index (ICRGC), Bekaert et al. (1997), subsequent to running regressions on each ICRG index, found that considerable information is contained in the economic and political ICRG ratings. Bekaert et al. (1997) found that portfolios comprised of emerging markets with low economic and political IRCG ratings (higher risk) produced an alpha of 37.3% and 29.3% respectively over the MSCI AC World Index from 1991 to 1996 using capitalization weights and quarterly rebalancing. These results are consistent with those presented in the Bekaert et al. (1996) study, which finds that countries which begin with very low country credit ratings (high risk) tend to improve (deteriorate), producing abnormal returns 20. However, a limitation of such studies is that whenever a survey is used to rate credit, political, or financial/economic risk, it is hard to define exactly the parameters taken into account as, at any point in time, an expert s recommendation will be based upon factors he or she feels are most relevant. 4. Inflation Empirical tests provided mixed results. While Fama and Schwert (1977) and Gultekin (1983) found negative relationships between inflation and nominal stock returns, Ritter and Warr (1997) presented evidence that valuation ratios tend to rise as inflation drops. 5. Country Credit Rating Country credit ratings were found to have substantial predictive power in differentiating between high and low expected returns in emerging stock markets (Erb et al., 1995). To validate their hypothesis, Erb et al. (1995) constructed equally weighted quartile portfolios of 14 emerging countries from highest country credit rating (1 st quartile) to lowest country credit rating (4 th quartile) over a period beginning in 1980 and ending in As can be seen in Exhibit 8, the credit risk variable is able to distinguish between high and low expected returns. The highest risk quartile has an average annual performance of 34.3% per year, while the lowest risk quartile has an average annual performance of 7.9%. Surprisingly, the volatility of the returns in all portfolios is fairly similar. 19 For more information, please visit 20 The Bekaert et al (1996) study, which has different sample period ( ), finds that the composite, financial and economic ratings are able to distinguish between high and low expected returns in emerging markets. 11

12 Exhibit 8: Country Selection Strategies Based on Country Credit Rating Rating Portfolio Characteristics-March 1980 to December 1993-In U.S. Dollars Annual Return (%) Annual Volatility (%) Average Dividend Yield (%) Highest Credit Risk High Credit Risk Low Credit Risk Lowest Credit Risk Source: Erb et al. (1995) Average Credit Rating 6. Currency Risk Barry et al. (1998) found that over a 20-year period from December 1975 June 1995, approximately 50% of returns (in local currency terms) were erased by depreciating currencies for a composite index, measured in US dollars, consisting of 17 emerging markets 21. Similar declines were found for 10-year and 5-year periods ending June However, this is not to be interpreted simplistically as emerging markets mean falling currency values. For example, in the 10-year period ending in June 1995, Taiwan, Malaysia and Thailand experienced currency appreciation. These findings highlight the importance of considering currency risks for global investors and the value of predicting currency movements. Research from Kumar et al. (2003) suggests that useful variables in predicting currency crashes include 12-month percentage changes in foreign exchange reserves, real GDP expressed as a deviation from trend and regional contagion. In non-crisis periods, a combination of fundamental analysis (based on relative real interest rate and relative GDP growth rates for directional trades) and technical trading rules (based on moving average, support and resistance rules) has been found to improve risk-adjusted returns (de Zwart et al., 2009). In addition to considering the direction of currency movements, it is also important to consider correlation of exchange rates movement with other asset classes. Analysing real exchange rates behaviour over , Dimson et al. (2002) observed that in spite of the high currency volatility during the 20 th century, currency risk did not add greatly to the risk of a US investor invested in international equities because the correlation between equity and currency returns were typically low and slightly negative, averaging across 15 non-us developed equity markets. In fact, exchange rate risk could offset local equity market risk so much so that a US investor would have experienced less volatility than domestic investors in Netherlands, Denmark and Sweden between 1950 and The negative correlation in developed countries could be the result of depreciating currencies increasing the attractiveness of the countries exports, leading to increased earnings and stock prices of exporters (Solnik and McLeavey, 2009 cited in Conover, 2011). Hence, in considering the impact of currency risk, it is important to consider correlation between exchange rate fluctuations and equities. In emerging markets, stock returns and currency changes are traditionally positively correlated as investors tend to lose confidence in both emerging market currencies and stocks during times of crisis (Conover, 2011). For example, using data from 1996 through 2005 for 17 emerging markets 22, 21 Countries covered in the study were Greece, Jordan, Nigeria, Zimbabwe, Argentina, Brazil, Chile, Colombia, Mexico, Venezuela, Korea, Philippines, Taiwan, India, Malaysia, Pakistan and Thailand. 22 Emerging markets covered in the study were Argentina, Brazil, Chile, Mexico, Peru, India, Indonesia, Korea, Malaysia, Philippines, Taiwan, Thailand, Czech Republic, Hungary, Poland, Russia and Turkey. 12

13 Cumperayot et al. (2006) found that extreme stock market declines are associated with currency declines in 13 out of 17 emerging countries. In a number of emerging markets undergoing a severe crisis 23, an extreme stock market decline significantly increased the probability of an extreme currency depreciation occurring on the same day. The observed effect of stock markets on currency markets might be due to large equity outflows depressing the currency or the fact that stock market anticipates a devaluation of a fixed or managed currency just before it occurs. Interestingly, more recent empirical research suggests that the relationship between stock market and currency returns might be changing in emerging markets. Chue and Cook (2008) examined two periods: and and found that in the earlier period, stock market and currency returns are positively related whereas in the later period, they found that this relationship is no longer significant and has even reversed sign. The positive relationship in the earlier period is believed to be the result of emerging markets having taken on excessive foreign-currency debt which implies that a depreciation of the local currency would increase firms debt burden, reducing returns. In the later period, the lack of relationship is consistent with the observations that domestic bond markets have grown in importance relative to international bond markets and that growing derivatives markets have enabled firms to hedge currency risks. In our view, the reversal in sign (albeit still statistically insignificant) may suggest that the correlation between currency and stock returns of emerging markets are gradually approaching that of developed markets where negative correlations are observed, in which case it may mean that hedging of currency risks for investors may become less important over time. Cumperayot et al. (2006) further found that spill-over of currency declines are usually contained within a region and that in some cases negative links were found across regions indicating flight of capital from one region to another during crisis periods. This suggests that investors could diversify currency risks by investing in different regions. Microeconomic Factors 1. Valuation Multiples a) Dividend-to-price ratio 24 Campbell and Shiller (2001) premised that the stability of a valuation ratio such as D/P and P/E implies that when a valuation ratio is at an extreme level, either the numerator (price) or the denominator (earnings or dividend) must move in a direction to restore the ratio to its normal level. Using aggregate annual US data from 1871 to 2000, Campbell and Shiller (2001) found that it is the denominator (price) and not the numerator (dividend) that brings the ratio back to its mean. They further showed that the D/P ratio had no forecasting power for stock price changes over the shortterm horizon (1 to 5 years), as the initial D/P ratio explains less than 1% of the annual variance of stock prices. However, when a long-term horizon of 10 years is considered, Campbell and Shiller (2001) noted a very significant positive relationship between the initial D/P ratio and the subsequent 10 years price growth. However, Campbell and Shiller (2001) study may be limited in that their study 23 The conditional probability of an extreme currency depreciation given a stock market decline was more than 20% for countries directly affected by the Asian crisis i.e. Indonesia (26%), Korea (23%), Malaysia (34%), Philippines (22%) and Thailand (22%). This is significantly higher than the 5% unconditional probability. 24 The D/P ratio is a widely used valuation ratio, but it can be affected by shifts in corporate financial policy. For instance, if stock repurchases replace dividends, then the past history of the dividend yield will be a misleading guide to future stock returns. 13

14 focused on the US, a developed market and thus it could be argued that their findings may not be applicable to emerging markets. b) Earnings Yield 25 Contrary to studies conducted on the US market (Bali et al. (2008); Lamont (1998) 26 ), Demirtas and Zirek (2010), who examined the time-series predictability of aggregate stock returns in 20 emerging countries 27 from 1977 to 2009, found that the earnings yield can predict one-quarter ahead market returns. In fact, they found the earnings yield coefficient was positive and highly significant in predicting expected returns 28. Moreover, they found that aggregate earnings co-vary positively with market returns, hence it is not just the mean reversion of stock prices (which was found to be negative and significant) that is responsible for the forecasting power of the earnings yield. There exists a positive and significant relationship between aggregate earnings and expected returns in emerging markets 29. A study by Demirtas and Zirek (2010), which examined the time-series predictability of aggregate stock returns in 20 emerging countries 30 from 1977 to 2009, found that, contrary to the US market (Shiller (1984); Fama and French (1988a and 1988b)), aggregate earnings may still contain information about future expected cash-flows. As opposed to the US, emerging markets have a lower number of industries and stocks are more highly correlated, meaning that idiosyncratic volatility is lower. Demirtas and Zirek (2010) were able to show that aggregate earnings co-vary positively with market level returns. c) Price-to-book ratio Using data from 1991 to 2001, Kouwenberg and Salomons (2003) found that emerging markets portfolio invested in countries with low price-to-book values significantly outperformed a portfolio of high price-to-book countries. The study covered 23 emerging markets from Asia, Latin America and Europe, Middle East and Africa 31 which investment professionals tended to focus on, thus excluding smaller and less liquid markets where investment strategies would be hard to implement due to transaction costs or other restrictions. The authors also set the beginning of the sample 25 In addition, while smoothed earnings used in the Campbell and Shiller (2001) study removes the occasional spikes in the P/E ratio and is in line with Graham and Dodd (1934) belief of using average earnings spanning across 7 or 10 years for valuation ratios, smoothed earnings also suffer from changes in accounting practices and inflation which can make it an unreliable indicator. 26 In contrast to Lamont (1998) and Bali et al (2008), Campbell and Shiller (2001) found that price-to-smoothed earnings (10 yr. moving average of earnings) ratio is good forecaster of 10 year growth in stock prices. These conflicting studies suggest to us that P/E or earnings yield may not be good predictors of returns in the US and possibly other developed markets. 27 Emerging countries covered in the study include Argentina, Brazil, Chile, China, Colombia, Czech Republic, Hungary, India, Indonesia, Malaysia, Mexico, Pakistan, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand and Turkey. 28 We note that these results are robust across different estimation methods and after Demirtas and Zirek (2010) control for a small sample bias in predictive regressions and for different macroeconomic variables. 29 A brief explanation about the predictive power of aggregate earnings follows: as opposed to the US market, the information content of firm-level earnings (unsystematic earnings) about future cash flows is not fully diversified away at the market level in emerging market, and hence, aggregate earnings covary positively with market level expected returns. 30 Emerging countries covered in the study include Argentina, Brazil, Chile, China, Colombia, Czech Republic, Hungary, India, Indonesia, Malaysia, Mexico, Pakistan, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand, and Turkey 31 Countries included in the study are China, India, Indonesia, Korea, Malaysia, Philippines, Taiwan, Thailand, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Venezuela, Czech Republic, Egypt, Hungary, Israel, Poland, Russia, South Africa and Turkey. 14

15 period to 1991, which is arguably the period when most emerging markets liberalization had already occurred by, in order to minimise the impact of a structural break in the data. Kouwenberg and Salomons (2003) ranked countries according to their P/B ratio at the beginning of each month and constructed four equally weighted portfolios, consisting of the emerging countries in each of the four P/B quartiles and recorded the returns of each portfolio during the month using Standard & Poor s and International Financial Corporation (S&P/IFC) indices for emerging equity markets. 32 The results of their study (Exhibit 9) showed that investing in countries with low P/B ratios (first quartile) led to outperformance in the sample period between January 1991 and December The average monthly return of 1.75% for the long strategy (first quartile) and 1.77% 33 for the long/short strategy (i.e. long position in the first quartile countries (low P/B) and short position in the fourth quartile countries (high P/B)) exceeded the average return of 0.73% for the equally weighted index portfolio of all emerging markets. Exhibit 9: Return and risk of the P/B strategy EW Index Q1 Q2 Q3 Q4 Long/Short Average Return 0.73% 1.75% 0.68% 0.48% -0.03% 1.77% (t-value) (1.35) (2.40) (0.96) (0.77) (-0.05) (2.84) Standard Deviation 6.2% 8.4% 8.1% 7.1% 6.2% 7.2% Downside Deviation 4.3% 5.2% 4.7% 4.9% 4.7% 4.1% Downside Correlation 61% 51% 39% 61% 59% 2% Worst returns -27.4% -31.8% -27.1% -25.3% -24.9% -15.6% Worst month Aug 98 Aug 98 Aug 98 Aug 98 Aug 98 Jan 99 Kouwenberg and Salomons (2003) Study From the above findings, one may interpret that higher returns are compensation for taking on additional risk (measured by higher standard deviation). However, such reasoning would not hold true for the long/short value strategy as it has lower downside deviation, downside correlation, and worst return but higher average return than the equally weighted index portfolio of all emerging markets. Kouwenberg and Salomons (2003) also found that using market beta as an alternative form of risk measurement similarly does not explain the positive performance of the long/short value strategy. Linkage between local macroeconomic variables and microeconomic factors Kouwenberg and Salomons (2003) provided a possible linkage between local macroeconomic variables and microeconomic factors by measuring the macroeconomic variables for the countries in each P/B quartile at portfolio formation 34 (Exhibit 10). Countries in the low P/B portfolio (Q1) had low GDP growth and higher GDP growth volatility compared to countries in the high P/B portfolio (Q4). Results also suggest that low P/B countries also had significantly higher inflation rates, and a more volatile and overvalued exchange rate on average 32 The quartile portfolios are rebalanced based on the new price-to-book ratios on a monthly basis 33 Transaction costs are believed to be limited, as even for the long/short portfolio, there are only two changes to the portfolio per month. 34 As the portfolios are equally weighted, Kouwenberg and Salomons (2003) also weight the macroeconomic variables of all countries in the portfolio equally each month, in order to get a time series of economic measures at the portfolio level. 15

16 than countries in the high P/B portfolio. Seen in this light, the price-to-book strategy is buying recent macroeconomic losers and selling recent macroeconomic winners. 16

17 Exhibit 10: Average of the five macroeconomic variables for the price-to-book quartile portfolios Variable Q1 (long) Q4 (short) Q1 Q4 (long/short) T-Value RG 3.1% 5.4% -2.3% -9.7 RGV 5.3% 1.6% 3.7% 14.2 IF 142.8% 17.3% % 6.8 PPPFX 9.1% 3.1% 6.0% 9.8 FXV Source: Kouwenberg and Salomons (2003) Study. RG refers to real GDP growth (YoY change); RGV refers to volatility of real GDP growth based on 3 years of monthly data; IF refers to inflation (YoY change); PPPFX refers to percentage deviation of spot rate from PPP and FXV refers to coefficient of variation based on 3 years of monthly data. The results from the Kouwenberg and Salomons (2003) study offer an interesting analogy with earlier research by Lakonishok et al. (1994), which provides a behavioural explanation for the superior returns of value strategies: naive investors extrapolate past experience too far into the future. Applied in this context, countries in the low P/B portfolio (Q1) might be perceived as losers with a bad economic outlook based on current conditions (lower and more volatile growth, higher inflation, currency turmoil, etc) and investors do not expect a macroeconomic reversal for these countries, leading to depressed equity prices and low P/B multiples. However, after portfolio formation, these countries often beat the low expectations and show some economic improvement, leading to superior stock market performance relative to countries in the high P/B portfolio. On the other hand, countries with high P/B multiples are expected to perform well in the future based on past and current favourable macroeconomic conditions, but often fail to beat expectations, leading to relatively subdued equity market performance. Exhibit 11 provides additional statistical evidence for the extrapolation hypothesis. It demonstrates that 3 years after portfolio formation, the macroeconomic gap between low P/B countries ( macroeconomic losers ) and high P/B countries ( macroeconomic winners ) had reduced significantly for all variables, except for currency overvaluation (PPPFX). Exhibit 11: Average of the five macroeconomic variables for the long-short P/B portfolio 3 years after formation Variable Q1 Q4 at portfolio formation Q1 Q4 36 month after formation Change in exposure from formation to 36m after RG (t-value) -2.3% (-9.6) -0.7% (-2.8) 1.5% (3.4) RGV (t-value) 3.7% (14.2) 1.3% (7.8) -3.2% (-12.1) IF (t-value) 125.4% (6.8) 97.8% (3.4) -74.6% (-2.0) PPPFX (t-value) 6.0% (9.8) 8.9% (7.8) 2.8% (1.7) FXV 0.18 (t-value) (10.1) Source: Kouwenberg and Salomons (2003) Study 0.09 (4.8) (-9.9) Having obtained an understanding of emerging markets investment performance and factors that affect emerging market returns, the next section looks at why an investor might want to invest in emerging markets particularly in a portfolio context. 17

18 SECTION III: WHAT IS THE POTENTIAL VALUE TO BE GAINED FROM INVESTING IN EMERGING MARKETS? Diversification In the following paragraphs, we analyse diversification benefits of investing in emerging markets at multiple levels: from the broader perspective of diversifying between emerging markets and developed markets to diversifying amongst emerging markets and finally diversifying within a single emerging market. Adding Emerging Markets to a Developed Markets Portfolio The long-term case for investing in emerging markets rests upon the prospect of taking advantage of diversification opportunities, thereby enhancing a portfolio s risk-return profile. The benefits available are a function of the level of correlation between emerging and developed market returns, as well as their relative risks and returns. Various empirical studies have been conducted that support the diversification potential of emerging markets. Errunza et al. (1999) found that the average correlation of the S&P 500 Index with the authors sample of nine emerging markets was 0.09, while the comparable average correlation with their sample of seven developed markets was considerably higher, at 0.40 for the period The findings of Harvey s (1995) study similarly support the diversification potential of emerging markets, with his study reporting correlation between developed and emerging markets of only 0.14 for the period March 1986 to June Our own research also supports the case for emerging market assets as diversification tools. We find that for the period January 1999 to March 2011, the average correlation between the MSCI World Index (which is a developed markets index) and twenty emerging markets was 0.56 compared to the average correlation between twenty-four developed countries, which was found to be This indicates the possibility for investors to improve the risk-return profile of their portfolio by including emerging market assets. As a result, although emerging markets experienced high volatility relative to developed markets during the period January 1999 to March 2011, Exhibit 12 illustrates that a portfolio mix of approximately 20% invested in the emerging markets index and 80% in the developed markets index produced the minimum variance portfolio for these two assets. Therefore, the addition of riskier emerging market stocks created a less risky portfolio than one composed entirely of the developed markets composite index (MSCI World Index), as well as resulting in higher return. In fact, a portfolio comprising only developed markets securities (as represented by the MSCI World Index) is not on the efficient frontier for this period. 35 Notably, correlation coefficients in our research are higher than earlier researches cited in the paragraph above. Several reasons could account for the difference: (i) Enhanced integration between financial markets increases correlation (ii) correlations tend to increase during crisis periods and the subprime crisis in was included in our study and (iii) our research uses different variables from the earlier study. 18

19 Exhibit 12: Portfolio Combinations of emerging markets and developed indices (Jan 1999-Mar 2011) Arithmetic Average Annualised Monthly Returns 14.0% 13.8% 13.6% 13.4% 13.2% 13.0% 12.8% 12.6% 100% emerging index 12.4% 100% 12.2% developed index 22.5% 23.0% 23.5% 24.0% 24.5% 25.0% Source: Bloomberg; Authors calculations Standard Deviation of Annaulised Monthly Returns If one examines the longer period January 1988 to March 2011, we can see that similar diversification opportunities existed (Exhibit 13). Over that period, the correlation between the indices was 0.76, as compared with 0.86 over the shorter period. The minimum variance portfolio required approximately a 75% investment in the emerging market index. Exhibit 13: Portfolio Combinations of emerging markets and developed indices (Jan 1988-Mar 2011) 12.90% 12.80% 12.70% 100% emerging index Arithmetic Average Annualised Monthly Returns 12.60% 12.50% 12.40% 12.30% 12.20% 100% developed index 19.00% 20.00% 21.00% 22.00% 23.00% 24.00% Standard Deviation of Annaulised Monthly Returns Source: Bloomberg; Authors calculations These results are indicative of the fact that relative performance varies over time (a topic which will be dealt with in more detail in a later section). Consequently, asset allocation must be dynamic in order to optimise portfolio performance. Asset allocations based on historical returns tend not to produce optimal performance in future portfolios. It is important to note that the results are limited by the fact that here we are considering a composite index of emerging countries. By doing so, one loses some of the idiosyncrasies of 19

20 individual emerging markets. In fact, we find that during the period January 1999 to March 2011, the average correlation between the MSCI World Index and twenty emerging markets 36 was 0.56, significantly lower than that for the emerging markets index (which was 0.86). Furthermore, it is important to note that this is merely an average and that the correlation between individual emerging countries and developed market index varies greatly. In fact, over the period tested, correlation was found to be as low as 0.19 in the case of Poland, but as high as 0.81 in the case of Mexico (see Appendix). This highlights the importance of looking at individual countries rather than simply considering emerging markets as a group in order to maximise the benefit that is gained by adding emerging market assets to a developed markets portfolio. This is supported by Barry et al. (1997) who concluded that some individual emerging markets provide powerful diversification opportunities for U.S. domestic investors. They found that some of the smaller and, at the time, newer emerging markets did not provide meaningful diversification benefits for U.S. stock portfolios. The reason for this was that correlations between those markets and the U.S. market were not low enough to offset the effects of high variability within individual emerging markets. Similarly, Barba and Ceretta (2010) found that for international diversification, each country should be analysed separately. Investigating four Latin American emerging markets (Argentina, Brazil, Chile and Mexico) and the United States before, during and after the financial crisis of 2007/2008, they concluded that the Latin American stock markets do not react homogenously to shocks in the U.S. stock market. Correlation over time Although the advantages of diversifying a portfolio through international investing are widely accepted, the benefits of doing so are not constant over time. Exhibit 14 shows that average correlation between emerging markets and the developed markets index has strengthened tremendously over the past ten years, with a spike in correlation when the financial crisis hit. Once the initial effect of the crisis wore off, correlation weakened, however, the general upward trend remains clearly evident. Exhibit 14: 24-month rolling average correlation between individual emerging markets and the developed markets index M M M M M M M M M M M M M M M M M M M M M M M M M01 36 Emerging markets are taken to be twenty of the twenty-one markets forming the MSCI Emerging Markets Index as at 27th May, 2010: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Morocco, Peru, Philippines, Poland, Russia, South Africa, Taiwan, and Thailand. Data for Turkey was not included due to limitations in data availability. 20