Investing on Business Climate and Reform in Emerging Markets: An Equity Portfolio Performance Evaluation

Transcription

1 Investing on Business Climate and Reform in Emerging Markets: An Equity Portfolio Performance Evaluation Facundo Martin, Camilo Mondragón-Vélez and Laura Vila International Finance Corporation World Bank Group January 2014 Abstract Extensive analysis and economic research has shown that a better business environment with sound institutions enforcing regulations is a crucial contributor to economic growth and prosperity. Accordingly, stock market returns should reflect improvements in the business environment. Therefore, this paper studies the relationship between business climate and reform with the performance of equity markets. The main question we address is if equity prices understood as short term available indicators of changes in investors views regarding expected long term performance react to signals of improvement in the business environment. For this purpose we test an investment strategy based on information from the World Bank s Doing Business and the World Economic Forum s Global Competitiveness Index, which over-weights the most actively reforming countries and passively replicates local stock market indices within each country. Our sample includes Emerging and Frontier markets during the period Our preliminary results suggest that a portfolio that assigns higher weight to countries that start from a low ranking and exhibit a greater momentum at improving their business climate, outperformed standard equity market benchmarks such as the MSCI Global Emerging Market Index, especially before the 2009 global financial crisis. Keywords: Business Climate, Emerging Markets, Frontier Markets, Equity Indices and Returns, Investment Strategy, Portfolio Allocation JEL Classification: D20, F21, G11, G15 The views expressed in this paper are those of the authors and do not necessarily represent those of the IFC, IFC management or the World Bank Group. All errors and omissions are sole responsibility of the authors. Corresponding Author: Camilo Mondragón-Vélez (CMondragonvelez@ifc.org) 1

2 1. Introduction The idea that better business environments generate greater economic growth and opportunity relies in a broad sense on the critical role of productivity in Solow s neo-classical growth theory. While higher productivity is the main driver of economic growth in the long term, an adequate environment to create and develop businesses is a necessary condition for an economy to become more productive; or as described in the World Bank s Doing Business website: A fundamental premise of Doing Business is that economic activity requires good rules. 1 The development of indicators such as the World Bank s Doing Business (DB) and the World Economic Forum s Competitiveness Indices (Business Competitiveness Index BCI, and Global Competitiveness Index - GCI), has not only improved the understanding of key elements and necessary reforms to improve the business environment and increase productivity overall, but has also generated awareness of these important issues for economic development around the world for the past decade. However, the long term nature of the expected economic performance following reform efforts to improve countries business environments, as measured by the indicators included in the DB and the BCI/GCI, makes it difficult to provide comprehensive empirical evidence in this regard at this point in time given the fact that these indicators have been collected for a relatively short period of time, in relation to the long term assessment implied by theory. However, a growing literature developed in the past decade has provided mixed evidence in this regard (see for instance, Djankov et. al, 2002; Ardagna and Lusardi, 2009; and Stel, Storey and Thurik, 2007). Extensive empirical articles and working papers have been written and published using data such as the one presented by Doing Business. The latest report, Doing Business in 2014, analyzes in detail many of the most recent findings 2. Most of the research so far has focused on the way that economic performance and development are affected by excessive business regulation in the way that firms go informal or cut investment as they find too costly to engage in the formal economy. Other studies looked into how trade costs affect an economy s export and import performance, while other more recent studies have focused on areas such as courts, credit markets, bankruptcy laws, and investor protection. The distortionary nature of high taxes and cumbersome tax systems has also been in the target of the literature, while many others have focused on how much a good business regulatory See Research on the effects of business regulations, pages in Doing Business 2014: Understanding Regulations for Small and Medium Size Enterprises. 2

3 environment matters for economic growth, higher productivity, and innovation. Results usually lead to the fact that a better business regulatory environment leads to faster growth, higher labor and total factor productivity in some countries, better living standards, and more incentives towards innovation. We have not found yet to the best of our knowledge literature linking the business climate data with performance of equity markets, and even less in terms of using the investment climate data as signals for asset allocation. Thus, in this paper we propose an alternative approach to overcome the lack of long term series on economic performance following reform, by using equity market prices as short term signals related to longer term views. Hence, we don t try to quantify the relationship between the business environment and the reform effort with long term performance per se; but with investors views about the long term as signaled by observed equity prices in the short term. The main idea behind this exploration follows a simple logic. Based on Gordon s (1959) growth model (also known as the Dividend Discount Model DDM), observed equity prices are driven by the expected growth rate of investment cash flows in the long term. In turn, the long term growth trend in investment cash flows for an investment portfolio (of listed companies) in a specific country should be a reflection of the country s economic growth prospects. Therefore, if (global) investors believe that reforms to improve the business environment will have a positive impact in long term growth, the local market equity index should increase shortly after in those countries showing higher reform efforts. In other words, improvements in the business environment domestically should increase the size of the domestic market in the medium to long run, as more entrepreneurs will try to start firms, some of these startups will survive while a small fraction could become large corporations. Overall, the private sector will grow more, adding more jobs and prosperity for the system as a whole. Reform efforts may also signal the governments willingness to continue improving conditions for further investment to take place, generating expectations of a virtuous cycle. Therefore, current equity valuations should reflect some of these expected effects in the short run. In order to test the validity of this logic we document the relationship between equity returns and business environment reform indicators in emerging markets through the performance evaluation of an investment strategy driven by reform signals relative to alternative global emerging markets equity benchmark indices. In short, the question this paper tries to answer is: how an investment 3

4 portfolio strategy (on listed country equity indices) driven by business environment and reform will perform relative to alternative benchmarks? We start by documenting facts about business environment and reform across emerging markets for the period , as provided by the DB and GCI indicators. We also look at country index returns and alternative benchmarks for investment strategies in the emerging markets equity asset class. Finally, we focus on the main contribution of this study, which is to document the performance of an investment strategy based on alternative combinations of elements within the DB and GCI (of measures such as rank, change in rank and number of reforms; as well as of combinations of indicators that generate the overall DB score: ease of starting a business, taxes, etc.). 3 To do this we build a signal for each combination of DB and GCI indicators and measures considered; which determines a deviation from the allocation each country included in the analysis has in the benchmark portfolio. Our preliminary results for the period March 2004 to February 2010 show that strategies driven by number of reforms and change in rank, as well as the rank inverse (and mainly by over-weighting DB relative to GCI indicators) tend to over-perform standard benchmarks and generate more efficient portfolios. Therefore, the evidence so far supports the intuitive idea that equity prices in the short run reflect investors views on countries long term performance following significant efforts to improve their business environment. This paper is organized as follows: Section 2 describes the DB and GCI data, as well as the equity market data used in the analysis; Section 3 provides an overview of equity markets performance, as wells as business environment dynamics as measured by DB and GCI over the period of analysis; Section 4 describes the investment portfolio strategy test; and Section 5 concludes. 3 We use the Global Competitiveness Index (GCI) instead of the Business Competitiveness Index (BCI), despite the fact that the BCI is thematically closer to the Doing Business for two reasons. First, the BCI series was discontinued after Second, the GCI is a broad business environment index, while BCI indicators are embedded in the GCI. 4

5 2. Data The data we use to build a signal of business conditions and improvement in the business environment is the World Economic Forum s Global Competitiveness Index (GCI) and the annual IFC/WB Doing Business report (DB). These two surveys complement each other capturing different aspects of the business environment. The DB report provides a measure of regulations related to the business environment for about 190 countries, as well as the number of (positive or negative) reforms carried along each of the ten dimensions it focuses on: starting a business, applying for licenses, registering property, obtaining credit, trading across borders, protecting investors, paying taxes, enforcing a contract and applying bankruptcy laws. On the other hand, the GCI measures competitiveness across more than 140 countries by looking at the set of institutions, policies, and factors that determine the level of productivity of a country. The GCI is a a weighted average of many different components, each measuring a different aspect of competitiveness, including institutions, infrastructure, macroeconomic environment, health, education, efficiency of goods and labor markets, financial market development, market size, innovation, business sophistication, and technological readiness. 4 The Doing Business (DB) consists of a series of surveys that are sent once a year to local practitioners of the law and regulations in each different area of interest including lawyers, regulatory authorities and tax experts, among others. The surveys are then coded and reform studies are done for cases when the regulation has changed from one year to the next. The report with the data and all the indicators is usually published between September and October, with data that corresponds to the previous year, providing a clear description of the environment to do business in each country and each area. Doing Business is not a perception-based survey, but a quantification of what the laws and regulations of each country stipulate for each area of business. Doing business was first published in September 2003 and has been published annually ever since. 5 The Global Competitiveness Index, on the other hand, is a weighted aggregation of scores of various indicators. More than 100 indicators are sorted into 3 large sub-indexes basic 4 A few DB individual variables are also part of GCI, but only represent a marginal weight of the whole index the number of procedures and the time required to start a business, together with DB s Legal Rights Index are 3 of more than 50 indicators used as efficiency enhancers to qualify the overall index that is composed with 46 other indicators. 5 For more information on Doing Business see Report.pdf 5

6 requirements, efficiency enhancers, and innovation and sophistication factors. The weight on each of these sub-indices depends on each country s stage of development. 6 While some indicators are opinion-based, many others are not, but all are coded into a similar scale to make the aggregation feasible. The Global Competiveness Index is part of the Global Competitiveness Report prepared by the World Economic Forum and published in the first half of September of each year, with data available at least since To measure the performance of equity markets for countries included in this analysis we are using the MSCI 8 Emerging Markets Index (MSCI EM) and the MSCI Frontier Markets Index (MSCI FM), which are the most widely used international equity indices for institutional investors. 9 MSCI indices are free float-adjusted market capitalization indices with a transparent and public methodology for calculating returns and rebalancing rules. For a single equity to be included in one of these indices, it has to pass strict filters on liquidity, frequency of trading, company size, security size and foreign ownership room. The difference between the MSCI EM and the MSCI FM are the thresholds imposed for these criteria, the efficiency of the operational framework and the stability of the institutional framework. There are no particular economic development criteria between the two indices (for instance, Argentina is part of the MSCI FM index); however the MSCI Developed Index includes countries with Gross Net Income above the World Bank high income threshold for three consecutive years. 10 Specifically, we are using the index that measures the Net Return, which excludes dividends (in US Dollar terms). 6 Each sub-index has more than one pillar that in many cases are also split into several individual categories of indicators Morgan Stanley Capital International. 9 S&P Frontier Markets index data is used only for countries not included in the MSCI indexes. Its construction is similar to the MSCI indices. 10 MSCI Market Classification Framework implies EM and FM composition changes over time. For further details see the Indices section of the MSCI website. 6

7 3. Overview of Investment Climate Indicators, Equity Markets and Macroeconomic performance in Emerging Markets ( ) Despite the 2009 global financial crisis, emerging markets (EM) managed to grow on average a strong 6.2% in the period , while MSCI frontier countries (FM) more affected by the global crisis still grew (o average) at a solid 5.3% rate. These growth rates contrast with the poor performance of developed countries, with growth below 1.6% per year on average and with serious challenges going forward. Before the global financial crisis, both EM and FM countries showed similar growth rates (7.5% on average for years 2004 to 2007). However, while EM average growth declined to 4.1% in , FM average growth reached a meagre 2.3% over these two years. In other words, during the global financial crisis, FM countries significantly underperformed their EM peers despite their positive fiscal and current account balances. The recovery has also been stronger in EM 5.8 vs. 4.4% for FM since While richer countries tend to have a better investment climate, the correlation is stronger with GCI than with DB. When compared with per capita GDP in 2013, GCI 2013 rankings have a 72% negative correlation while DB 2013 rankings have a 59% negative correlation, meaning that DB indicators allow for many developing countries (with lower per capita GDP) to score better than richer countries in terms of the business environment. In any case, there is still a strong positive correlation (84%) between the GCI and DB rankings for Looking at the performance of countries in the DB indicators since 2003 when the first report was published, allow us to differentiate among those countries that have clearly improved their business environment by improving in the Ease of DB ranking, and those that have made it worse by introducing excessive regulation. Rwanda has been the country with the most significant improvement in the rankings since the DB inception in 2003, followed by eight countries in the Europe and Central Asia region. 11 On the other hand, countries that have gone up (worsen) in the rankings the most include Namibia, Kuwait, Argentina, Kenya, Nepal, Venezuela, and most Pacific and Caribbean islands. The number of DB reforms gives a relatively similar picture in terms of which countries have reformed the most since 2003, with countries in Europe and Central Asia among the top reformers again. However, countries like Colombia, Mexico, Vietnam, India, Russia, Egypt and Burkina Faso are also among the top 20 reformers, even if they have not improved significantly on the Ease of 11 These countries are Georgia, Belarus, Ukraine, Albania, Azerbaijan, Macedonia, Kyrgyz Republic, and Kazakhstan 7

8 DB ranking over time. Average GDP growth in doesn t seem to be correlated with the number of DB reforms or the cumulative change in DB rankings when looking at cross-country data. However, this period includes the global financial crisis and the subsequent rebound when the performance of most developing countries was driven more by events in the developed countries than on the domestic reform environment. In many cases, the magnitudes of the GDP growth changes in the period were high enough to drive the average. EM and FM in particular, are quite heterogeneous groups that in their track to catch-up with advanced economies or richer developing countries in terms of growth and development, bring significant profit opportunities to investors. Asset price appreciation and dividend strength for potential equity investments are driven by different forces that can range from massive increase in working age population, increases in general income, discoveries of natural resources, improvements of market and macro structures, progressive reforms or a combination of any of these. The investment strategy proposed in this paper, based on signals from DB and GCI, is an attempt of capturing those factors that should lead to better outcomes as countries develop and improve their investment climate. With regard to global equity markets, EM and FM experienced an almost continued bull market between 2002 and October 2007, increasing by 377 % and 310% respectively. This performance reflects, in part, the rising importance of emerging economies in the global economic activity in particular the so called BRIC countries as well as the strong advance of the Chinese economy during this period and the increase in current account surpluses in most of these countries. From being around one-fifth of the world GDP in the late 1990s, emerging economies accounted in 2007 for less than one-third of world GDP. Besides moving up in the development curve, equity markets in EM, and somehow in FM, benefited also from a higher sophistication of the financial sector of these countries, increased access to foreign investors and growing a domestic investor base. EM equity peaked in October 2007 and FM in February 2008, when investors started to realize that the world economy was about to enter into a sharp slowdown. By February 2009, both indices were down more than 60% from their peak. Interestingly, the performance of EM and FM followed a similar pattern u to 2008, but decoupled thereafter: in 2009 the EM equity index grew by 78%, while the FM equity index only grew 12%. The relatively faster recovery of EM was driven by economies better prepared to cope with a slowdown in developed markets thanks to years of 8

9 prudential macroeconomic and fiscal policies and a strong accumulation of international reserves. The strong economic package to stimulate the Chinese economy and announced at the beginning of 2009, together with the low interest rates in the US facilitated equity investors to return to EM markets. The recovery was not equal among countries and the performance of the MSCI EM index was influenced by the performance of China, Korea and Taiwan which together accounted for approximately 45% of the index. Eastern Europe showed the worst performance and the fact of being less open and liquid helped the performance of low-income countries. Figure 1 Equity Price Performance (Rebased to 100 on Dec 31 st 2002, monthly data from MSCI in USD) However, EM and FM equity markets have not been able to surpass the peak of 2007/2008 and currently trade 13% and 27% below that peak. In the case of EM, equity markets have stayed at a small range since 2011 due to the crisis in Western Europe, the slowdown in commodity prices, the slowdown of the Chinese economy and the expectation of the end of the quantitative easing policy in the United States. Over the past few years, FM begun to attract investor interest as most of their economies have grown and stock exchanges have exhibited a robust performance, particularly in East Asia. Some FM have favorable demographics with large portions of the population entering the work force, are part of a global open market that facilitates integrated trade, benefit from other nations rapid technological advances that can be readily implemented, and are some of the hot destinations for capital looking for high returns. 12 Overall, EM outperformed on a relative basis MSCI FM since However, since early 2011, EM markets have been range bound while FM has consistently trended higher and significantly outperformed EM during See more details in Frontier Markets The Nuts and Bolts of Global Open Market Investing, by Jean-Pierre Lacombe, Facundo Martin, and Rosant Rosantsson Investing in Frontier Markets

10 4. Equity Performance and Investment Climate: A portfolio risk-return optimization approach This section describes in detail the design and performance of the investment strategy based on DB and GCI data. The first step in the analysis is to define an investment universe. In this particular case this corresponds to the group of countries to be included in the portfolio allocation process. Given the purpose of this study we restrict the sample to include only emerging markets equity indices. Ideally, the portfolio should be comprised by countries with an operating stock exchange open to foreign investors and a stock market active enough to make investments in practice. We define emerging active stock markets as those included in the MSCI (mainly) or S&P emerging or frontier markets indices. Thus, the availability of equity market index data somehow dictates our sample selection. In the simulations presented at the end of this section, the investment universe is comprised by 49 countries. Table 1 shows the source of equity index data for the countries included in the investment universe, grouped according to the MSCI s definition of emerging and frontier markets as of December Selected Countries from MSCI Emerging Market Index as of December 2013 Table 1 Investment Universe Selected Countries from MSCI Frontier Market Index as of December 2013 Selected Countries from S&P Frontier Market Index as of December 2013 Brazil Argentina Bangladesh Chile Bulgaria Bosnia and Herzegovina China Croatia Botswana Colombia Estonia Ecuador Egypt Jordan Ghana Hungary Kazakhstan Jamaica India Kenya Macedonia Indonesia Kuwait Saudi Arabia Korea Lebanon Serbia Malaysia Mauritius Trinidad and Tobago Mexico Morocco Venezuela Peru Nigeria Philippines Oman Poland Pakistan Russia Romania South Africa Sri Lanka Thailand Turkey Tunisia Ukraine UAE Vietnam 10

11 Given a defined investable universe, the investment objective for a portfolio manager is typically to outperform a benchmark portfolio or market index. A good benchmark should be publicly available and managed by a third party, and it should be easily replicated by any investor in the market. Furthermore, all investors should be able to calculate and track benchmark returns using publicly accessible data. For the purposes of measuring the relative performance of the investment strategy discussed below, we ll use the MSCI Emerging Markets (EM) Global index as our benchmark. 13 It is important to note that the MSCI EM is a market capitalization weighted index. Thus the BRIC countries (Brazil, Russia, India and China) together, account for more than half of the overall weight. On the other hand, frontier markets are not included in this benchmark. However, if one tries to build a market capitalization benchmark including both emerging and frontier countries, the latter would have less than 5% of the overall weight. 14 Once the benchmark and the investment universe are defined, the next step is to design an investment strategy using the business environment signals coming from both DB and GCI indicators. The investment strategy follows a two-stage process: i. Defining a Starting Portfolio ii. Generating the Investment Portfolio, by under and over-weight individual country allocations in the starting portfolio based on a signal built from DB and GCI indicators Defining a Starting Portfolio Given the existence of a benchmark, one could easily define the starting portfolio to be the same as the benchmark portfolio. While it can be argued that this would make the overall investment strategy a direct deviation from a market portfolio, this also implies that larger countries in the market capitalization weighted benchmark will have a relative advantage within the investment strategy that may be completely uncorrelated with their business environment and reform effort The MSCI Emerging Markets Global Index includes Czech Republic, Greece and Taiwan, in addition to all the countries listed in the first column of table We actually in fact used such a benchmark in some of our simulations, which we don t document in detail but will comment on in this paper. 15 The fact that seven countries account for 75% of the index weight, means that small market cap countries that are improving their business environment it will be very hard to have an impact in the total portfolio return. 11

12 On the other extreme, one could define the starting portfolio to be an equally weighted portfolio where all countries start from the same point. This approach seems fair in the sense of pure deviations towards countries with an improving business environment, and it also increases financial diversification. However, it may also generate distortions when compared to an accepted market benchmark. Thus, in the simulations documented below we use a middle ground approach which reduces the initial over-weight towards large markets, but keeps the potential investment in small markets realistic. We begin with a composite portfolio that includes both emerging and frontier markets from MSCI, and test a starting portfolio that over-weights frontier markets relative to the market capitalization weights through a fixed rule that initially assigns equal weights for countries within four groups (sorted by market size) as follows: 7.5% for the largest markets, which usually include the BRIC countries plus Korea, South Africa and Mexico. These markets account for about 75% of the composite s market capitalization portfolio. 3.0% for each of the countries accounting for the next 20% of the composite s market capitalization portfolio. 1.0% for each of the countries accounting for the next 4% of the composite s market capitalization portfolio. The rest of the weight is allocated equally to the remaining countries. As a result, the starting portfolio will reduce the weight of the seven top countries in the EM-FM composite from around 75% to about 50%. Accordingly, the starting weight of frontier countries is increased to about 17% compared to less than 5% of the overall market capitalization portfolio. Figure 2 compares the weight of the composite market capitalization portfolio and the weight of the starting portfolio, as of year Generating an Investment Portfolio The main goal of the investment portfolio is to adjust the starting portfolio to reflect countries record at improving their business environment based on the signals from both DB and GCI. Countries that have an above-average signal will have a higher weight relative to their initial allocation weight, while countries with below-average signals will end up below their initial allocation weight. 12

13 Figure 2 Market Capitalization Weights and Starting Portfolio as of year 2007 The signal is defined as a weighted average of the following indicators: 16 DB Rank: for this purpose we first re-rank the countries within the investment universe from the original rankings published in the DB report each year. We then invert the ranks, so as to have a higher numerical value for the countries best ranked. DB Change in Rank: given methodological changes and inclusion of new indicators over time, we first generate comparable ranks for each pair of consecutive years ( , , and so on) from the original DB indicators published in the DB report each year, for countries within the investable universe. We then compute the corresponding changes in rank taking into account that going up in the original rank means a relative deterioration in the business environment, and hence a negative change in rank. DB Reforms: these are taken directly from DB report published each year. GCI Rank: we follow the same process as for the DB rank. GCI Change in Rank: we follow the same process as for the DB change in rank, except the revision of the methodological changes from year to year, which we assume not to be significant in the GCI survey. 16 The Employing Workers indicator of Doing Business was excluded from the signal calculation, since the IFC/World Bank has decided to drop it from the overall ranking computation since 2011 due to different interpretations of the results and some controversy in terms of the desirability of a higher or lower level of the indicator. 13

14 The next issue to be resolved is how to weight these indicators into a numerical signal. For this purpose, we run the investment model for about 8,000 portfolios generated by different indicator weightings (for years ) and analyzed the results in the context of a risk-return profile. The goal was to identify efficient weighting structures those that maximize returns under tolerable risk. Figure 3 shows the mapping of annualized excess returns and ex-post tracking errors resulting from these simulations. Figure 3 Risk-Return Profile of DB/GCI Indicators Weighting Combinations What we learned from this analysis was that weighting structures that significantly favored DB over GCI, and significantly over-weighted DB change in rank and DB reforms over DB rank, generated efficient portfolios with high returns. That is, the largest returns without greatly increasing the corresponding volatility. In short, this implies that the investment strategy awards countries with a large reforming effort (reforms) relative to peers (change in rank), and that still have a lot of challenges to overcome in terms of their business environment (low weight on the rank signal). In addition to a transformation where countries with above-average signals have positive deviations, we normalize the signals making sure that the size of the deviation is proportional to the signal strength. This mapping generates an unconstrained portfolio, which is then re-shaped according to certain constraints: i) short positions (i.e. negative weights) are not allowed; ii) maximum country weight caps are imposed in order to guarantee diversified strategies away from corner solutions; and iii) maximum overall risk is monitored and kept under tolerable ranges. 14

15 Investment Portfolio Performance We now discuss the in-sample performance of the investment strategy for the period March 2004 through February In the simulations below, the DB/GCI investment portfolio is rebalanced annually after the publication of the DB and GCI reports, starting the process each year from the updated composite market capitalization portfolio as described above. We start by looking at portfolio differences in terms of country allocations. Figure 4 shows the country allocations of the market capitalization benchmark, our starting portfolio and the final investment portfolio for year While the investment portfolio is over-weighted in large countries such as China and India, it also shows sizable allocations for mid-sized markets like Indonesia, Nigeria and Egypt, while taking important positions in small markets like Mauritius, Tunisia and Ghana. The right portion of the graph shows the larger diversification towards smaller markets, which improved their business environments according to DB and GCI, generating larger diversification opportunities relative to the benchmark portfolio. Figure 4 Country Allocations for Year Benchmark Starting Portfolio Investment Portfolio CHINA BRAZIL KOREA SOUTH AFRICA INDIA RUSSIA MEXICO MALAYSIA INDONESIA TURKEY CHILE KUWAIT THAILAND POLAND PERU EGYPT COLOMBIA UNITED ARAB PHILIPPINES HUNGARY MOROCCO NIGERIA KAZAKHSTAN OMAN JORDAN PAKISTAN CROATIA LEBANON ARGENTINA KENYA VIETNAM ROMANIA MAURITIUS TUNISIA ESTONIA SRI LANKA UKRAINE BULGARIA BANGLADESH BOSNIA BOTSWANA ECUADOR GHANA JAMAICA MACEDONIA SAUDI ARABIA SERBIA TRIN & TOBAGO VENEZUELA We now turn to long term financial performance. Table 2 compares the average monthly returns for the entire period of analysis. While the DB/GCI investment portfolio showed almost twice the average return of the benchmark (MSCI EM Global index), the volatility was lower, resulting in a higher Sharpe ratio when comparing both portfolios directly, and a Sharpe Ratio above 1.0 when 15

16 looking at excess returns. 17 Therefore, the DB/GCI investment strategy for the overall period of analysis performed significantly better than the benchmark. Table 2 Annualized monthly returns March 2004 February 2010 % Annualized monthly average return (Mar/04 - Feb/10) Global MSCI EM DB / GCI based Portfolio Excess Return Average Std Deviation Sharpe Ratio Figure 5 shows the cumulative returns of the investment portfolio relative to the benchmark. An investor following the DB-GCI strategy would have multiplied its capital by almost four times, relative to two times when investing in the benchmark index during the period In addition, we see how the gap between the two increased significantly in the pre-crisis years, contracted during the 2009 crisis, and started widening again from mid-2009 through early Figure 5 Long term performance of the investment portfolio relative to the benchmark Benchmark: Global MSCI EM Index Investment Portfolio Cummulative Return Feb-04 Jun-04 Oct-04 Feb-05 Jun-05 Oct-05 Feb-06 Jun-06 Oct-06 Feb-07 Jun-07 Oct-07 Feb-08 Jun-08 Oct-08 Feb-09 Jun-09 Oct-09 Feb The Sharpe ratio developed by Nobel laureate William F. Sharpe measures risk-adjusted performance, and is calculated by subtracting the benchmark rate from the rate of return for a portfolio and dividing the result by the standard deviation of the portfolio returns. 16

17 As suggested by figure 5, the 2009 global financial crisis, which generated a large market correction across emerging and frontier markets, also implied a change in sentiment across these asset classes. Thus, we decompose cumulative returns to look more closely at short term returns. Table 3 shows the annualized monthly returns for each of the annual portfolios simulated. The results show high and positive excess returns from the investment strategy for years , sizable negative excess returns during the year 2009, and high returns for the first months of the latest portfolio, but with negative excess returns. Table 3 Annualized monthly returns per year % Annualized monthly average return Global MSCI EM DB / GCI based Portfolio Excess Return Mar/ Feb/ Mar/ May/ Jun/ Aug/ Sep/ Aug/ Sep/ Aug/ Sep/ Feb/ In order to understand better the portfolio performance over time, we compared the average returns per year for the groups of countries (by market capitalization size) used to generate the starting portfolio. Figure 6 shows that while for years the largest markets (groups 1-2, which drive the benchmark's performance) had lower average returns than the smaller ones; during the downside/crisis years the largest countries performed better, as heightened global risk aversion during the 2009 crisis over-penalized frontier markets. While these results clearly show that the investment strategy over-performed the MSCI Emerging Markets Index during boom times (years ) and under-performed during the crisis years ( ), we still need to look more broadly at how the strategy performed in recent years. Thus, we re currently in the process of updating the analysis with the latest DB/GCI reports and market performance data, to include out-of-sample performance analysis and global business cycle allocation characteristics before, during, and in the aftermath of the 2009 global financial crisis. 17

18 Figure 6 Average returns by groups of countries defined by market size Finally, we look at the role of the starting portfolio in the performance of the final investment strategy, in order to establish if the over-performance observed relative to the benchmark is really driven by the DB/GCI signal or by the initial over-weight to smaller markets. Figure 7 shows that the cumulative returns of the starting portfolio are slightly higher but similar to those of the benchmark. This implies that the over-performance of the investment portfolio relative to the benchmark for the pre-crisis period is mainly driven by the deviations based on the DB/GCI signal. 18 Figure 7 Cumulative returns of the starting and investment portfolio relative to the benchmark 18 We still need to verify if this fact continues holding beyond year 2008 when we update the overall analysis. 18

19 5. Conclusions and Next Steps This paper develops and tests an investment strategy based on Doing Business and Global Competitiveness Indices in order to validate if investors views about countries future performance, embedded in equity prices, are impacted by new information on countries business environments and reform efforts. So far, the results support the idea that allocations that favor reform efforts, especially from countries that rank low in these surveys, outperform standard equity market benchmarks. The results are particularly strong during the pre-crisis years ( ), and not so strong during the crisis year Therefore, there are several next steps related to this research project: Update the simulations up to year 2013 in order to: i) include more countries, given additional equity index coverage by MSCI and S&P; ii) document the out-of-sample performance of the investment strategy; iii) validate if the results hold in the aftermath of the 2009 global financial crisis; and iv) explain the results when comparing performance across different time periods. Enrich the analysis by documenting the investment strategy performance: i) when using alternative starting portfolios within the investment strategy; ii) when using subsets of indicators within the DB and/or GCI; and iii) when relaxing some of the constraints imposed in the country allocation process. Use regression analysis as a parallel validity test, correlating business environment, reform efforts and market performance, under macroeconomic controls. 19