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Benefits of Diversification in Emerging Markets

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One of the most significant contributions to the investment community has been Markowitz’s modern portfolio theory (MPT) and its foundations in risk return trade-offs and international asset diversification. The growing dependency of Emerging market countries on the US for its stable currency and export sales among other factors has increased their dependence on US markets for their GDP and market growth. This has caused a reduction in the diversification benefits in the Emerging markets. This paper will examine the various empirical evidence on emerging markets diversification and will also construct a portfolio to assess whether investment in these markets still provide benefits.

MPT is based on two key principles of investing, namely that an investor will seek to maximise expected return whilst also minimising risk. Its risk is measured by its standard deviations of returns around expected values. By considering “the expected return of each investment in relation to the impact that it has on the risk of the overall portfolio,” (Litterman (2004) p. 12) An investor can prevent weaknesses in one asset class from reducing the portfolio’s overall return. Therefore a portfolio that is invested in a range of industries or asset classes is more diversified against risks that may affect only one asset class. (Crescenzi (2008) p. 141) The implication is that portfolios are constructed with a rate of return equal to the weighted average rate of return of the holdings and yet its risk will be less than the weighted average return of the portfolio. (Litterman (Ibid) p.14)

Recent developments in Exchange Traded Funds (ETFs) and mutual funds have allowed investors to be invested across a range of markets and countries without being exposed to the potentially large risks of any one internationally traded company. (Crescenzi (Ibid) p.141) More specifically, Index ETF, such as those of iShares, which are designed to closely follow their relevant indices whilst being internationally invested. (Barclays (Ibid) p. 2)

MPT also demands investment in asset classes that correlate as little as possible with each other, as measured by their covariance. In fact, the covariance should be less than one in order to reduce the risk in the portfolio. Asset returns that have covariance equalling one are highly dependent on each other and a covariance of zero means they are independent of each other. Covariance is calculated by multiplying the correlations by the variances of their returns. (Litterman (Ibid) p. 12) A portfolio’s overall risk in relation to its benchmark is measured by its beta. A portfolio with a beta of 1 is has a volatility that is equal to that of its index, whereas a beta greater than one will have greater volatility than the index and is likely to achieve returns greater than the index. It is calculated by dividing a portfolio’s covariance with the index by the index’s variance. (MacKay Shields (2003) p.2)

Mean variance approach

MPT’s mean variance approach demonstrates efficient combinations of high expected returns with a specific level of risk. Any portfolios that exist below the frontier are considered inefficient because they are earning lower returns for the same amount of risk in comparison to those on the frontier. Unfortunately, this is difficult to apply in reality because it requires the use of an optimiser which is based on the calculation of expected returns to arrive at weights. The resulting weights are often considered extreme and inappropriate and the actual calculation of expected returns is also considered difficult to obtain, with the closest and most widely available data being historical returns. Additionally, the approach requires investment in the entire universe of stocks however oftentimes fund managers seek to create portfolios which are invested in a small universe, to attract local investors. (Zimmerman (Ibid) p. 282-262)

Another concern is the models static nature which requires action once the initial allocation of wealth to the securities is made, until the investment horizon is reached. The dynamic nature of stock markets and the wide ranging risks that underline them can greatly impact asset returns, making it crucial for the profitability of an investor to continually rebalance their portfolio according to changes in them. (Korn (1997) p. 12)

Empirical Evidence of Emerging Markets Diversification

There is extensive empirical evidence to support Markowitz’s theory that investment across the globe reduces portfolio risk levels. Cumby and Glen ((1990) cited in Aiello and Chieffe (1999) p. 29) find superior returns are gained by internationally diversified investment funds. Divecha, Drach, and Stefek ((1992) cited in Aiello (Ibid) p. 29) show more specifically that investment in the Emerging markets is likely to reduce a portfolios total risk. Moreover, Masters ((1998) cited in Aiello (Ibid) p. 29) recommend allocate of at least 6 percent in the Emerging markets, to benefit from the rapid economic growth in the region. Speidell and Sappenfield ((1992) Aiello (Ibid) p. 29) maintain that developed countries, unlike emerging markets, move in close tandem with each other and therefore provide less diversification.

A study by Aiello and Chieffe also finds that diversification in the Americas Free Index provides the lowest standard deviation of returns. However, Aiello also notes that the Emerging markets are characterised by high volatility due to asset and sector concentrations, small markets, insider trading and poor information. (Aiello (Ibid) p. 34)

Constructing the Portfolio

Initially a portfolio comprised of solely developed countries will be constructed using index ETFs. iShares Morgan Stanley Country Indices (MSCI) will be used for the purposes of this paper. Initially an assessment of the regional ETF index risk and returns will be made from which individual countries will be selected for investment. A portfolio of developed countries will first be selected followed by a selection of Emerging market countries to assess their impact on the portfolio’s overall risk and return. The period of investment which will be used for the construction of this portfolio will be 2nd January 2009 to 13 March 2009. Unfortunately, access to iShares MSCI data is limited to between 2008 and 2009 for the majority of countries which is insufficient given the significant downturn in the global economy. A time horizon of one year would not highlight the potential benefits, if any, of investing in the Emerging markets. Ideally a two or three year time horizon would be more appropriate.

The above table shows the various Index ETFs by global regions and their corresponding returns, standard deviations, variances and covariance. In comparing the returns it can be seen that the Emerging markets (-8.20%) and Latin America (-3.30%) had the best returns in comparison to Europe (-24.9%) and USA (-18.9%). However, these are also accompanied by high variances relative to developed countries. Covariances between the U.S. and other regions are all under unity and therefore have low dependency in their relationships. The Latin American and Emerging Markets regions proved to have the greatest covariances with the U.S. and therefore have the greatest dependency on American markets for their own performances. This is likely to due to their currencies being pegged to the US dollar and their strong dependency on export sales to the US.

Despite the higher risks associated with investment in the Emerging markets their returns are worthy of investment to diversify a global portfolio. Therefore investment in the Emerging markets will be added to the portfolio. Given the high dependency of Latin American markets on the US, this market will not be included in the portfolio.

Of the developed countries, those with covariances with the US, greater than 0.0007, such as Australia and France will not be included. The remaining countries: US, Canada, UK, Japan and Germany remain for consideration.

The choice of weights invested in the portfolio will depend on their individual risks and returns. The portfolio weights will reflect the risk averse nature of the investor. As can be seen from the table above, Japan and the US have the lowest risk levels but their returns vary greatly being -18.6% and -26.3% respectively. Additionally, the US and UK have similar returns and yet the former has a much lower variance and will not therefore be included in the portfolio. Similarly Germany has a slightly greater risk compared to Canada but with half the return, there is therefore no reason to invest in Germany.

The US and Canada have the highest returns with the US having the lowest standard deviation. It will therefore have a 50 percent weight in the fund leaving Canada 40 percent weight. Whilst Japan has the lowest return it also has the worst return of the three and therefore will have the smallest weight of 10 percent. Since the portfolio is made up of mostly the US index and is not greatly diversified internationally the most appropriate benchmark will be the S&P 500.

The portfolio return for the year to date comes to -16.7%, calculated by summing the weights of each country index multiplied by their returns, thereby outperforming the index by less than 3%. The portfolio beta is 1.01, calculated by dividing the portfolio covariance with the index, by the variance of the S&P500. The portfolio beta being marginally greater than unity implies it is slightly more volatile in comparison to the index, due in large part to the Japanese weighting.

Investing in the Emerging Markets

Given that the Emerging markets have been shown empirically to provide greater diversification benefits and are recommended by the MPT this region will also be considered for investment.

Choosing a set of Emerging market index ETFs will begin by taking out those with the highest covariances with the S&P 500, namely South Korea and South Africa. Taiwan has the strongest return with a risk level, as measured by its variance and standard deviation, close to that of Hong Kong and Singapore. It will therefore have a high weight in the Emerging Markets portion of the fund. Singapore’s returns is the lowest with an almost equal risk level to the other countries, therefore it will not be considered for investment. Malaysia whilst it has a slightly lower return does have the lowest risk level. This is likely to be due to its much more developed stock market and more stable political environment and will help to diversify the region’s risk level in the portfolio. The remaining countries are Taiwan, Hong Kong and Malaysia.

In considering weight allocations countries with low standard deviations, such as Malaysia (50%) will be given greatest weight. Taiwan and Hong Kong have only slightly differing variances but very different returns and therefore their weights, 10% and 40% respectively, will reflect Taiwan’s greater return. The combined return of these three countries is -6.8% which against the MSCI Emerging Markets Index, outperformed by 1.4%. Their combined beta is 0.60, half the volatility of the index. Moreover, its covariance with the S&P 500 is only 0.00051, making it very independent of the US market.

Given the positive returns, low risk and low dependency on the US market, the Emerging markets will be given a weight of 30% in the original developed countries portfolio. This improves the original portfolio return from -17% to -2% which against the S&P 500 benchmark, outperforms by over 16%, during one of the most tumultuous market downturns in recent history. Although the standard deviation of the new internationally diversified portfolio is the same, its beta is 0.90 and covariance is 0.0006 making it very independent of the US market.

Ongoingly investors must assess the risk and return of any of the country index ETFs that he or she is invested in, rebalancing the portfolio accordingly. Factors such as political unrest, financial fraud, poor macroeconomic management and manufacturing can all greatly increase country risks and reduce their returns.

Conclusion

This paper set out to assess whether the Emerging markets still have diversification benefits on a portfolio’s return and risk levels. The various empirical literature examined in the paper conclude that the Emerging markets do still add to portfolio diversification. The portfolio that was constructed also demonstrates the added benefits of investing in these markets to its performance.

Some of the limitations of this paper include the relatively short time frame chosen for the model portfolio. A period of two to three years would have been more ideal. Middle Eastern ETF representations were limited to only Israel and Turkey and therefore did not provide a reasonable representation of Emerging markets in the Middle East.

Bibliography
Aiello, S. and Chieffe, N. (1999) International index funds and the investment portfolio Financial Services Review 8, p. 27–35
Barclays Global Investors (2009) An Introduction to iShares: Exchange Traded Funds, www.ishares.com
Barclays Global Investors, (March 2009) iShares Products http://us.ishares.com/content/stream.jsp?url=/content/repository/material/product_expense_ratio_report.pdf&mimeType=application/pdf
Crescenzi, A. (2008) Investing From the Top Down: A Macro Approach to Capital Markets, McGraw-Hill Professional
Korn, R. (1997) Optimal portfolios: stochastic models for optimal investment and risk management in continuous time, World Scientific
Litterman, B. (2004) Modern Investment Management: An Equilibrium Approach, Quantitative Resources Group, John Wiley and Sons
MacKay Shields (2003) Managed Accounts: Modern PortfolioTheory, MacKay Shields Investment Management LLC
Zimmermann, H., Drobetz, W. and Oertmann, P. (2003) Global Asset Allocation: New Methods and Applications, John Wiley and Sons
iShare ticker symbols and index information sourced from iShares.com
Historical prices from which data was calculated was sourced from yahoo.com/finance

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