Naturally, large excess returns of EM debt reported in the previous section stem from various risk premia, to which the emerging market sovereigns are exposed. Excess returns include a risk premium as compensation for credit risk inherent in sovereign debt. Furthermore, investors might require a premium for currency depreciation risk and various types of liquidity risk such as flight to quality episodes following a negative market sentiment. Therefore in this section, we attempt to analyze the exposition of EM bond portfolios to these risk premia by regressing the excess returns of EM sovereign local and foreign currency-denominated bond portfolios on excess returns of various the US equity and bond market portfolios.
Table 13 reports the regression results of excess returns of sovereign local currency bond port-folios (converted to US Dollars) on the three Fama-French Factors, and the excess returns on:
five-year US Treasury bonds, US corporate investment grade and high-yield bond indices by Bar-clay’s Capital, detailed explanation of which is provided in the Data section of this paper. In line with the findings on determinants of yields, regression results of local currency bond excess returns
show that the US market factors do not have significant explanatory powers for majority of the countries. In particular, 9 sovereigns have significant coefficients for weighted US equity market index by Fama-French, 6 have significant coefficients for investment grade bond index, and 2 have significant coefficients for US Treasury index. While all of the alphas are positive, 7 of them are significant, which might be an indicator of some important omitted variables explaining the varia-tions in the excess returns. The mean alpha of 16 countries adds up to 0.58 per month. Average alpha is high when we think of the average monthly excess returns is only 0.75(Table 11). For the portfolio of all the local currency bonds of all of the 16 EM sovereigns (GBI-EM Composite), only US equity market and investment grade bond index have significant coefficients, while its alpha is significantly positive and R-squared is 52%.
Table 14 reports the regression results of excess returns of sovereign dollar-denominated bond portfolios on the excess returns of the US market factors. The results suggest that US market factors explain a larger variation in the excess returns of foreign currency bonds. Mainly, the US corporate investment grade bond, US Treasury bond and the US equity market index excess returns explain a large part of deviation in the dollar-denominated bond excess returns. R-Squareds are high with an average of 64%, ranging from 29% for Brazil to 84% for Malaysia. Although all of 16 sovereigns have positive alphas, only one of these is significant, which suggests that the model does relatively well explaining the variations in the excess returns. US equity market, Treasury, investment grade and high-yield bond indices have all significant explanatory powers on the portfolio of 32 emerging market dollar-denominated bond indices (EMBI Global). Furthermore, the R-squared of the regression of EMBI global is as high as 82%. Thus, after controlling for global risk factors as proxied by U.S. equity and bond market excess returns, there is little or no evidence of an individual risk premium, which makes it more difficult to diversify away the risk. In other words, the positive mean excess return from taking sovereign dollar-denominated bond positions appears to be, to a large part, compensation for bearing the risk of global factors that drive sovereign spreads;
a diversified portfolio of the US stock and bond positions reproduces a substantial portion of the historic excess returns in the sovereign dollar-denominated debt market.
Emerging market local currency-denominated bond excess returns show little dependence on US market factors comparing to the case for dollar-denominated bond excess returns. At a first glance, an analysis comparing the large portfolios of all the bonds of all the countries suggests a
significant difference in the reliance of two EM bond markets to the global market. While 4 of 6 US market variables have significant explanatory power on dollar-denominated portfolio; in explaining the local-currency denominated portfolio, only the US equity market variable has a significant beta coefficient. Furthermore, the R-Squared of foreign currency-denominated large portfolio is 82%, which is 50% larger than that of local currency-denominated large bond portfolio.
5 Conclusion
Emerging market sovereign debt has become a firmly established strategic asset class. Besides dollar-denominated debt, local currency emerging market debt has also been developing to become an attractive and complementary investment to traditional fixed income instruments. EM countries have been successful to reduce currency mismatches and maturity problems by implementing sound fiscal and monetary policies, which in return allowed them to extend the maturity of their borrowings denominated in local currency. While many EM governments have been improve their debt structure by developing local-currency bond markets, international investors are watching more closely at local markets in search for higher yield and greater diversification. In our paper, therefore, we try to answer the question whether EM local-currency bond markets diversification benefits provide higher risk adjusted excess returns . This issue has become even exceptionally relevant as the correlations between asset-returns have drastically increased due the recent financial turmoil.
Analyzing the period from 2002 to July 2009, we show that the local currency debt provides significant additional alpha and diversification to traditional bond portfolios. In particular, first, EM local currency bond returns are less correlated to the US stock market, treasury and high-yield bond markets and global risk premia comparing to the a case of emerging market equity and dollar-denominated bond markets. Contrary to the literature suggesting a low correlation between the equity markets in developed countries, EM equity markets are highly correlated and possibly largely affected by global factors such as variation in credit risk premia, market liquidity and trading movements of international investors. On the other hand, local-currency bonds reflect significant lower correlations, which signals that the effects of various country specific factors such as political risk, inflation and exchange rate expectations predominates when determining the returns.
In order to analyze the common factors that cause the correlation between the returns of EM
assets, we perform a principal component analysis. The results indicate that there is a significant amount of commonality in the returns of EM asset classes. However, this commonality is the least in the local-currency bond and money market returns. We see that the first principal component cap-tures 37% of the variation in the correlation matrix of local-currency bond returns. This percentage rises to 49% and 54% for EM foreign currency denominated bond and equity market returns.
Furthermore, we document that yields and excess returns on local currency debt depend largely on expected depreciation of the exchange rate, while excess returns on foreign currency denominated debt are for the most part compensation for bearing the global risk. As a novelty in this literature, we use the weekly percentage change in forward rates of exchange rates against USD as a proxy for the change in the depreciation expectations. By definition, EM local currency bond holders bear an additional risk comparing to dollar-denominated bond holders, i.e. currency risk. In particular, unlike local currency bonds, dollar-denominated bond yields are affected heavily by global financial market performance. This is an important result as it suggests while local-currency bond yields largely move along with exchange rate expectations, dollar-denominated bond yields reflect the changes in the global financial market conditions and risk premia.
Last but not the least, we report that EM sovereign local currency bond returns beat other emerging market and traditional investment classes by providing higher annual and long term risk adjusted excess returns, providing added alpha and diversification to bond portfolios. Consistent with the previous sections, emerging market local-currency denominated bond excess returns show little dependence on excess returns of US market factors comparing to the case for foreign currency bond excess returns.
In summary, we argue that local currency bond returns are determined primarily by idiosyn-cratic or country-specific factors, which allows standard portfolio diversification methods to manage sovereign local currency bond portfolios. Indeed, our results suggest that there exists a large country specific premium in the local-currency bond returns even after controlling for global risk factors.
These country specific premia might stem from various country specific factors such as political risk, inflation and exchange rate expectations. On the other hand, after controlling for global risk factors as proxied by the US equity and bond market excess returns, there is little or no evidence of an individual risk premium in the dollar-denominated bond returns, which makes it more difficult to diversify away the risk. In other words, the positive mean excess return from taking sovereign
dollar-denominated bond positions appears to be, to a large part, compensation for bearing the risk of global factors that drive sovereign spreads; a diversified portfolio of US stock and bond positions reproduces a substantial portion of the historic excess returns in the sovereign debt market.
We believe that our results will have important policy implications not only for market par-ticipants but also for the governments and the international institutions. We suggest that the development of local currency bond markets in EM countries could contribute to global financial stability by reducing reliance on foreign currency debt and currency mismatches, which in turn is linked to growth and poverty reduction.
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Table 1: Maturity of domestic central government debt outstanding. Average original and remaining maturity in years Government debt outstanding includes bonds, notes and money market instruments. Regional totals based on the countries listed in the table and weighted by the corresponding amounts outstanding. Asia larger economies and total emerging markets exclude China for all periods. These estimates should be regarded as indicative and may not be strictly comparable across countries. Industrial countries consist of Australia, Belgium, Canada, Germany, Spain, the United Kingdom and the United States.
2002 2003 2004 2005 2006 2007 2008
Original Remaining Orig. Remain. Orig. Remain. Orig. Remain. Orig. Remain. Orig. Remain. Orig. Remain.
Argentina ... ... 1 0.7 1.3 1 1.1 12 17 11 16.5 10.3 16.7 10.6
Brazil ... 2.9 ... 2.7 ... 2.4 ... 2.3 ... 2.6 ... 3 ... 3.3
Chile 5.6 13 7.6 5.4 7.2 6.9 8.4 6.7 5.6 7.8 7.8 6.8 10.2 9.2
Colombia 6.4 4.5 6.5 4.2 6.8 4.1 6.8 3.8 7.5 3.9 7.7 4.1 8.2 4.4
Czech Rep. 7.3 5.2 7.9 5.7 8.5 6 8.6 5.7 9.3 6.3 8.5 5.6 9.3 5.8
Hungary ... 3.7 ... 4 ... 4.1 ... 4.1 ... 4 6.8 4 7.1 3.8
India 14 8 14 9 15 10 14 10 16.9 10 14.7 10 14.9 10.6
Indonesia 13.1 7.6 7.8 7.8 7.9 8.4 7.6 7.6 11.5 7.1 13.3 12.7 4.8 4.1
Korea 5.4 3.7 5.5 3.7 5.8 4 6.1 4.1 6.6 4.2 7 4.4 7.5 4.5
Malaysia ... 4 ... 5 ... 5 8.6 5 8.4 5.2 10 5.4 9.7 5.3
Mexico ... 2.3 ... 2.5 ... 3 ... 3.4 ... 4.3 ... 5.7 ... 6.5
Peru 2.5 1.2 3.3 2.1 6.5 5.5 11 9.9 13.9 12.2 18.5 16.5 19.4 16.6
Philippines 7.1 4.2 7 4.2 7 3.9 7.2 4.1 7.9 4.7 7.8 5 8.1 4.9
South Africa 17.4 8.9 16.6 8.2 15.4 8.2 16 8.1 16.8 8.3 17.3 8.3 18.3 9.9
Poland 4.3 2.7 4.4 2.7 5.4 3.2 6.2 3.6 6.9 3.9 8 4.3 8.6 4.2
Russia 3.8 1.7 5.6 4.1 10.8 8.9 11.1 8.6 11.9 9 12.9 9.7 13.4 9.7
Thailand 9.4 ... 8.5 6 8.7 6 8.6 5.6 8.8 5.4 9.7 5.8 10.2 5.8
Turkey 3.2 2.4 2.9 1.9 2.8 1.6 3.3 1.8 3.5 1.9 3.8 1.1 3.9 1.9
Industrial Count. 9.9 5.2 10 5 10.2 4.9 10.4 5.9 10.6 5 10.9 5.4 11 5
Central Europe 4.8 3.3 5.1 3.5 6 3.8 6.6 4 7.4 4.3 7.8 4.4 8.4 4.4
Asia, L. Econs. 10.9 7 10.6 7.1 10.7 7.3 10.1 7 11.2 6.9 10.9 7.1 11.5 7.6
Latin America 5.5 2.8 2.6 2.5 3.4 2.7 3.5 3.9 13.7 4 13.6 4.4 14 4.9
Total EM‘s 9.4 5.1 8.1 4.8 8.4 4.9 8.2 5 9.9 5.1 9.9 5.2 10.2 5.5
Source: BIS Working Group Survey
26
Table 2: Descriptive Statistics and first order serial correlations for JP Morgan GBI-EM Broad Index. This table reports summary statistics for week-end percentage total US-dollar returns for JP Morgan GBI-EM Broad Bond Indeces for emerging market sovereigns.
Mean Std Dev. Minimum Maximum Obs. Serial Corr.
Argentina -0.11 6.49 -29.97 20.62 107 0.196
Brazil 0.33 2.64 -13.33 10.26 393 0.111
Chile 0.24 1.75 -10.01 6.16 350 -0.023
China 0.15 0.62 -4.73 3.18 289 -0.045
Colombia 0.36 2.36 -10.26 10.11 341 -0.038
Egypt 0.14 1.55 -6.84 5.46 93 0.242
Hungary 0.26 2.86 -17.79 12.06 393 -0.015
Indonesia 0.29 3.22 -25.58 24.63 341 0.037
Malaysia 0.09 0.79 -3.36 3.74 393 0.045
Mexico 0.11 1.94 -9.30 12.07 393 0.012
Peru 0.24 2.02 -6.86 14.48 145 0.074
Poland 0.23 2.38 -14.35 10.73 393 -0.124
Russia 0.05 1.57 -10.37 8.08 232 0.010
South Africa 0.34 3.11 -16.67 13.01 393 -0.052
Thailand 0.18 1.09 -3.87 3.94 393 0.178
Turkey 0.34 2.89 -15.18 9.93 276 0.050
Gbi-Em Composite 0.23 1.10 -4.78 5.31 393 0.023
Gbi-Em Europe 0.26 2.19 -12.22 10.16 393 -0.068
Gbi-Em Latin America 0.33 2.80 -16.36 21.00 393 -0.017
Gbi-Em Mid E/Afr 0.22 1.76 -10.57 7.00 393 0.009
Gbi-Em Asia 0.16 0.62 -2.38 3.09 393 0.156
Table 3: Descriptive Statistics for JP Morgan EMBI Global Index.This table reports sum-mary statistics for week-end percentage total returns for JP Morgan EMBI Global Bond Indeces for emerg-ing market sovereigns.
Mean Std Dev. Minimum Maximum Obs. Serial Corr.
Argentina 0.12 3.81 -22.09 19.28 393 0.075
Brazil 0.30 2.29 -15.58 10.24 393 0.080
Chile 0.14 0.89 -4.06 2.95 393 -0.006
China 0.12 0.80 -5.64 4.87 393 0.102
Colombia 0.21 1.49 -5.90 10.70 393 0.079
Egypt 0.16 0.57 -2.01 2.88 393 0.020
Hungary 0.08 1.47 -16.66 10.52 393 0.078
Indonesia 0.23 2.92 -15.36 31.56 267 0.015
Malaysia 0.15 0.98 -8.84 5.74 393 -0.038
Mexico 0.16 1.13 -7.40 6.80 393 0.188
Peru 0.21 1.60 -7.70 13.13 393 0.055
Poland 0.13 0.92 -5.51 5.39 393 0.162
Russia 0.23 1.69 -10.50 17.36 393 -0.015
South Africa 0.16 1.15 -8.25 10.15 393 0.106
Thailand 0.11 0.47 -1.23 1.84 222 0.031
Turkey 0.25 2.07 -10.83 20.73 393 -0.010
EmbiG Composite 0.20 1.34 -7.08 12.83 393 0.094
EmbiG Europe 0.22 1.60 -10.34 18.10 393 0.006
EmbiG Latin America 0.21 1.03 -9.35 6.30 393 0.076
EmbiG Middle East 0.20 1.49 -7.61 9.78 393 0.124
EmbiG Asia 0.17 1.29 27 -7.97 15.60 393 0.007
Table 4: Correlation Matrix of Weekly Returns in GBI-EM Index of Sovereigns. This table reports the pairwise correlation coefficients for weekly percentage returns in the local currency GBI-EM Broad Bond Indices converted to US Dollars.
Argentina Brazil Chile China Colombia Egypt Hungary Indonesia Malaysia Mexico Peru Poland Russia S.Africa Thailand Turkey
Argentina 1
Brazil 0.47 1
Chile 0.26 0.24 1
China -0.02 -0.05 -0.01 1
Colombia 0.37 0.48 0.29 -0.01 1
Egypt 0.31 0.3 0.26 -0.14 0.23 1
Hungary 0.37 0.27 0.06 0.02 0.35 0.18 1
Indonesia 0.43 0.36 0.21 0.04 0.38 0.34 0.4 1
Malaysia 0.23 0.25 0.1 0.17 0.33 0.07 0.39 0.41 1
Mexico 0.36 0.45 0.27 0.05 0.38 0.22 0.43 0.38 0.22 1
Peru 0.34 0.49 0.26 0.02 0.5 0.23 0.43 0.54 0.29 0.56 1
Poland 0.41 0.32 0.11 0.07 0.35 0.06 0.8 0.4 0.45 0.42 0.46 1
Russia 0.24 0.34 -0.03 0.1 0.26 0.09 0.64 0.24 0.35 0.4 0.25 0.64 1
S.Africa 0.3 0.24 0.07 0.04 0.29 0.17 0.53 0.31 0.33 0.32 0.46 0.53 0.41 1
Thailand 0.1 0.18 0.18 0.11 0.17 -0.05 0.29 0.33 0.42 0.19 0.23 0.31 0.2 0.23 1
Turkey 0.41 0.58 0.12 0.05 0.48 0.23 0.67 0.45 0.45 0.6 0.51 0.62 0.37 0.66 0.29 1
Source: JP Morgan, Datastream
Table 5: Correlation Matrix of Weekly Returns in EMBI Global Index for sovereigns. This table reports the pairwise correlation coefficients for weekly percentage returns in the EMBI Global Indices.
Argentina Brazil Chile China Colombia Egypt Hungary Indonesia Malaysia Mexico Peru Poland Russia S.Africa Thailand Turkey
Argentina 1
Brazil 0.42 1
Chile 0.22 0.36 1
China 0.13 0.15 0.74 1
Colombia 0.52 0.66 0.3 0.21 1
Egypt 0.24 0.34 0.33 0.35 0.34 1
Hungary 0.34 0.15 0.41 0.38 0.27 0.14 1
Indonesia 0.59 0.67 0.4 0.28 0.76 0.2 0.47 1
Malaysia 0.26 0.23 0.81 0.86 0.29 0.36 0.38 0.43 1
Mexico 0.49 0.61 0.5 0.4 0.68 0.33 0.45 0.68 0.44 1
Peru 0.46 0.68 0.34 0.29 0.76 0.41 0.27 0.71 0.36 0.65 1
Poland 0.15 0.15 0.66 0.8 0.16 0.33 0.4 0.03 0.73 0.38 0.21 1
Russia 0.52 0.53 0.42 0.39 0.63 0.34 0.44 0.83 0.49 0.68 0.66 0.26 1
S.Africa 0.45 0.37 0.58 0.53 0.57 0.34 0.55 0.79 0.65 0.7 0.59 0.44 0.76 1
Thailand 0.04 -0.06 0.66 0.78 0.04 0.27 0.55 0.24 0.72 0.39 0 0.58 0.26 0.57 1
Turkey 0.49 0.55 0.35 0.28 0.62 0.27 0.36 0.85 0.37 0.61 0.62 0.18 0.74 0.67 0.07 1
Source: JP Morgan, Datastream
28
Table 6: Correlation Matrix of Weekly Returns in Gbi-Em Composite, Embi Global Composite, Elmi+ Compos-ite, Msci-Em ComposCompos-ite, S&P 500 ComposCompos-ite, Merrill Lynch US Corporate High Yield and Barclays Capital US Corporate Investment Grade Indeces and the current 5 year US Treasury Bond.
Local Dollar Money Equity S&P500 US Trsy High Yield Inv Grade
Local Curr. 1
Dollar Curr. 0.6 1
Money Mkt 0.89 0.62 1
Equity Mkt 0.67 0.61 0.72 1
S&P500 0.38 0.31 0.42 0.63 1
US Trsy 5-Year 0.03 0.13 -0.03 -0.25 -0.38 1
High Yield 0.37 0.58 0.37 0.52 0.4 -0.14 1
Inv Grade 0.23 0.44 0.17 0.07 -0.12 0.67 0.42 1
Source: JP Morgan, Merrill Lynch, Datastream
29
Table 7: Principal Component Analysis. This table presents the results for the principal component analysis (pca) of the correlation matrix of weekly percentage returns of local currency denominated bond indices(Gbi-Em), USD denominated bond indices (Embi Global), local currency money market indices (Elmi+) and equity market indices (Msci) for emerging market countries in our sample. All observations section presents the results of the pca analysis using the pairwise correlation matrix calculated by using all the observations available. Overlapping observations section reports the pca analysis using the correlation matrix calculated by using the sample period for which the data is available for all sovereigns.
All Observations Overlapping Observations
All Observations Overlapping Observations