Global Emerging Markets Equity
Global Emerging Markets Equity funds’ performance varies significantly across the category, with the best 5% of the funds in the universe outperforming the market (pegged to MSCI Emerging Market Index) by approximately 22% and the worst 5% underperforming by approximately 16% over the last 52 weeks (ending October 1, 2010).What role do favourable style allocations […]
Global Emerging Markets Equity funds’ performance varies significantly across the category, with the best 5% of the funds in the universe outperforming the market (pegged to MSCI Emerging Market Index) by approximately 22% and the worst 5% underperforming by approximately 16% over the last 52 weeks (ending October 1, 2010).What role do favourable style allocations play? We take a closer look at common factors describing the best and worst funds on an aggregate basis. When funds are aggregated in a group, their common factors crystallize and specific bets are diversified away, which provides the basis for such an analysis. Our analysis suggests that the top- and bottom-performing funds, on average, invested in quite different emerging market segments which impacted their performance. While top-performing funds benefited most exclusively from stock selection, the worst performers were negatively impacted by having high exposure to cash and bonds, and limited exposure to favourable emerging market segments. Using an attribution framework, we were able to quantify the impact of each bet on the overall performance. Please note that our conclusions may change if a different timeframe is used to select the best/worst funds. Click here to download the PDF.
– Although funds in the defined universe are classified as Global Emerging Market funds, a brief review of the strategies and prospectuses reveal that some funds have significant holdings in cash, cash equivalents and firms in developed markets (such as USA and Europe).
– Analysis of the universe (297 funds) suggests that many of the funds have large exposures to cash and bonds. While the worst performing funds appear to have the largest exposure to cash and bonds.
– In terms of region and capitalization average exposure over the past 12 months, the funds in the universe cover the entire equity style space; however, there is higher exposure to Large Cap Asia and EMEA (as shown in the chart below).
Selection of Top/Bottom Fund Groups
– Based on the universe of 297 funds, the total annualized performance is calculated during the last 52 weeks to rank the funds. Using the top 5% (15 funds) and bottom 5% (17 funds) equally weighted, daily rebalanced portfolios are created to try to understand why, on average, one group performed better in terms of style exposures.
Returns-Based Style Analysis Highlights
– As shown below, the top 5% of funds outperform its peers, benchmark and bottom 5%. Over the analysis period, the top 5% group returns approximately 22% above the MSCI Emerging Markets index while the bottom 5% group returns 16% below the index.
– The style map (see chart below) and asset loadings provide insight into how the top and bottom performers differ. The funds are mostly exposed to large to mid-cap equities within different regions, particularly in Emerging EMEA and Emerging Asia. The style map shows a trend in exposures over time while the asset loadings chart illustrates average exposures for the period.
– As shown in the asset loadings chart below, the top 5% of funds are exposed to all regions of the MSCI Emerging Markets index with varying proportions. On the contrary, the bottom 5% of funds made bets away from the benchmark with allocations to developed markets (such as USA and Europe). These funds also kept, on average, large amounts of cash and bond positions, or potentially hedged their exposures. Exposures to most emerging segments are also smaller than the exposures for the benchmark.
– The allocation decisions are reflected by a slight positive (almost negligible) timing effect with the majority of excess performance due to good selection picks for the top 5%. The bottom 5% display negative selection and timing effects—with timing displaying the largest negative effect. Please refer to chart on the next page.
– The top funds’ overexposure (vs. the benchmark) to Small-to-Mid Cap segment of EM EMEA and Latin America had a positive contribution (which was partially offset by the negative impact from a small cash exposure) and resulted in the overall positive timing effect. At the same time, the bottom funds’ allocation decisions resulted in under-exposure to all emerging regions, except for EMEA Smid and Asia Large, and, more importantly, to significant over-exposure to cash, EM bonds and US equities which led to considerable underperformance vs. the benchmark.
– As expected, the diversification effects of blending a large number of funds together in an equally-weighted portfolio results in very high explanatory power of the analysis with R-Squared values in the mid 90s for the top 5% and mid 70s for the bottom 5%. As a group, the top 5% displays strong selection skills whereas the bottom 5% displays negative selection and timing. Selection and timing returns represent components of excess benchmark performance.
Rolling Risk/Return Analysis: Consistent Behaviours
– The chart below illustrates that over the period of analysis, the top (bottom) 5% consistently outperformed (underperformed) the benchmark on a 12-week rolling return basis. This over (under) performance accounts to the 21.77% (-16.27%) return in excess over (under) the benchmark during this period.
– The top 5% display risk in line with the benchmark, as defined by the 12-week rolling standard deviation. The bottom 5% has much lower risk which reflects high exposure to cash and bonds. The top 5% of managers have been adept at limiting risk while generating significant returns in excess of the benchmark, on a cumulative and rolling basis.
– On a risk-adjusted basis and comparing the funds with the Capital Market Line (see following chart), the top 5% portfolio provides a higher return per unit of risk than the benchmark. The bottom 5% appears to be properly priced in this manner.
- Database provider: Lipper, a Thomson Reuters Company
- Registered for sale countries: Austria, France, Germany, Italy, Netherlands, Offshore, Spain, Sweden, Switzerland, and the UK
- Filters: share class, at least 1 year of performance history, Asset Type: Equity, Geographical Focus: Global, Lipper Global Category: Emerging Markets, AUM: minimum EUR 10 Million
- Number of funds analyzed: 297
- Date interval: Last 52 weeks starting on October 5, 2009 and ending on October 1, 2010
- Currency: Euro
- Analysis Frequency: Weekly (with compounded daily data)
- Cash proxy (Risk Free Rate): EONIA Index
- Benchmark: MSCI Emerging Markets
- Style factors: BarCap Global Emerging Markets, MSCI USA, MSCI Europe, MSCI EM Asia Large, MSCI EM Asia Smid, MSCI EM Latin America Large, MSCI EM Latin America Smid, MSCI EM EMEA Large, MSCI EM EMEA Smid
- Analysis performed with mpi Stylus Pro™
Style Return: Return of the Best Fit Portfolio for the Manager Series, where the holdings of the portfolio are the Style Indices.
Selection Return: Calculated as the Manager’s Return subtracted by the Style Return. This is an indication of the Manager’s Selection or Stock Picking abilities.
Timing Return: Calculated as the Manager’s Style Return subtracted by the Benchmark’s Style Return. This indicates whether the Manager’s decisions, to over or under weight the style holdings, as compared to the benchmark, added to the portfolio’s return or not.
Style R Squared (R2): Measure of the model’s power in describing the Manager’s past behaviour in terms of style. The higher the Style R Squared value, the better the model’s explanatory power.
Predicted Style R Squared (PR2): Measure of the model’s power in predicting the Manager’s future behaviour in terms of style. The higher the Predicted Style R Squared value, the better the model’s predictive power.
Style Map: Graphic representation of the results of the Style Analysis. The series being analyzed are mapped unto a Cartesian plane, in which the X and Y axis represent exposures to different Styles and Sizes.
Asset Loadings: Weights of the Style Indices, as holdings, of the Style Portfolio, as calculated by mpi Stylus Pro.
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