Markov Processes International

Asia Pacific ex Japan–USD & EUR Denominated Share Classes

MPI_Research

Asia Pacific ex Japan equity funds’ performance ranges from -0.59% to 40.34% over the last 52 weeks (ending February 25, 2010), in USD terms. The best 5% of the funds outperform the market (pegged to the MSCI AC Asia Pacific ex Japan) by approximately 11.9% and the worst 5% underperform by approximately 14.4%. What role do favourable style allocations play? We examine style/capitalization and country 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, had focused on the same countries in the region, albeit with somewhat different levels of exposures. The top funds outperformed through selecting better performing stocks within those countries, which is reflected in their positive Selection return; on the other hand, the bottom group displayed negative Selection, implying that although they were invested in the same countries as the top funds, their intra-country stock selection hindered their performance. Both groups of funds are mostly exposed to Cash, Hong Kong and Singapore, loadings that represent close to 52% of the top funds exposure and 58% of the bottom funds exposure. Using an attribution framework, the impact of each bet on the overall performance is quantified. 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.

Universe Overview – RBSA Analysis

– The universe is comprised of 201 funds that are classified under Lipper Global: Equity Asia Pacific ex Japan, with AUM of at least EUR 10 million and denominated in EUR and USD. Our analysis takes into account the performance of the Primary Share Class, as defined by Lipper.

– Using a 26 week centered, rolling window, we run Returns Based Style Analysis using mpi Stylus Pro to estimate the average exposures over the last 52 weeks ending on February 25, 2011.

– RBSA average exposures to the different countries that make up the MSCI AC Asia Pacific ex Japan index shows that the funds in the universe invest across all the countries in the region[1], together with an exposure to Cash of around 7.2%. The top 5% of funds display a higher Cash exposure, approximately equal to 17.8%, while the bottom 5% have an exposure of close to 13%. These estimated exposures to cash can be validated by reviewing the latest factsheets for the funds that make up each of the top and bottom portfolios.

– In terms of Style-Capitalization factors, one can see that the funds behave similarly, with the funds being exposed to a blend of mid caps with a value tilt, which is more pronounced for the bottom funds. It is worth noting that that the top and bottom funds behave very differently than the benchmark, which is a blend of large caps, as well as behaving differently than the majority of their peer group.

Chart 1: Style-Capitalization Map

Selection of Top/Bottom Fund Groups

–  Based on the universe of 201 funds, the total annualized performance is calculated during the last 52 weeks to rank the funds. Using the top 5% (11 funds) and bottom 5% (12 funds) equally weighted, daily rebalanced portfolios are created to try to identify why, on average, one group performed better in terms of style exposures. – Unsurprisingly, the top 5% of funds outperform its peers, benchmark and bottom 5%. Over the analysis period, the top 5% group returns approximately 11.9% above the MSCI AC Asia Pacific ex Japan Index while the bottom 5% group returns 14.42% below the index.

Chart 2: Cumulative Performance Chart

Returns-Based Style Analysis Highlights

– Using country market indices as factors, our RBSA analysis demonstrates that the top and bottom 5% funds’ are making more concentrated country bets since their top 5 exposures represent, respectively, 71% and 83% of the funds’ behaviour. In comparison, the Peer Group average is more diversified, with the 5 largest exposures representing about 61% of the peer group performance.

– The diversification effects of blending a large number of funds together in an equally-weighted portfolio result in high explanatory power with R-Squared values of close to 83% for the top 5% and 78% bottom 5%. This allows us to have a sufficient level of trust in the points and conclusions we have made in this analysis.

– The top funds’ performance is mostly explained by their exposure to (from largest to smallest): Singapore, Cash, Hong Kong, Malaysia, and Taiwan. The bottom funds’ are best explained by: Singapore, Hong Kong, Cash, China, and India.

– Cash exposures for both groups of funds are significant, 17.8% for the top funds and 13.3% for the bottom funds. This average exposure does not display the dynamics of the portfolio’s behaviour over the past year. Over the past 6 months there was a steady increase in Cash exposures, reaching their highest level (close to 30%) around early November 2010. The exposure has since then leveled off to show a year-to-date estimated value of 23.5% and 20.5% for the top and bottom funds, respectively. This helped both portfolios avoid larger losses stemming from year to date losses in the countries’ in which they invest. Losses in these markets range from 1% (Malaysia) to over 15% (India).  Among the worst performers that affected the top and bottom funds’ performance YTD are: Indonesia (-5.72), Singapore (-4.47), Thailand (-4.41), and China (-3.93).

– The bottom funds’ exposure to India increased over the past 52 weeks, reaching its highest of approximately 19% in the last 8 weeks ended on February 25th. The bottom 5% overweight in India, versus the benchmark, during this period hurt them as this country index dropped by over 15%, year to date. The top funds’ were not as exposed to losses in this country, as their exposure was limited to about 4% of their overall loadings.

– It also worth highlighting the fact that neither the top nor bottom funds are exposed to Australia, which makes up for a large portion of the MSCI AC Asia Pacific ex Japan Index, as well as for the overall Peer Group average.

Chart 3: Average Asset Loadings – Country factors

– Although the top and bottom funds have average exposures to the same countries, albeit in different proportions, their performance is vastly different. This allows one to conclude that the top funds excelled in selecting better performing stocks within each country, with the bottom funds selecting poor performers. This can be translated as positive selection returns for the top funds and negative selection returns for the bottom funds.- Interestingly, the notable differences in country exposures of the top and bottom funds’ vs. the benchmark did not translate in significant positive timing returns. The effects of differentiation for the top funds had negligible positive effects on the portfolio’s overall performance, while it was markedly negative for the bottom funds. Although both groups of funds tend to over- and under-weight the same countries, their timing returns are completely different. This is because timing returns are the result of the dynamics of a fund’s exposure to the different Style indices over the total period of analysis. It takes into account the weights in excess of the benchmark at each point in time, which are different than the overall average displayed in the chart above. This means that the top (bottom) funds may have overweighted (underweighted) one country at the right (wrong) time, but in average their weights are estimated to be the same.

Chart 4: Timing and Selection Returns

– Style attribution analysis can explain which factors best describe the funds’ performance. The sum total of the factor returns is approximately equal to the funds’ style return, which represents the funds’ expected performance had the managers followed a passive approach. The difference between the managers’ actual return and the style return is the selection return, which can be explained as the active return generated by the managers’ intra-country stock selections, which can be positive or negative.

Chart 5: Style Attribution Analysis

– The top 5% style return is estimated to be 13.75%, which is below their total return of 32.52%. The difference of 18.77% is the selection return. The bottom 5% would have been better off following a passive approach, as their stylus return is estimated to be 15.81%, which is higher than the 6.2% actual return experienced by the fund. This provides for a negative 9.61% selection return.

Conclusions

Both groups of funds’ style exposures are similar, having many of their top country loadings in common. It is the managers’ abilities to select the better stocks within those countries that differentiate the top 5% funds from the bottom 5%. Over- and under-weight exposures to certain countries versus the benchmark did not generate significant timing returns for the top funds, but generated negative timing returns for the bottom funds. This stresses the need of selecting managers with proven knowledge of each of the countries in which they invest.

UNIVERSE DEFINITIONS & ASSUMPTIONS

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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Markov Processes International, LLC (MPI) is a global provider of investment research and technology solutions. MPI’s analytical tools and methodologies are employed by the finest institutions and financial services organizations to enhance their investment research, reporting, data integration and content distribution. MPI offers the most advanced platform available to analyze hedge funds, mutual funds, portfolios and other investment products, as well as asset allocation and portfolio optimization tools. MPI’s Stylus Pro software is utilized by alternative research groups, hedge fund of funds, family offices, institutional investors, consultants, private banks, asset managers, diversified financial services organizations as well as marketing, product development and IT departments around the world. MPI also offers solutions for investment advisors and private wealth professionals. For more information on past MPI research articles visit http://markovprocesses.com/company/research.htm

[1] The MSCI AC Asia Pacific ex Japan Index is made up equities in the following countries: Australia, China, Hong Kong, India, Indonesia, Korea, Malaysia, New Zealand, Philippines, Singapore, Taiwan, and Thailand.
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