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The recent media spotlight on exchange-traded funds has helped fuel debate on the enduring question regarding the benefits of active and passive investment
management. Often, however, the focus of this debate is overly broad, such as looking only at large-cap U.S. funds or looking at all funds across all market categories.
This paper takes a more detailed and practical approach, trying to determine if either an active or passive approach is advantageous for specific investment categories.
The study also identifies investment categories that have historically provided positive exotic beta. Allocating a portion of an investor’s portfolio to investment categories that provide
positive exotic beta provides the potential for increased portfolio returns and the opportunity to reduce the level of risk in a portfolio through additional diversification.
Study Overview
We analyzed the historical performance of over 16,000 actively managed mutual funds in 58 categories representing over $7 trillion of assets. Returns were analyzed net of management
fees and other expenses. Complete study results and methodology are provided in the appendices.
Mutual funds were analyzed for the 3-, 5-, 10- and 15-year trailing periods from April 1992 to March 2007.
The study sought to identify:
• Investment categories in which active managers provided value through their unique investment management capabilities in excess of the category’s index movement (asset-weighted)
• Investment categories that have generated excess returns through risk premiums not correlated to the broad markets (asset-weighted)
• The percentage of managers in each investment category
which outperformed their respective category benchmarks (nonasset-weighted)
Methodology
Alpha is a portfolio measure of the difference between actual returns and expected performance, given a level of risk as measured by beta.
Portfolio return = alpha + beta * (market risk component)
In other words, alpha is the excess return, on a risk-adjusted
basis, that active fund managers generate over and above their benchmark. The volatility of the residual returns is its active risk. A positive alpha figure indicates better performance
than beta would predict. In contrast, a negative alpha indicates underperformance, given the expectations established
by the beta. It is generally believed that positive alpha is easier to find in less-efficient markets, while capturing alpha is very difficult in larger and more liquid asset classes.
Alpha can be used to directly measure the value added or subtracted by a manager. Alpha depends on two factors:
1) the assumption that market risk, as measured by beta, is the only risk measure necessary, and 2) the strength of the linear relationship between the portfolio and the benchmark, as it has been measured by R-squared.
In addition, a negative alpha can sometimes result from the expenses that are present in the returns of a manager, but not in the returns of the comparison index.
Beta measures the sensitivity of a portfolio relative to the market; a portfolio with a beta of 1 will exactly track the market.
Exotic Beta
The concept of exotic beta was first introduced into the hedge fund world. Exotic beta refers to a premium associated with a particular asset class exposure. Some studies suggest that hedge fund returns are composed of three portions: traditional
beta, exotic beta and real alpha.
Portfolio return = real alpha + exotic beta * (particular asset class risk component) + traditional beta * (market risk component)
Traditional beta refers to the return derived from exposure to traditional stock or bond markets, while exotic beta refers to the return derived from exposure to other systematic risk factors (such as credit risk, liquidity risk, volatility risk) common
to each family of hedge fund strategies.
Real Alpha
Real Alpha is the additional return truly stemming from the unique ability and skill set of the hedge fund manager. It is the active alpha that can be ported onto completely unrelated betas. Real alpha measures the manager skill.
Recent academic analysis suggests that only a small fraction
of hedge fund returns are actually accounted for by real alpha.
The main sources of returns are the risk premium derived from exotic betas. Roger Ibbotson and Peng Chen’s study “The A,B,Cs of Hedge Funds” (2006) suggests that, during
the time period from January 1995 through April 2006, on average, hedge funds have generated an alpha of 3.04 percent and returns from the betas of 5.94 percent. The 3.04 percent alpha measured here is traditional alpha, which includes the returns from exotic betas. Real alpha is hard to find and expensive to access, while exotic beta is relatively easy to find and cheap to get.
In this study, we applied the concepts of real alpha and exotic beta to the mutual fund world. We calculated the best-fit alpha and traditional alpha of funds in each asset category.
We believe the best-fit alpha represents the real alpha, and the difference between the best-fit alpha and traditional alpha reflects the return derived from the exotic beta embedded
within each asset category.
Exotic beta is an important source of return, and also provides the benefit of diversification. Measuring each asset category’s exotic beta can help optimize a portfolio’s
tactical asset allocation.
Regression Analysis
Mathematically, alpha is a regression coefficient. In calculating, we deducted the return of the three-month T-bill from the total return of both the portfolio and benchmark. Thus, the alpha figures
shown here may be lower than those published elsewhere.
We believe that this calculation represents the fact that every investor has choices about where to place his or her money.
Traditional alpha was calculated by Morningstar for each portfolio,
using a standard set of benchmarks for each asset group. In the United States, Morningstar uses the following benchmarks for alpha statistics: S&P 500 Index for U.S. stock portfolios, MSCI EAFE for international stock portfolios, Lehman Brothers Aggregate Bond for taxable bond portfolios, and Lehman Brothers Muni for municipal bond portfolios.
Best-fit alphas are calculated using the market index that shows the highest correlation (R-squared) between a portfolio and an index over the most-recent certain time periods based on the best-fit R-squared. The indexes that were regressed against portfolios in calculations are shown in Figure 1.
Next, we calculated the exotic beta.
Since,
Portfolio return = traditional alpha + traditional beta * (broad market index risk component);
Portfolio return = best-fit alpha + best-fit beta * (best-fit index risk component);
And,
Portfolio return = best-fit alpha + exotic beta * (particular asset class risk component) + traditional beta * (broad market risk component)
Then,
Return from exotic beta
= exotic beta * (particular asset class risk component)
= best-fit beta * (best-fit index risk component) – traditional beta * (broad market index risk component)
= traditional alpha – best-fit alpha
Therefore, return from exotic beta is the difference between traditional alpha and best-fit alpha.
Figure 1
Figure 2
Source: FundQuest
Figure 3
Source: FundQuest
Figure 4
Source: FundQuest
Figure 5
Source: FundQuest
Figure 6
Source: FundQuest
Figure 7
Source: FundQuest
Actionable Conclusions
Real Alpha
We recommend using active managers for investment categories
deemed to have consistently generated positive “real alpha” through manager skill. Specifically, we suggest an active approach if the investment category generated positive real alpha over at least three of the four time periods in the study, and if the real alpha for the fourth time period (if applicable) was determined
to be neutral.
Conversely, we recommend a passive approach for investment
categories that have underperformed for at least three of the four time periods of the study, and if the real alpha for the fourth time period (if applicable) was determined to be neutral.
Investment categories that fall outside of these two definitions
are considered to have performed in line with their style benchmarks, and either active or passive management could be appropriate. In addition, investment categories were assessed as neutral if historical data was not available for at least three of the four time periods of the study.
An investment category was considered to have generated
positive real alpha if its asset-weighted real alpha exceeded +0.5 percent for the time period. If the asset-weighted average real alpha was below -0.5 percent, we consider the category to have underperformed for the time period. If the asset-weighted average real alpha fell between +0.5 percent and -0.5 percent, we consider the category neutral.
Figure 8
Percentage Of Active Managers Outperforming
Based on the asset-weighted average measurement, actively managed mutual funds in certain categories held an advantage to passive indexes, although only a portion of active managers actually outperformed their benchmark indexes. This table highlights which categories of active managers outperformed their benchmarks over different time periods.
Source: FundQuest
Exotic Beta
In terms of exotic beta, a category was considered to have consistently provided a specific risk premium on top of broad market returns if its asset-weighted average exotic beta was above +0.5 percent for at least three of the four time periods of the study, and if the exotic beta for the fourth time period (if applicable) was determined to be neutral (between +0.5 percent and -0.5 percent). We recommend an overweighting of these categories
which are more likely to obtain above-market returns.
Similarly, if the asset-weighted average exotic beta was below -0.5 percent for at least three of the four time periods of the study, we consider the category to have generated fewer premiums than broad market returns. We recommend an underweighting of these categories which are less likely to obtain above-market returns.
Investment categories that fall outside of these two definitions
are considered neutral. In addition, investment categories were assessed as neutral if historical data was not available for at least three of the four time periods of the study.
Risk premiums vary by investment category. For example, mutual funds in an international bond category may provide a specific risk premium derived from a lack of liquidity, political instability or currency changes.
Percentage Of Actively Managed Mutual Funds Within Each Category Which Outperformed Their Respective Category Benchmarks.
This nonasset-weighted analysis examined the number of mutual funds that outperformed their benchmarks considering
the four time periods noted previously. In some instances the results differed from the asset-weighted analysis as the size of the fund was not a factor in the results. This helps differentiate how many funds outperformed
versus how much of an investment category’s assets outperformed the category benchmark.
Results Of Analysis
We found that, based on the industry average, after adjusting
for expenses, active managers performed in line with both the broad market indexes and their best-fit benchmarks over time. Within the general universe, the study found no meaningful difference between active and passive investing approaches. This finding supports the hypothesis that markets
are generally efficient and that it is difficult for active managers to outperform the markets consistently.
However, when we look closer into each mutual fund investment category, the results are mixed. In some categories,
active managers consistently outperformed their benchmarks over various time periods, while in other categories active managers consistently underperformed. In other words, both active and passive investments had strengths and weaknesses. Utilizing active managers might be more favorable than passive in certain categories, but less favorable in others. This conclusion is consistent with the findings of our previous studies.
We also found that, although most categories performed
in line with the broad markets over the long run, some categories, such as Bank Loan, Emerging Markets Bond, High Yield Bonds, Small Value, Mid Blend and Long-Short, generated positive exotic beta consistently over
different time periods.
Based on the results of this study, Figure 3 provides a recommendation on whether an active or passive approach is advantageous for each mutual fund category. In addition, it provides tactical allocation recommendations that may be used during the portfolio construction process. Figure 3 also provides an assessment as to how many actively managed funds consistently outperformed their category benchmarks.
Mutual Funds By Category
Figure 3 is a summary of suggestions. For instance, the Bank Loan category is read as “active,” “overweight,” and “Between 50-74 percent.” That is to say, first, actively managed Bank Loan mutual funds generally held an advantage over passive indexes in this category. If only one position is selected from this category, actively managed funds might be better candidates than passive index funds or ETFs. Second, the Bank Loan category has historically
outperformed the broad bond market by adding exotic beta returns, thus overweighting this category in a tactical asset allocation
may enhance portfolio performance against the broad markets.
Finally, between 50-74 percent of active Bank Loan mutual funds actually outperformed their benchmarks.
More granular results can be found in the Figures 4–8.
Conclusion
While the debate between the merits of active and passive management is likely to continue, this study offers practical and actionable information, providing insight into the level of success/failure for actively versus passively managed mutual funds in discrete market categories. Within the general universe,
the study found no meaningful difference between active and passive investing approaches. However, once the universe was broken down into distinct categories, there were significant performance differences.
The general theme was that more-efficient categories were more favorable to passive investing while less-efficient (meaning
smaller or less heavily researched) categories showed benefits from active management. There were a number of exceptions to this theme, though, and the explanations for those variations are not within the scope of this paper.
The analysis of exotic beta identified categories that may enhance a portfolio’s overall performance compared to the broad markets. The general theme was that more-exotic (less correlated to traditional stock and bond investments) categories
were more likely to outperform the broad markets.
It is important to note that, even in a category where active managers have historically underperformed their benchmarks,
there are managers generating positive real alpha. It is in these categories where more comprehensive research and analysis is critical to uncover this subset of managers.
Overall, this study can be used as a reference tool for portfolio construction and as a potential indicator for which investment categories may be the most appropriate for selecting active or passive investment strategies.
The authors, Jane Li and Ruhan Inanoglu, are both Chartered Financial Analysts and work in the investment management group at FundQuest Incorporated.
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