Practical Applications of Active and Passive Investment ...

Practical Applications of Active and Passive Investment Management:

Examining Real Alpha and Exotic Beta

Jane Li, CFA Ruhan Inanoglu October 2007

Practical Applications of Active and Passive Investment Management: Examining Real Alpha and Exotic Beta

2 FundQuest White Paper

Introduction

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. This paper will assess the two methods of investment management to determine if either proves a better method. This research provides practical insight regarding allocation weightings and an assessment to determine if either an active or passive approach is advantageous for specific investment categories. The paper also provides tactical allocation recommendations that may be utilized in portfolio construction. While FundQuest has previously examined the benefits of active and passive investment management, our 2007 analysis has been expanded and enhanced while still utilizing the fundamental methodology of our previous studies. A summary of the differences between the two studies, including changes in the results, is provided as Appendix 1. FundQuest has built a family of funds and a mutual fund investment program based on this research. A version of this paper was published in the Journal of Indexes in the March/April 2008 issue. Active portfolio managers believe they can outperform their benchmark or index, or “beat” the market. They believe there are certain inefficiencies in the market that can be taken advantage of to achieve potentially higher returns than that of a benchmark or index. They use available qualitative and quantitative information and employ forecasting techniques and proprietary models for research.

Active Management Benefits

Active Management Challenges

Expert analysis of experienced investment professionals

Higher fees and operating expenses

Upside potential - the possibility of achieving returns higher than those of the index.

Poor security selection or sector allocation decisions may impact returns

Downside protection - managers may act defensively during market downturns and periods of market uncertainty.

Investment philosophy or process that is out of favor may result in lower returns.

Passive or Index portfolio managers believe that the market is inherently efficient and that it is difficult to beat the market. They offer a portfolio that represents a broad-based index with the aim of providing performance closely representing that of the index (low tracking error).

Passive Management

Benefits Passive Management

Challenges Generally lower management expenses Investors cannot expect to exceed index

returns Generally no decision making required by the manager

No ability to provide downside protection

© FundQuest Incorporated 2007 V2101507



Study Overview I. Investments Analyzed. 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.

II. Time Period. Mutual funds were analyzed for the 3, 5, 10, and 15-year trailing

periods from April 1992 to March 2007. III. Framework of Analysis. The study sought to identify:

o Investment categories in which active managers provided value through their unique investment management capabilities in excess of the category’s index movement (asset weighted)

o Investment categories that have generated excess returns through risk

premiums not correlated to the broad markets (asset weighted)

o The percentage of managers in each investment category which outperformed their respective category benchmarks (non-asset weighted)

To identify these categories, the study focused on:

o 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.

Real Alpha is the additional return truly stemming from the unique ability and skill set of the investment manager.



An investment category was considered to have generated positive Real Alpha if its asset-weighted Real Alpha exceeded +0.5% for the time period. If the asset-weighted average Real Alpha was below -0.5%, we consider the category to have underperformed for the time period. If the asset-weighted average Real Alpha fell between +0.5% and -0.5%, we consider the category neutral. Real Alpha differs from Alpha (referred to here as Traditional Alpha) in that Traditional Alpha measures each investment’s relative performance compared to the broad market indices such as the S&P 500, MSCI EAFE and Lehman Brothers Aggregate Bond whereas Real Alpha measures each investment’s relative performance compared to its best fit or category benchmark. Traditional Alpha can come from two sources: manager skill (as measured by Real Alpha) and category specific risk premium captured by managers (as measured by Exotic Beta).

o 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% 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% and -0.5%). 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% 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. Exotic Beta is an important source of return which also provides the benefit of diversification. Measuring each investment category’s Exotic Beta can help optimize a portfolio’s tactical asset allocation. 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 premiums derived from Exotic Beta.

Exotic Beta is used to identify investment categories that may generate extra returns through risk premiums not directly correlated to the broad markets.



o Percentage of actively managed mutual funds within each category

which outperformed their respective category benchmarks.

This non-asset 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 covering fund expenses, active managers performed in line with both the broad market indices 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.

Actively Managed Mutual Funds For periods ending March 31, 2007

3 Year 5 Year 10 Year 15 Year

Asset Weighted Traditional Alpha -0.18 0.30 0.73 0.24 Asset Weighted Real Alpha -0.18 -0.52 -0.14 -0.37 Asset Weighted Exotic Beta 0.00 0.82 0.87 0.62 Asset Weighted Expenses 0.90 0.93 0.92 0.81 Number of Active Funds 16,316 12,891 6,512 2,214

Source: FundQuest 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, the table below 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. The table also provides an assessment as to how many actively managed funds consistently outperformed their category benchmarks.



How to Read the Table The table is a summary of suggestions. For instance, the Bank Loan category is read as “active,” “overweight,” and “Between 50-74%”. That is to say, first, actively managed Bank Loan mutual funds generally held an advantage over passive indices 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 overweighing this category in a tactical asset allocation may enhance portfolio performance against the broad markets. Finally, between 50-74% of active Bank Loan mutual funds actually outperformed their benchmarks.

Mutual Fund Recommendations by Investment Category

Morningstar Category

Active vs. Passive

Recommendation based on Real

Alpha

Tactical Allocation

Recommendation based on Exotic

Beta

Percentage range of actively managed mutual funds in

category which outperformed category benchmarks*

Bank Loan Active Overweight Between 50-74% Bear Market Passive Neutral Between 0-24% Conservative Allocation Active Overweight Between 25-49%

Convertibles Neutral Underweight Between 25-49%

Diversified Emerging Mkts Active Neutral Between 75-100% Diversified Pacific/Asia Active Neutral Between 50-74% Emerging Markets Bond Neutral Overweight Between 50-74% Europe Stock Active Neutral Between 25-49% Foreign Large Blend Neutral Neutral Between 0-24% Foreign Large Growth Passive Neutral Between 0-24% Foreign Large Value Neutral Neutral Between 50-74% Foreign Small/Mid Growth Active Neutral Between 75-100% Foreign Small/Mid Value Neutral Neutral Between 50-74% High Yield Bond Passive Overweight Between 0-24% High Yield Muni Neutral Neutral Between 75-100% Inflation-Protected Bond Neutral Neutral Between 25-49% Intermediate Government Passive Neutral Between 0-24% Intermediate-Term Bond Neutral Neutral Between 0-24% Japan Stock Neutral Neutral Between 25-49% Large Blend Neutral Neutral Between 0-24% Large Growth Passive Neutral Between 0-24%

* The “percentage range of actively managed mutual funds in a category which outperformed category benchmarks” is the average of the data for time periods with available historical data.



Mutual Fund Recommendations by Investment Category (continued)

Morningstar Category

Active vs. Passive

Recommendation based on Real

Alpha

Tactical Allocation

Recommendation based on Exotic

Beta

Percentage range of actively managed mutual funds in

category which outperformed category benchmarks

Large Value Neutral Overweight Between 0-24% Latin America Stock Active Overweight Between 75-100% Long Government Neutral Neutral Between 0-24% Long-Short Neutral Overweight Between 50-74% Long-Term Bond Passive Neutral Between 0-24% Mid-Cap Blend Neutral Overweight Between 25-49%

Mid-Cap Growth Passive Neutral Between 25-49%

Mid-Cap Value Neutral Overweight Between 25-49%

Moderate Allocation Neutral Neutral Between 0-24% Multisector Bond Neutral Overweight Between 25-49% Muni National Interm Neutral Neutral Between 0-24% Muni National Long Neutral Neutral Between 0-24% Muni National Short Passive Neutral Between 0-24% Muni Single State Interm Passive Neutral Between 0-24% Muni Single State Long Passive Neutral Between 0-24% Muni Single State Short Passive Neutral Between 0-24% Pacific/Asia ex-Japan Stk Active Underweight Between 75-100% Short Government Neutral Neutral Between 0-24% Short-Term Bond Neutral Neutral Between 0-24% Small Blend Active Neutral Between 25-49%

Small Growth Neutral Neutral Between 25-49%

Small Value Active Overweight Between 25-49% Specialty-Communications Active Underweight Between 50-74% Specialty-Financial Neutral Overweight Between 25-49% Specialty-Health Active Neutral Between 50-74% Specialty-Natural Res Neutral Neutral Between 50-74% Specialty-Precious Metals Active Neutral Between 75-100% Specialty-Real Estate Neutral Overweight Between 25-49% Specialty-Technology Passive Neutral Between 0-24% Specialty-Utilities Neutral Overweight Between 75-100% Target-Date 2000-2014 Neutral Neutral Between 25-49% Target-Date 2015-2029 Neutral Neutral Between 0-24% Target-Date 2030+ Neutral Neutral Between 0-24% Ultrashort Bond Neutral Neutral Between 0-24% World Allocation Active Neutral Between 75-100% World Bond Neutral Neutral Between 25-49% World Stock Active Underweight Between 50-74%

Source: FundQuest



Conclusion While the debate between the merits of active and passive management is likely to continue for the foreseeable future, this study offers practical and actionable information, providing insight into the level of success/failure for actively versus passively managed mutual funds. 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 when 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. Index and benchmark performance information is presented for comparison purposes only and does not represent the actual performance of any specific investment product or portfolio. Fees and expenses are not included in the performance of an index. An investment cannot be made directly into an index. Past performance is not indicative of future results. An individual investors’ situation can vary. Therefore, the information presented in this document should be relied upon only when coordinated with individual professional advice.

Appendices

Appendix 1: Summary of Differences Between 2006 and 2007 Studies Appendix 2: Methodology and Complete Results Appendix 3: Indexes Regressed Against Portfolios (Mutual Funds)



Appendix 1 Summary of Differences 2006 and 2007 Studies While FundQuest previously examined the benefits of active and passive investment management, our 2007 analysis was expanded while still utilizing the fundamental methodology of our previous studies. As with our 2006 study, the new analysis provided recommendations about whether an active or passive investment approach proved advantageous for specific mutual fund investment categories. However, the 2007 study provided additional findings that advisors may find useful during the portfolio construction and security selection processes. Specifically, Exotic Beta was used to identify investment categories that may generate excess returns through risk premiums not correlated to the broad markets. In addition, the study provided an analysis of the percentage of mutual funds in each investment category which outperformed their respective category benchmarks. We strived to obtain the historical data of each fund’s assets over the past 15 years as well as each fund’s assets under management as of March 31, 2007. When calculating the asset weighted category average of each statistic, we used each fund’s assets at the beginning of each time period. Changes in Active v. Passive Assessment from 2006 to 2007 Our 2007 study showed that, based on the industry average, after covering fund expenses, actively managed funds have performed in line with both the broad market indices and their best fit benchmarks over time. However, when we look closer into each investment category, the results were mixed. In some categories, actively managed funds consistently outperformed their benchmarks over various time periods, while in other categories, active managers consistently underperformed. In other words, both active and passive investments have strengths and weakness. Utilizing active managers might be more favorable than passive in certain categories, but less favorable in other categories. This conclusion is consistent with the findings of our previous studies.

At the same time, the study provided differences in findings. For example, actively managed mutual funds in the large growth and long term bond categories outperformed in the 2006 analysis, but underperformed in this study. On the other hand, active managers in the large value and short government bond categories underperformed in the 2006 analysis, but performed in line with their best fit benchmarks in this study. Compared to previous studies, there are more categories that performed in line with their best fit benchmarks, and fewer categories that outperformed. These changes may be due to the much longer time horizon of the 2007 study as well as the emphasis on consistency.

2006 vs. 2007 Results

Active v. Passive

Recommendations by Mutual Fund Investment Category 2006

Results 2007

Results Active -- Number of Investment Categories in which Active Mutual Funds Outperformed their benchmarks

31 15

Passive -- Number of Investment Categories in which Active Mutual Funds Underperformed their benchmarks ̀

9 12

Neutral -- Number of Investment Categories in which Active Mutual Funds performed in line with their benchmarks

23 31

Total 63 58*

* The 2007 study excluded state-specific municipal bond fund categories as they achieved very similar results to the municipal single state categories.



Appendix 2 Methodology and Complete Results Investments Analyzed: Over 16,000 actively managed U.S. domiciled mutual funds in 58

categories representing over $7 trillion of assets. Funds included in the study had a minimum of a 3-year history in the Morningstar database.

Time Period: April 1992 to March 2007. Every fund’s behavior pattern and performance

was analyzed for four time periods, the 3, 5, 10 and 15-year trailing periods ending March 31, 2007.

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. 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 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. Traditional alpha is the combination of real alpha and exotic beta. 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% and returns from the betas of 5.94%. The 3.04% alpha measured here is traditional alpha, which includes the returns from exotic betas. 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. Real alpha is hard to find and expensive to access, while exotic beta is relatively easy 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, as well as providing the benefit of diversification. Measuring each asset category’s exotic beta can help optimize a portfolio’s tactical asset allocation.

Mathematically, Alpha is a regression coefficient. In calculating, we deducted the return of the 3-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.

Let, be the return of a portfolio in month t be the risk-free return (or defined by user) in month t be the return of a benchmark index in month t be the simple (monthly) mean return of a portfolio

be the simple (monthly) risk-free mean return be the simple (monthly) benchmark index mean return be the number of time months

Suppose that,

Then, Jensen’s Alpha can be calculated by,

Annualized Jensen’s Alpha can be calculated by,



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 indices that were regressed against portfolios in calculations are shown in Appendix 3. 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.

Detailed Results The tables on the following pages provide details of each aspect of the study not included in the main section of the study. Real Alpha The following tables highlight investment categories which have (1) consistently generated over +0.5 Real Alpha, (2) consistently generated under -0.5 Real Alpha , or (3) consistently generated neither positive nor negative Real Alpha, for the 3, 5, 10, and 15-year trailing periods ending March 31, 2007. The results show that 15 investment categories have consistently generated positive Real Alpha, 12 categories have consistently generated below -0.5 Real Alpha, and 31 categories consistently generated neither positive nor negative Real Alpha. Investment categories were assessed as neutral, or to have consistently generated neither positive nor negative Real Alpha, if historical data was not available for at least three of the four time periods of the study.



Mutual Fund Investment Categories Consistently Generating over +0.5 Real Alpha For the trailing periods ending March 31, 2007

Morningstar Category 3 Year 5 Year 10 Year 15 Year

Bank Loan 1.44 0.78 0.54 0.71 Conservative Allocation 0.00 0.64 1.25 0.92 Diversified Emerging Mkts 3.64 5.09 2.55 2.39 Diversified Pacific/Asia 0.57 1.94 0.90 2.88 Europe Stock 0.50 0.94 0.54 0.33 Foreign Small/Mid Growth 0.78 5.14 6.98 4.39 Latin America Stock 3.99 3.76 2.95 1.64 Pacific/Asia ex-Japan Stk 5.37 5.55 6.15 3.82 Small Blend 1.11 0.10 0.50 0.84 Small Value 1.54 0.72 0.92 1.43 Specialty-Communications 3.26 6.14 3.48 1.61 Specialty-Health 3.01 3.12 3.67 1.96 Specialty-Precious Metals 8.78 17.85 6.04 6.74 World Allocation 1.68 3.71 5.40 5.18 World Stock -0.11 1.56 3.95 4.52

Mutual Fund Investment Categories Consistently Generating Below -0.5 Real Alpha For the trailing periods ending March 31, 2007


Bear Market -4.12 -3.02 -3.28 -2.44 Foreign Large Growth -1.78 -1.45 -2.34 -3.31 High Yield Bond -0.65 -1.98 -1.92 -1.47 Intermediate Government -0.51 -0.42 -0.63 -0.78 Large Growth -0.85 -1.29 -0.62 -0.52 Long-Term Bond 0.00 -0.79 -1.01 -0.90 Mid-Cap Growth 0.09 -1.45 -0.54 -0.53 Muni National Short -0.69 -0.34 -0.53 -0.51 Muni Single State Interm -0.86 -0.71 -0.78 -0.69 Muni Single State Long -0.51 -0.56 -0.84 -0.64 Muni Single State Short -0.71 -0.90 -0.91 -1.01 Specialty-Technology -3.27 -2.02 -7.04 -3.77



Mutual Fund Investment Categories

Which Have Consistently Generated Neither Positive nor Negative Real Alpha For the trailing periods ending March 31, 2007


Convertibles 0.78 -0.30 0.55 0.32 Emerging Markets Bond 7.70 2.46 -2.26 N/A Foreign Large Blend -1.22 -1.01 -0.13 0.96 Foreign Large Value -0.36 0.56 1.27 -1.11 Foreign Small/Mid Value 3.75 2.50 -5.09 -2.75 High Yield Muni 1.83 N/A N/A N/A Inflation-Protected Bond 0.22 0.88 -1.12 -0.69 Intermediate-Term Bond -0.04 -0.18 -0.15 -0.12 Japan Stock -3.66 -0.09 3.28 2.51 Large Blend -0.76 -0.88 -0.20 -0.20 Large Value 0.00 -1.34 -0.81 -0.39 Long Government -0.36 -0.22 -0.26 -0.29 Long-Short -1.35 0.42 2.28 2.80 Mid-Cap Blend 0.47 0.03 0.40 0.97 Mid-Cap Value 1.33 -3.02 -1.61 -1.25 Moderate Allocation -0.49 0.06 0.21 0.06 Multisector Bond 0.84 0.95 -0.13 -0.28 Muni National Interm -0.43 -0.43 -0.60 -0.53 Muni National Long -0.14 -0.26 -0.73 -0.68 Short Government -0.55 -0.38 -0.43 -0.38 Short-Term Bond -0.15 -0.19 -0.09 -0.08 Small Growth 0.18 -0.24 0.86 1.25 Specialty-Financial -1.08 0.30 -1.15 -0.29 Specialty-Natural Res -0.76 3.83 5.43 6.23 Specialty-Real Estate 0.60 4.22 0.16 -1.46 Specialty-Utilities 7.91 4.36 -2.80 -9.61 Target-Date 2000-2014 -0.87 -1.15 -0.09 0.68 Target-Date 2015-2029 -0.62 1.24 0.05 N/A Target-Date 2030+ -0.11 1.07 -0.39 N/A Ultrashort Bond -0.56 -0.22 0.07 -0.33 World Bond 0.59 0.82 0.09 0.01



Exotic Beta The following tables highlight investment categories which have (1) consistently generated over +0.5 Exotic Beta, (2) consistently generated under -0.5 Exotic Beta, or (3) consistently generated neither positive nor negative Exotic Beta, for the 3, 5, 10, and 15-year trailing periods ending March 31, 2007. The results show that 14 investment categories have consistently generated positive Exotic Beta, 4 categories have consistently generated below -0.5 Exotic Beta, and 40 categories which have consistently generated neither positive nor negative Exotic Beta. 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.

Mutual Fund Investment Categories Which Have Consistently Generated Over +0.5 Exotic Beta

For the trailing periods ending March 31, 2007

Morningstar Category 3 Year 5 Year 10 Year 15 Year Bank Loan 0.33 2.08 0.76 0.89 Conservative Allocation 0.71 -0.26 0.74 1.02 Emerging Markets Bond 1.73 7.63 10.55 N/A High Yield Bond 5.00 8.15 3.56 3.95 Large Value 1.97 3.18 2.69 2.34 Latin America Stock 3.75 4.52 3.94 2.88 Long-Short 0.66 0.86 0.53 0.28 Mid-Cap Blend 0.91 5.00 4.48 2.42 Mid-Cap Value 1.42 7.87 6.43 4.92 Multisector Bond 2.11 3.35 0.96 1.58 Small Value -0.32 5.93 5.40 1.45 Specialty-Financial 0.54 2.42 4.20 4.36 Specialty-Real Estate 8.85 12.44 9.75 9.78 Specialty-Utilities 7.23 4.28 7.87 12.96

Mutual Fund Investment Categories Which Have Consistently Generated Below -0.5 Exotic Beta

For the trailing periods ending March 31, 2007

Morningstar Category 3 Year 5 Year 10 year 15 Year Convertibles -3.64 -1.47 -1.14 -0.83 Pacific/Asia ex-Japan Stk -4.90 -1.28 -5.93 -2.42 Specialty-Communications -2.55 -1.69 -2.03 -2.95 World Stock -2.08 -4.62 -1.35 -0.62



Mutual Fund Investment Categories

Which Have Consistently Generated Neither Positive nor Negative Exotic Beta for the trailing periods ending March 31, 2007

Morningstar Category 3 Year 5 Year 10 Year 15 Year Bear Market 3.30 1.33 -0.53 -0.18Diversified Emerging Mkts -4.50 1.13 -1.62 -1.17Diversified Pacific/Asia -5.07 0.66 -2.58 -2.82Europe Stock 1.32 -2.13 2.16 3.16Foreign Large Blend -0.05 -0.12 0.86 0.50Foreign Large Growth -0.47 0.04 1.50 2.69Foreign Large Value 0.25 -0.38 1.16 4.23Foreign Small/Mid Growth 0.00 0.17 -0.90 0.46Foreign Small/Mid Value -0.55 0.05 11.17 6.27High Yield Muni 0.69 NA NA NAInflation-Protected Bond -0.70 -0.37 0.01 0.18Intermediate Government 0.28 0.11 0.23 0.22Intermediate-Term Bond 0.12 0.44 0.03 0.08Japan Stock -7.65 2.21 -3.13 -4.61Large Blend 0.50 1.29 0.25 0.08Large Growth -2.05 -0.15 -0.29 -0.93Long Government 1.24 -1.17 -1.61 -1.14Long-Term Bond 1.25 0.16 -0.42 -0.17Mid-Cap Growth -1.00 3.50 2.15 0.13Moderate Allocation 0.77 -2.59 -0.10 0.50Muni National Interm -0.22 -0.16 -0.03 0.03Muni National Long 0.17 0.05 0.10 0.09Muni National Short -0.91 -0.44 -0.35 -0.24Muni Single State Interm -0.03 -0.05 -0.01 0.01Muni Single State Long 0.29 0.23 0.15 0.08Muni Single State Short -1.29 -0.43 -0.33 -0.02Short Government -0.64 -0.28 -0.04 -0.01Short-Term Bond -0.60 0.03 0.05 0.08Small Blend -1.34 4.75 4.67 3.36Small Growth -4.04 1.78 0.58 -1.02Specialty-Health -1.45 -1.34 2.23 1.76Specialty-Natural Res 13.73 10.62 3.03 -1.12Specialty-Precious Metals -22.28 -5.34 1.17 -1.76Specialty-Technology -5.61 -2.74 6.64 3.02Target-Date 2000-2014 -0.10 -0.09 -0.46 -0.02Target-Date 2015-2029 -0.05 -4.50 -1.57 NATarget-Date 2030+ -0.41 -5.46 -2.06 NAUltrashort Bond 0.06 0.08 0.04 0.09World Allocation 2.36 -1.33 -2.58 -1.74World Bond 0.41 1.93 -0.16 -0.10



Percentage of Active Managers Outperforming Based on the asset weighted average measurement, actively managed mutual funds in certain categories held an advantage to passive indices, although only a portion of active managers actually outperformed their benchmark indices. The table on the following pages highlights which categories of active managers outperformed their benchmarks over different time periods:

Percentage of Mutual Funds with Real Alpha of >+0.5 within their investment category

for the trailing periods ending March 31, 2007

Morningstar

Category 3 Year 5 Year 10 Year 15 Year Bank Loan Between 75-100% Between 50-74% Between 50-74% Between 50-74% Bear Market Between 0-24% Between 0-24% Between 0-24% Between 0-24% Conservative Allocation Between 0-24% Between 0-24% Between 25-49% Between 50-74% Convertibles Between 25-49% Between 25-49% Between 50-74% Between 50-74% Diversified Emerging Mkts Between 75-100% Between 75-100% Between 75-100% Between 50-74% Diversified Pacific/Asia Between 50-74% Between 75-100% Between 50-74% Between 50-74% Emerging Markets Bond Between 75-100% Between 50-74% Between 0-24% NA Europe Stock Between 25-49% Between 50-74% Between 50-74% Between 0-24% Foreign Large Blend Between 0-24% Between 0-24% Between 0-24% Between 25-49% Foreign Large Growth Between 0-24% Between 25-49% Between 0-24% Between 0-24% Foreign Large Value Between 25-49% Between 50-74% Between 50-74% Between 50-74% Foreign Small/Mid Growth Between 25-49% Between 75-100% Between 75-100%

Between 75-100%

Foreign Small/Mid Value Between 50-74% Between 75-100% Between 50-74% Between 25-49% High Yield Bond Between 0-24% Between 0-24% Between 0-24% Between 0-24% High Yield Muni Between 75-100% NA NA NA Inflation-Protected Bond Between 0-24% Between 50-74% Between 25-49% Between 0-24% Intermediate Government Between 0-24% Between 0-24% Between 0-24% Between 0-24% Intermediate-Term Bond Between 0-24% Between 0-24% Between 0-24% Between 0-24% Japan Stock Between 0-24% Between 0-24% Between 25-49% Between 25-49% Large Blend Between 0-24% Between 0-24% Between 25-49% Between 25-49% Large Growth Between 25-49% Between 0-24% Between 25-49% Between 25-49% Large Value Between 25-49% Between 0-24% Between 0-24% Between 0-24% Latin America Stock Between 75-100% Between 75-100% Between 75-100%

Between 75-100%

Long Government Between 25-49% Between 0-24% Between 0-24% Between 0-24%




for the trailing periods ending March 31, 2007 (continued) Morningstar Category 3 Year 5 Year 10 Year 15 Year

Long-Short Between 25-49% Between 25-49% Between 75-100% Between 75-

100% Long-Term Bond Between 25-49% Between 25-49% Between 0-24% Between 0-24% Mid-Cap Blend Between 25-49% Between 25-49% Between 25-49% Between 25-49% Mid-Cap Growth Between 25-49% Between 0-24% Between 25-49% Between 25-49% Mid-Cap Value Between 50-74% Between 0-24% Between 0-24% Between 0-24% Moderate Allocation Between 0-24% Between 0-24% Between 25-49% Between 25-49% Multisector Bond Between 50-74% Between 50-74% Between 25-49% Between 0-24% Muni National Interm Between 0-24% Between 0-24% Between 0-24% Between 0-24% Muni National Long Between 0-24% Between 0-24% Between 0-24% Between 0-24% Muni National Short Between 0-24% Between 0-24% Between 0-24% Between 0-24% Muni Single State Interm Between 0-24% Between 0-24% Between 0-24% Between 0-24% Muni Single State Long Between 0-24% Between 0-24% Between 0-24% Between 0-24% Muni Single State Short Between 0-24% Between 0-24% Between 0-24% Between 0-24% Pacific/Asia ex-Japan Stk Between 75-100% Between 75-100% Between 75-100% Between 25-49% Short Government Between 0-24% Between 0-24% Between 0-24% Between 0-24% Short-Term Bond Between 0-24% Between 0-24% Between 0-24% Between 0-24% Small Blend Between 25-49% Between 25-49% Between 50-74% Between 50-74% Small Growth Between 25-49% Between 25-49% Between 50-74% Between 25-49% Small Value Between 25-49% Between 25-49% Between 25-49% Between 25-49% Specialty-Communications Between 25-49% Between 50-74% Between 50-74%

Between 75-100%

Specialty-Financial Between 0-24% Between 25-49% Between 25-49% Between 50-74%

Specialty-Health Between 25-49% Between 50-74% Between 50-74% Between 75-

100% Specialty-Natural Res Between 25-49% Between 75-100% Between 50-74%

Between 75-100%

Specialty-Precious Metals Between 75-100% Between 75-100% Between 75-100%

Between 75-100%

Specialty-Real Estate Between 25-49% Between 50-74% Between 25-49% Between 25-49% Specialty-Technology Between 0-24% Between 25-49% Between 0-24% Between 0-24%

Specialty-Utilities Between 75-100% Between 75-100% Between 75-100% Between 75-

100% Target-Date 2000-2014 Between 0-24% Between 0-24% Between 25-49% Between 50-74% Target-Date 2015-2029 Between 0-24% Between 0-24% Between 0-24% NA




for the trailing periods ending March 31, 2007 (continued)

Morningstar Category 3 Year 5 Year 10 Year 15 Year Target-Date 2030+ Between 0-24% Between 0-24% Between 0-24% NA Ultrashort Bond Between 0-24% Between 0-24% Between 0-24% Between 0-24%

World Allocation Between 25-49% Between 75-100% Between 75-100% Between 75-

100% World Bond Between 25-49% Between 25-49% Between 25-49% Between 25-49% World Stock Between 25-49% Between 50-74% Between 50-74% Between 50-74%

Appendix 3 Indexes Regressed Against Portfolios (Mutual Funds) 6 Month CD Lehman Brothers Municipal New York

Citigroup ESBI-Capped Brady Merrill Lynch Conv Bonds, All Qualities

Citigroup Non-$ World Govt Bond MSCI AC Far East ex Japan ID

CSFB High Yield MSCI AC World ID

Dow Jones 60% Global Portfolio MSCI EAFE NDTR_D

Dow Jones Financial MSCI EASEA (EAFE ex Japan) NDTR_D

Dow Jones Healthcare MSCI EM ID

Dow Jones Telecommunications MSCI EM Latin America ID

Dow Jones Utility MSCI Europe NDTR_D

Goldman Sachs Natural Resources MSCI Japan NDTR_D

JSE Gold (USD) MSCI Pacific ex JAPAN NDTR_D

LB 1-5 YR Govt MSCI Pacific NDTR_D

LB 1-5 YR Govt/Credit MSCI World ex US NDTR_D

LB 5-10 Yr Govt/Credit MSCI World Metals & Mining ID

LB Long Term Govt/Credit Bond MSCI World NDTR_D

LB Municipal 10YR (8-12) Pacific Stock Exchange Tech 100

LB Municipal 20YR (17-22) Russell 1000

LB Municipal 3YR (2-4) Russell 1000 Growth

LB U.S. Universal Bond Russell 1000 Value

Lehman Brothers Aggregate Bond Russell 2000

Lehman Brothers Credit Bond Russell 2000 Growth

Lehman Brothers Government Bond Russell 2000 Value

Lehman Brothers Intermediate Treasury Russell Midcap Growth

Lehman Brothers Long Term Govt Bond Russell Midcap Value

Lehman Brothers Long Term Treasury Bond Standard & Poor's 500

Lehman Brothers Mortgage-Backed Bond Standard & Poor's Midcap 400

Lehman Brothers Municipal Bond Wilshire 4500

Lehman Brothers Municipal California Wilshire REIT



Note: FundQuest has built a family of funds and a mutual fund investment program based on this research. A version of this paper was published in the Journal of Indexes in the March/April 2008 issue.

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