In Search of Skill Morningstar Investment Management s Approach to Selecting Managers Bill Harding Head of Manager Research, Morningstar Investment Management 2012 Morningstar, Inc. All rights reserved. <#>
The Challenge Active management is zero-sum game: superior investors earn positive alpha, inferior investors generate negative alpha Average actively managed fund doesn t capture alpha net of fees Good news is that academic research reveals manager skill may exist Challenge is to identify those superior managers beforehand and limit exposure to inferior managers
Research on Performance Persistence Ibbotson and Patel (2002) found that funds with highest alpha against returns-based style benchmark outperform Peterson, Iachini, and Lam (2011) found evidence of persistence in alpha among separately managed accounts over 1 to 3-year periods Harlow and Brown (2006) found that selecting funds with higher past alpha and lower expenses significantly increases probability of identifying future superior managers Kosowski, Timmermann, Wermers, and White (2006) found significant persistence in alphas of top decile managers based on a bootstrap analysis that adjusts for non-normality in fund alphas
Research on Fund Characteristics Morningstar study of mutual fund stewardship (2011) found that funds with higher levels of manager ownership of funds shares earned higher risk-adjusted returns relative to category peers. Morningstar stewardship study (2011) revealed a more positive assessment of a firm s culture led to better manager retention and better risk-adjusted performance. Morningstar and Kinnel (2010) found that funds with lower expense ratios tend to outperform. Cremers and Petajisto (2009) found that active share is a significant predicator of future alpha. Multivariate regressions revealed funds with highest active shares, smaller assets, and best one-year performance produces highest future alpha.
Research on Fund Characteristics Peterson, Iachini, and Lam (2011) found evidence that more assets under management can be a negative factor for performance of separately managed accounts Wei, Wermers, and Yao (2009) found that funds that hold contrarian stocks tend outperform herding managers based on their four-factor alpha that controls for the momentum effect Idzorek, Xiong, and Ibbotson (2011) found that funds that invest in low liquidity and high momentum stocks outperform
Manager Evaluation Process
Morningstar Investment Management: Manager Evaluation Process Qualitative Research Forward looking Identify competitive advantages Depth in coverage Quantitative Analysis Disciplined Unbiased Breadth in coverage Create portfolios of managers with: Demonstrated evidence of skill Possess competitive advantages to repeat success Higher probability to deliver alpha in future Work well in portfolios based on client objectives
Manager Evaluation Process Universe Qualitative Research Fundamental evaluation of five pillars converted into scores Quantitative Analysis Multi-factor model produces a forward-looking alpha measure Blended Alpha Forecast Portfolio Optimizer
Quantitative Analysis Calculate forward-looking alpha based on following factors: Short-Term Performance Persistence Active Share or Tracking Error Momentum of underlying stocks Liquidity of underlying stocks Based on research findings Supported by convincing back test
Qualitative Research: Five Pillars Parent Structure/ownership Organization stability/financial strength Culture/stewardship Regulatory/compliance People Team quality/experience Team depth Team continuity Alignment of interests
Qualitative Research: Five Pillars Process Security selection/idea generation Valuation discipline Portfolio construction/risk management Capacity Performance Rolling risk-adjusted returns vs. style benchmark Downside statistics Attribution Price Expense ratio relative to peer group
Portfolio Construction Determine the role each fund meant to serve in portfolio Returns- and holdings-based analysis to understand fund exposures Examine interaction of funds (common holdings, correlations) Monitor risk characteristics of portfolio and contribution by each fund Use optimization techniques to put together funds with attributes that maximizes the portfolio s return for given level of risk.
Portfolio Construction Example: Common Holdings/Overlap Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results.
Portfolio Construction Example: Correlations Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results.
Due Diligence Process
Key Factors in Ongoing Due Diligence Manager and/or organizational changes Strategy and/or style drift Changing portfolio or risk characteristics Performance relative to benchmark and peers Performance attribution Changes in expenses Asset bloat
Due Diligence Toolkit Qualitative research Performance analysis and attribution Holdings-based analysis Return-based style analysis
Qualitative Research Filings, fund company materials Morningstar analyst reports Due diligence questionnaire Due-Diligence Questionnaire Excerpt On-site visits Conference calls Manager meetings Meeting Notes Excerpt For illustrative purposes only.
Research Management System Central repository of due diligence documents Vital source of qualitative information on managers and funds Easy to retrieve information on certain security or manager Fosters collaboration across global team For illustrative purposes only.
Performance Attribution Example Attribution 1/1/2009-12/31/2011 Rescaled Weights % Return % Attribution Effect Port BM Port BM Morningsta r Sector Selectio n Active Return Basic Materials 5.51 3.18 0.31 59.22 0.01-3.70-3.68 Communication Services 0.86 4.20 18.58 44.33-0.18-0.05-0.24 Consumer Cyclical 8.48 8.51 96.05 99.64 0.30-0.06 0.24 Consumer Defensive 14.44 12.10 60.68 49.26 0.58 1.56 2.14 Energy 14.36 11.99 35.47 45.08 0.01-1.64-1.63 Financial Services 27.52 13.79 34.11 7.03-5.30 7.88 2.57 Healthcare 9.84 12.22 47.99 37.16 1.23 0.08 1.32 Industrials 6.68 11.61 35.04 52.93 0.04-1.43-1.39 Real Estate 1.05 1.41 90.42 86.75-0.13-0.18-0.31 Technology 8.20 17.24 73.23 84.04-2.08-0.58-2.66 Utilities 0.17 3.59 40.05 39.76 0.30 0.19 0.49 Unclassified 1.03 0.21 47.70 64.62 0.87-0.57 0.30 Cash 2.16 0.00 0.36-1.08 0.00-1.08 Attribution Total 100.00 100.00 45.16 49.07-5.42 1.51-3.91 Benchmark: S&P 500 Index Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results.
Performance Attribution Example Attribution 1/1/2009-12/31/2011 Rescaled Weights % Return % Attribution Effect Port BM Port BM Economic Moat Weighting Selection Active Return Narrow 47.44 45.01 46.04 49.53 0.13-1.75-1.62 None 6.97 9.35 79.00 58.77-0.09 1.22 1.14 Wide 34.86 43.08 42.47 45.99 0.48-1.83-1.35 Unclassified 8.58 2.56 39.95 67.64 0.90-1.89-0.99 Cash 2.16 0.00 0.36-1.08 0.00-1.08 Attribution Total 100.00 100.00 45.16 49.07 0.34-4.25-3.91 Benchmark: S&P 500 Index. Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results.
Returns-Based Style Analysis Example World Stock Fund Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results.
Returns-Based Style Example Small-Growth Fund Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results.
Holdings-Based Time Series Example Small Growth Fund 90.00 8,000,000,000 80.00 7,000,000,000 70.00 6,000,000,000 60.00 5,000,000,000 % Assets 50.00 40.00 4,000,000,000 Net Assets 30.00 3,000,000,000 20.00 2,000,000,000 10.00 1,000,000,000 0.00 Jun- 01 Dec- 01 Jun- 02 Dec- 02 Jun- 03 Dec- 03 Jun- 04 Dec- 04 Jun- 05 Dec- 05 Jun- 06 Dec- 06 Jun- 07 Dec- 07 Jun- 08 Dec- 08 Jun- 09 Dec- 09 Jun- 10 Dec- 10 Jun- 11 Sep- 11 0 Mid Cap % Small Cap % Net Assets Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results.
Active Share Time Series Example Foreign Large Blend Fund 0.9000 6.00 0.8500 4.00 0.8000 2.00 0.7500 0.00 Active Share 0.7000 0.6500 0.6000-2.00-4.00-6.00 1-Year Alpha 0.5500-8.00 0.5000 0.4500 0.4000 Active share and alpha measured against the MSCI ACWI ex US Index. Q1 2007 Q2 2007 Q3 2007 Q4 2007 Q1 2008 Q2 2008 Q3 2008 Q4 2008 Q1 2009 Q2 2009 Q3 2009 Q4 2009 Active Share Alpha Q1 2010 Q2 2010 Q3 2010 Q4 2010 Q1 2011 Q2 2011 Q3 2011 Q4 2011 Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results. -10.00-12.00-14.00
Holdings-Based Time Series Example Foreign Large Blend Fund 800 30,000,000,000 # Holdings 700 600 500 400 300 200 100 0 Jan-02 Jul-02 Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10 Jul-10 Jan-11 Jul-11 Dec-11 # Holdings Fund Size 25,000,000,000 20,000,000,000 15,000,000,000 10,000,000,000 5,000,000,000 Source: Morningstar Direct, as of 12-31-2011. For illustrative purposes only; indexes are unmanaged and not available for direct investment; past performance is not indicative of future results. 0 Fund Assets
Questions
References Harlow, W. Van, and Keith Brown. 2006. The Right Answer to the Wrong Question: Identifying Superior Active Portfolio Management. Journal of Investment Management, vol.4, no. 4 (2006):1-26. Ibbotson, Roger, and Amita Patel. February 2002. Do Winners Repeat with Style? Available at www.ibbotson.com/research Idzorek, Thomas, James Xiong, and Roger Ibbotson. January 2011. Combining Liquidity and Momentum to Pick Top-Performing Mutual Funds. Available at www.ibbotson.com/research Cremers, Martijn and Antii Petajisto. 2009. How Active is Your Fund Manager? A New Measure That Predicts Performance, Review of Financial Studies, vol.22, no.9: 3329-3365.
References Kinnel, Russell. 2010. How Expense Ratios and Star Ratings Predict Success. Morningstar Advisor (August 10, 2010). Kosowski, Robert, Allan Timermann, Russ Wermers, and Hal White. 2006. Can Mutual Fund Stars Really Pick Stocks? New Evidence from a Bootstrap Analysis. The Journal of Finance, vol. 61, no.6 (December 2006): 2551-2596. Lutton, Laura Pavlenko, Katie Rushkewicz, Kailin Liu, and Xin Ling. 2011. 2011 Mutual Fund Stewardship Grade Research Paper. Available at http://corporate.morningstar.com/us/documents/methodologydocum ents/researchpapers/stewardshipstudy.pdf
References Peterson, James, Michael Iachini, and Wynce Lam. 2011. Identifying Characteristics to Predict Separately Managed Account Performance, Financial Analysts Journal, 2011, v67, no.4: 30-40. Wei, Kelsey, Russ Wermers, and Tong Yao. 2008. Uncommon Value The Investment Performance of Contrarian Fund, working paper available at http://www.cfrcologne.de/download/researchseminar/ws0809/russwermers_cont rarian 20081012.pdf
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