Patience is a Virtue: Understanding Short-Term Performance in Successful Managers

Scott Cameron, CFA
Principal/Chief Investment Officer

 

Multnomah Group recently completed a webinar entitled "Why Doesn't Your Retirement Plan Work? 13 Traps that Limit the Effectiveness of Your Plan" (Link to Recording). In that webinar my colleague, Erik Daley, reviewed some of the common challenges that prevent participants from achieving their retirement outcomes.

As I thought about his presentation I realized that many times Investment Committees fall into self-created traps that perpetuate a cycle of bad performance for their plans and poor outcomes for their participants. One of the most frequent traps we see when onboarding new clients is with investment policy statements (IPSs) that are too prescriptive in their evaluation methodology. An example is where the Committee includes specific metrics and time horizons in their IPS for the evaluation of funds.

Frequently these criteria include peer group rankings or outperformance relative to the assigned benchmark over a 3 year time horizon. Funds that fail to outperform over that time period get placed on a Watch List to be monitored for 3 quarters in order to determine whether the fund's performance has improved. If the performance has not improved then the Committee either needs to take action to replace the manager or is forced to justify continuing to use a manager that fails their investment criteria.

Unfortunately, this type of prescriptive decision-making is too common. It is not hard to demonstrate the challenges it presents to an investment committee. We analyzed funds that have been successful in outperforming the benchmark over the long term (10 years in this example) to see how they perform using a shorter term rolling 3 year analysis. Our full methodology is described in the Appendix.

The results of our analysis are overwhelming and, frankly, a little surprising in their magnitude. Almost every manager that outperformed the benchmark over the long-term had at least one 3 year period in that 10 year period where they underperformed the benchmark. In fact, 99.3% of the "successful" managers (all but 5 out of 715) underperformed at some point. Those periods of underperformance were not outliers. Across all peer groups we studied, the successful long-term investment managers underperformed in the short-term 36% of the time.

Overwhelmingly good funds, funds that have long-term success, underperform their benchmark and do so with some regularity. Therefore, using past performance in a prescriptive manner causes investment committees to chase performance and buy high/sell low with investment managers in the same way that individuals do with stocks.

TABLE: RESEARCH RESULTS

Fund
Category
# of Funds# of Funds
with
Positive
Excess
Returns
% of Funds
with
Positive
Excess
Returns
% of
Successful
Funds With
At Lease One
Negative
Rolling 3
Year Period
Average # of
Negative
Rolling 3
Year
Periods for
Successful
Funds
Average %
of Negative
3 Rolling
Periods
Intermediate Bond 225 114 51% 100% 31 37%
Large Value 200 63 32% 100% 31 37%
Large Blend 313 85 27% 98% 32 38%
Large Growth 309 122 39% 99% 34 40%
Mid Cap Value 60 13 22% 100% 37 43%
Mid Cap Blend 88 18 20% 100% 41 48%
Mid Cap Growth 154 52 34% 100% 28 33%
Small Value 57 42 74% 98% 29 34%
Small Blend 134 55 41% 100% 26 31%
Small Growth 144 58 40% 100% 28 33%
Foreign Large Value 57 25 44% 100% 24 29%
Foreign Large Blend 121 45 37% 98% 25 29%
Foreign Large Growth 40 23 58% 100% 23 28%
Total 1,902 715 38% 99% 30 36%

 

APPENDIX: RESEARCH METHODOLOGY

To conduct our research we utilized the Morningstar US Mutual Fund database. We divided the database up based on the Morningstar Category and filtered the database to utilize the Oldest Share Class for each mutual fund. Many fund managers offer multiple share classes of the same portfolio to target different buying groups. The only difference between the share classes is the expense ratio charged to investors. Filtering out the Oldest Share Class removes duplicates and prevents the dataset from getting skewed by funds that offer the most number of share classes. Additionally, only funds that had a full 10 year track record were included in the dataset.

For each peer group analyzed a benchmark index was selected. We chose the peer groups based on those most frequently found in our clients' investment menus. The table below shows the peer groups analyzed and the assigned benchmark.

Morningstar CategoryBenchmark Index
Intermediate Bond Barclays Capital US Aggregate Bond Index
Large Value Russell 1000 Value Index
Large Blend Russell 1000 Index
Large Growth Russell 1000 Growth Index
Mid-Cap Value Russell Mid-Cap Value Index
Mid-Cap Blend Russell Mid-Cap Index
Mid-Cap Growth Russell Mid-Cap Growth Index
Small Value Russell 2000 Value Index
Small Blend Russell 2000 Index
Small Growth Russell 2000 Growth Index
Foreign Large Value MSCI World ex USA Large Value USD
Foreign Large Blend MSCI World ex USA Large Cap USD
Foreign Large Growth MSCI World ex USA Large Growth USD

Excess returns were calculated for each fund in the peer group relative to the peer group benchmark index. Excess returns were calculated for the 10 years ending March 31, 2013 as well as for the rolling 36 month windows beginning April 1, 2003. In total there were 85 rolling 36 month windows that were calculated.

 

Information herein is provided for general informational purposes and is not intended to be completely comprehensive regarding the particular subject matter. Multnomah Group does not represent, guarantee, or provide any warranties (express or implied) regarding the completeness, accuracy, or currency of information or its suitability for any particular purpose. Receipt of information does not create an adviser-client relationship between Multnomah Group and you. Neither Multnomah Group nor our advisory affiliates provide tax or legal advice or opinions. You should consult with your own tax or legal adviser for advice about your specific situation.