Pension funds and their investment consultants Tim Jenkinson Professor of Finance Director, Private Equity Institute May 2014
A mystery Academic evidence, and industry analysis,over several decades has shown that active management in mature asset classes adds no value on average The additional costs outweigh any performance enhancement And while, obviously, some asset managers out-perform each year, returns have been shown to mean-revert So why do pension funds and other large investors continue to chase fools gold? Or, to put it another way, why are there so many active asset managers? Why are Darwinian forces working so slowly? 2
Investment consultants Investment consultants advise many retirement plans, foundations, endowments, and other plan sponsors On the asset side, the most important services are money manager search/selection and asset allocation development On the liability side, many ICs are part of organizations that also provide actuarial and liability modelling services Worldwide, $25 trillion of assets are under advisement The industry is concentrated: the top 5 ICs are Hewitt ($4.4 tr), Mercer ($4 tr), Cambridge Associates ($2.5 tr), Russell ($2.4 tr) & Towers Watson ($2.1 tr) A recent survey by Pension and Investments found that 94% of plan sponsors employed ICs 3
Conflicts of interest? Investment consultants are the key gatekeepers for asset managers, in their attempts to convince plan sponsors to invest and yet many asset managers, and plan sponsors, seriously doubt their abilities Arguably, they have an interest in complexity, and in plan sponsors believing in active management as it justifies their role in manager selection and increases their fees So the cost to plan sponsors, and society, may be more via the increased fees of active management than the consultants fees per se 4
Questions We analyze 1 What drives investment consultants recommendations of institutional funds 2 What impact these recommendations have on flows 3 Whether recommendations add value for plan sponsors 5
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Data We are the first to use an annual survey of investment consultants recommendations produced by Greenwich Associates We focus on US active equity products for which there is the longest consistent data series Data covers 1999-2011 (survey coverage 91% as of 2011) US equities are probably more efficient than other asset classes so may be more difficult to pick winners but they all continue to try 9
Recommendations Consultants are asked to recommend 4-6 asset managers (Ams) for each investment style (e.g. Large Cap Growth, Large Cap Value, etc.) Responses are anonymous Consultants also judge fund managers according to: 1. Soft investment factors, i.e. clear decision making, portfolio manager s capability, consistent investment philosophy 2. Service factors, i.e. capable relationship professional, useful reports prepared by fund managers, effective presentations to consultants 10
Performance data Assets under management and performance data is derived from evestment, a third-party provider These are institutional products not mutual funds We limit our analysis to US long-only equity products (we eliminate index funds, hedge funds, REITs and retail funds) We also eliminate products in size/style categories not covered by the GA survey (i.e. MidCap Growth and Value before 2001) Data on benchmarks (Russell indexes) is from Datastream and factors (Fama-French-Carhart) from CRSP/Ken French 11
Final sample Number of Number of Investment Recommend Consultants ations Number of Products Not Recommend Recommend Total ed ed Average Product Asset Size Not Recommend Recommend Total ed ed 1999 25 459 116 849 965 7,911 560 1,871 2000 36 1398 241 856 1,097 5,624 737 2,140 2001 27 966 230 993 1,223 4,168 828 1,659 2002 32 1434 314 1,266 1,580 2,757 632 1,150 2003 30 1444 357 1,306 1,663 3,244 721 1,382 2004 30 1745 409 1,913 2,322 4,056 1,079 1,709 2005 29 1940 452 1,959 2,411 3,925 994 1,641 2006 28 2107 503 1,930 2,433 4,198 984 1,733 2007 29 2297 526 1,909 2,435 3,836 1,108 1,749 2008 30 2164 557 1,842 2,399 2,611 650 1,138 2009 29 1887 533 1,742 2,275 2,982 655 1,219 2010 27 1608 476 1,672 2,148 3,481 798 1,414 2011 28 1501 454 1,537 1,991 3,549 864 1,490 Large Cap Growth 29 437 90 345 435 6,045 927 2,185 Large Cap Value 29 455 91 315 406 5,610 1,257 2,334 Mid Cap Growth 24 150 38 121 159 2,216 513 958 Mid Cap Value 25 108 29 92 121 2,753 564 1,169 Small Cap Growth 26 160 50 204 254 1,309 483 664 Small Cap Value 27 167 51 191 242 1,519 499 746 Core 23 316 104 491 595 3,147 902 1,332 12
3 Do consultants add value? We create equal- and value-weighted portfolio returns of recommended and not recommended products Returns are gross of asset management fees (evidence from evestment records indicate that intra-style variation in fees is extremely small; see also Busse et al., 2010) Recommended product returns are also gross of invesment consultant fees With these returns we estimate one (CAPM), three (FF) and four (FFC) factor alphas and excess returns over portfolios of selected benchmarks 13
Table IV Avg. Returns Avg. Excess Ret. over Benchmark One Factor Alpha Three Factor Alpha Four Factor Alpha Recommended Products 7.13% 1.25% 2.43% 1.14% 1.14% (1.40) (2.14)** (2.63)*** (1.42) (1.36) Equally Weighted Not Recommended Products 8.13% 2.35% 3.52% 2.00% 2.00% (1.59) (3.19)*** (3.30)*** (2.33)** (2.33)** Recommended - Not Recommended Products -1.00% -1.10% -1.09% -0.85% -0.86% (2.01)** (-3.03)*** (2.49)** (2.31)** (2.33)** Recommended Products 4.90% 0.96% 0.18% 0.39% 0.39% (0.92) (1.26) (0.22) (0.48) (0.48) Value Weighted Not Recommended Products 5.16% 0.57% 0.55% -0.32% -0.23% (1.02) (0.73) (0.55) (-0.41) (-0.31) Recommended - Not Recommended Products -0.26% 0.40% -0.37% 0.72% 0.62% (-0.20) (0.51) (-0.29) (0.73) (0.68) 14
Summary and conclusions Consultants recommendations are a function of past fund performance, but also of other factors (service and investment) Not merely a return chasing strategy They have a large and significant effect on flows into (and out of) institutional investment products But they fail consistently to add value in US equities for plan sponsors The underperformance of recommended products can be explained by consultants tendency to recommend relatively large products However, even allowing for this constraint (legitimate or not), recommended products still fail consistently to outperform 15
Why the attention? Because Investment Consultants are so powerful Asset managers seem to be extremely skeptical about IC s abilities but to question them could be very costly Trustees seem to think of ICs as, to some extent, an insurance against being sued But ICs have no interest in simplicity they encourage trustees in their search for fools gold and the costs are borne by the pensioners and other beneficiaries It is time that the performance of ICs was subject to proper scrutiny but their reaction to this paper has been to threaten to withdraw from the GA survey 16
Passive presumption Should there be a passive presumption for pension fund trustees? Only if they can articulate why they believe the active managers they choose will add value should they pay the additional fees And they should then subject themselves to careful monitoring to see whether they did beat passive strategies 17
More? Take a look at Picking Winners? Investment Consultants Recommendations of Fund Managers, by Tim Jenkinson, Howard Jones and Jose Vicente Martinez http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2327042 Or Google Tim Jenkinson 18
Extra slides 19
1 What drives recommendations? We estimate a Poisson model, with the standard exponential mean parameterization, on pooled yearly data We estimate the impact of past returns, return volatility, soft investment factors, and service factors Consultants recommendations are partly driven by past fund performance, but also by other factors (service and investment quality factors) Not merely a return chasing strategy Indeed, the soft investment factors and service factors are economically much more important 20
2 Recommendations & flows We consider two measures: A) $ flows and B) % flows Bivariate relationship between flows and recommendation changes Flow-performance regressions confirm that recommendations have a large and significant effect on flows into (and out of) institutional investment products 21
Product Size Investment consultants recommendations tend to be concentrated on large products Recommended products are 4 times as large as non-recommended ones (although partly as a result of recommendations attracting assets) Research shows that funds that manage more assets tend to perform worse (Chen et al, 2004) The preference for recommending large products may not be entirely free; consultants may be inclined to recommend large products due to liquidity reasons or doubts about the ability of small products to handle a larger pool of assets We then control for size, and still find that recommended products tend to underperform, although not significantly (see Table VII) 22
Changes in recommendations We also look at the relationship between recommendation changes and product performance So all these products have been considered appropriate for institutional investors We identify products that experience a net increase (decrease) in the number of recommendations and follow them for 12 / 24 months Net increases/decreases indicate whether, on average, a given product is being added/withdrawn from consultants shortlists We form portfolios and estimate one (CAPM), three (FF) and four (FFC) factor alphas and excess returns over portfolios of selected benchmarks 23
Table VIII 12 Month Period Following Addition/Deletion Avg. Returns Avg. Excess Ret. over Benchmark One Factor Alpha Three Factor Alpha Four Factor Alpha Increase in Number of Recommendations 5.34% 0.62% 2.26% 0.99% 0.94% (0.95) (1.02) (2.31)** (1.25) (1.19) Equally Weighted Decrease in Number of Recommendations 6.58% 1.19% 3.55% 1.48% 1.54% (1.20) (2.13)** (2.34)** (1.21) (1.32) Difference -1.24% -0.57% -1.29% -0.49% -0.59% (-0.86) (-0.80) (-0.89) (-0.49) (-0.69) Increase in Number of Recommendations 2.12% -0.35% -0.98% -0.22% -0.30% (0.36) (-0.24) (-0.56) (-0.19) (-0.29) Value Weighted Decrease in Number of Recommendations 4.62% 0.54% 1.63% 0.74% 0.81% (0.90) (0.75) (1.09) (0.67) (0.78) Difference -2.51% -0.89% -2.61% -0.97% -1.12% (-0.83) (-0.54) (-0.88) (-0.50) (-0.65) 24