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Pension funds and their investment consultants

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(1)

Pension funds and their

investment consultants

Tim Jenkinson

Professor of Finance

Director, Private Equity Institute

(2)

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?

(3)

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

(4)

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

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Questions

We analyze

What drives investment consultants’ recommendations

of institutional funds

What impact these recommendations have on flows

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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

(10)

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

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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

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Final sample

Number of Investment Consultants Number of Recommend ations

Number of Products Average Product Asset Size

Recommend ed Not Recommend ed Total Recommend ed Not Recommend ed Total 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

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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

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Avg. Returns Avg. Excess Ret. over Benchmark One Factor Alpha Three Factor Alpha Four Factor Alpha Equally Weighted Recommended Products 7.13% 1.25% 2.43% 1.14% 1.14% (1.40) (2.14)** (2.63)*** (1.42) (1.36) 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)** Value Weighted Recommended Products 4.90% 0.96% 0.18% 0.39% 0.39% (0.92) (1.26) (0.22) (0.48) (0.48) 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)

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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

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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

(17)

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

(18)

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

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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

(21)

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

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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)

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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

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12 Month Period Following Addition/Deletion

Avg. Returns Avg. Excess Ret. over Benchmark One Factor Alpha Three Factor Alpha Four Factor Alpha Equally Weighted 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) 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) Value Weighted 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) 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)

Table VIII

References

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