Time-Varying Incentives in the
Mutual Fund Industry
Jacques Olivier
HEC Paris
Anthony Tay
Singapore Management University
Motivation
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Existing empirical literature on mutual fund flows:
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Ippolito (1992), Gruber (1996), Chevalier and Ellison (1997), Sirri
and Tufano (1998), Del Guercio and Tkac (2002), Lynch and Musto
(2003), Barber, Odean and Zheng (2005), Gallaher, Kaniel and
Starks (2006) and Huang, Wei and Yan (2007)…
Because of fee structure, investor flows shape the
incentives of mutual fund managers
Crucial property of flows: convex function of past
performance, which provides incentives for strategic
risk-shifting
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Chevalier and Ellison (1997), Brown et al. (1996)
Preview (1)
 Central
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result of this paper:
Convexity of the flow-performance relationship
varies with economic activity
The stronger is economic activity, the more
convex is the flow-performance relationship
Preview (2)
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5 issues:
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(i) Is the effect economically significant?
• YES:
+1% GDP growth implies (more than) twice as much
convexity as on average
-1% GDP growth implies no convexity whatsoever (and even
some concavity)
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(ii) Is the effect driven by “abnormal” years?
• NO: removing years with deep recessions or strong booms
leaves the result unchanged
Preview (3)
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5 issues (continued):
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(iii) Through which channel does economic activity affect
the nature of the flow-performance relationship?
• GDP growth, NOT market returns
• Aggregate flows, NOT volatility
• Consistent with consumption smoothing + disposition effect
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(iv) Does the time variation of the flow-performance
relationship affect decisions of fund managers?
• YES: strategic risk-shifting occurs only when GDP growth is high
• Effect of GDP growth dominates that of market returns
Preview (4)
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5 issues (continued):
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(v) Other reasons why we care about the result:
• Rationalizes existing results on mutual fund performance
over the business cycle
• Methodological aspects
• Time-varying risk premia (more tentative…)
Data and Methodology (1)
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No-load US domestic equity mutual funds appearing in CRSP
survival bias free mutual fund database between 1980 and 2006
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Exclude multiple classes, index funds, funds of funds, funds closed
to investors, funds that never reached 10M$ of total net assets
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Flow variablei,t = Dollar Flowi,t = TNAi,t – (1+ri, t) TNAi, t-1
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Where TNAi,t represent Total Net Assets at the end of year t
Data and Methodology (2)
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Rank (or relative performance): year-by-year ranking of
fund managers according to their (1-factor) alpha:
• Measure between 0 (worse performer) and 1 (best performer)
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Following Sirri and Tufano (1998), divide performance in
three regions:
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TOP: top quintile (relative performance from 0.8 to 1)
MIDDLE: middle three quintiles (from 0.2 to 0.8)
BOTTOM: bottom quintile (below 0.2)
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Estimate piecewise linear regression of current flows on
past performance
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Robustness checks:
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Rank managers by their excess returns or by their 4-factor alphas
Use 1-factor alphas themselves instead of the ranking
Data and Methodology (3)
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Standard flow-performance regression (e.g. Sirri and Tufano, 1998):
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Where:
Data and Methodology (4)
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Interpretation of the standard regression:
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There is convexity if and only a1 – a3 is positive and
significant
In other words, if and only if flows react more to
differences in performance of good performers than
to differences in performances of lousy performers
Data and Methodology (5)
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What we test in this paper:
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Does the difference a1 – a3 vary with economic activity?
Our basic regression:
Data and Methodology (6)
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Interpretation: Business cycle effects measured by
deviations (in percentage) of real US GDP growth
from its sample mean
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Year-fixed effects: take care of impact of business cycle
on the intercept
Slope effects: captured by interaction variable:
Data and Methodology (7)
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Interpretation of coefficient on performance: impact of
performance on flows when US GDP growth is equal to
its sample mean
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Interpretation of coefficient on interaction variable: how
does a +1% deviation of GDP growth change the (total)
impact of performance on growth
Data and Methodology (8)
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Tests of convexity
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Flow-performance relationship is convex on average if
and only if:
a1 is (significantly) larger than a3
A +1% increase of GDP growth rate increases
convexity if and only if:
a4 is (significantly) larger than a6
Data and Methodology (9)
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Unbalanced Panel Data
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Year fixed effects though year dummy variables
Standard errors clustered by funds
Methodological remark:
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Usual methodology used in mutual fund flows literature: FamaMac Beth regressions
Assumes that slope coefficients in each annual regression drawn
from the same distribution
Not valid if systematic time variation at business cycle frequency in
slope coefficients
Comparable to point made 10 years ago in the asset pricing
literature (conditional vs. unconditional CAPM)
Basic Results (1)
Basic Results (2)
Basic Results (3)
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Interpretation:
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Flow-performance relationship convex on average
Stronger reaction of flows to good performance when economic
activity is strong
Stronger convexity of the flow-performance relationship when
economic activity is strong
Order of magnitude: a +/- 1% change of GDP growth (more than)
doubles / eliminates the convexity in the flow-performance
relationship
Robustness Checks
Economic Interpretation (1)
Economic Interpretation (2)
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Candidate 1: flow composition effect
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Step 1: convexity of new inflows and of portfolio rebalancing flows
• Investors look for positive alpha funds
• Positive alpha funds concentrated in upper tail of the distribution
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Step 2: outflows are a flat or concave function of performance
• Concentration of portfolios + short-sale constraints
• Disposition effect
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Step 3: more outflows when economic activity is weak
• Consumption smoothing
Economic Interpretation (3)
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Candidate 2: volatility effect
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Step 1: convexity driven by investors looking for positive alpha
funds
Step 2: volatility is countercyclical
Step 3: performance is less informative about skill when volatility
is high (more noise)
Economic Interpretation (4)
Implications (1)
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Tournament Hypothesis
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Brown et al. (1996), Chevalier and Ellison (1997): convexity of flowperformance relationship provides incentives for poor mid-year
performers to take on more risk
Empirical evidence on risk-shifting: very mixed depending on
samples
Kempf et al. (2008): cost of switching jobs imply more risk-shifting
under good than under bad market conditions
2 issues:
• No direct estimate of cost of switching jobs and relative magnitude
compared to high-powered incentives in the industry
• Could go either way (foregone bonuses)
Implications (2)
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Conditional Tournament Hypothesis
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When the flow-performance relationship is convex, then poor midyear performers have incentives to increase the risk of their
portfolios
Thus, more risk-shifting when economic activity is strong
If risk-shifting mostly driven by the flow-performance relationship
then no impact of market conditions on risk-shifting once business
cycle effects are accounted for
Implications (3)
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Conditional Tournament Hypothesis (continued)
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Negative coefficient of interaction variable: poor performers
increase their risk even more when GDP growth is high
Year fixed effect and fund clustered standard errors
Implications (4)
Implications (6)
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Conclusion:
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Behavior of fund managers is consistent with time-series properties
of the flow-performance relationship
Reconciles insights of seminal papers in the field with conflicting
empirical evidence
Once time-varying nature of incentives are accounted for, only mild
support for impact of employment risk
Some evidence in favor of market timing by fund managers
Other Reasons to Care About the Result
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Kosowski (2006): Funds have significantly larger alphas
during recessions than during booms
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This paper provides a possible rationale for the result: more
distortion of incentives of mutual fund managers during booms
Mechanism supported by Huang et al. (2008): risk-shifting destroys
value
Asset pricing literature: Non constant discount factors
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This paper provides a (very) specific example where business cycle
variations generate endogenously shifts to risk aversion of agents
(fund managers)