Do Funds Make More When They Trade More?

• Date: 01 August 2017
• Author: ROBERT F. STAMBAUGH,ĽUBOŠ PÁSTOR,LUCIAN A. TAYLOR
• DOI: http://doi.org/10.1111/jofi.12509
• Published date: 01 August 2017

THE JOURNAL OF FINANCE •VOL. LXXII, NO. 4 •AUGUST 2017

Do Funds Make More When They Trade More?

ˇ

LUBO ˇ

SP´

ASTOR, ROBERT F. STAMBAUGH, and LUCIAN A. TAYLOR∗

ABSTRACT

We model fund turnover in the presence of time-varying profit opportunities. Our

model predicts a positive relation between an active fund’s turnover and its sub-

sequent benchmark-adjusted return. We find such a relation for equity mutual

funds. This time-series relation between turnover and performance is stronger than

the cross-sectional relation, as the model predicts. Also as predicted, the turnover-

performance relation is stronger for funds trading less-liquid stocks and funds likely

to possess greater skill. Turnover is correlated across funds. The common component

of turnover is positively correlated with proxies for stock mispricing. Turnover of

similar funds helps predict a fund’s performance.

MUTUAL FUNDS INVEST TRILLIONS of dollars on behalf of retail investors. The

lion’s share of this money is actively managed, despite the growing popularity

of passive investing.1Whether skill guides the trades of actively managed

funds has long been an important question, given active funds’ higher fees and

∗ˇ

Luboˇ

sP

´

astor is at the University of Chicago Booth School of Business. Robert F. Stambaugh

and Lucian A. Taylor are at the Wharton School of the University of Pennsylvania. P´

astor and

Stambaugh are also at the NBER. P´

astor is additionally at the National Bank of Slovakia and

the CEPR. We are grateful for comments from Jonathan Berk, Justin Birru, David Chapman,

Alex Edmans, Gene Fama, Miguel Ferreira, Francesco Franzoni, Vincent Glode, Todd Gormley,

Christian Hansen, Marcin Kacperczyk, Fabio Moneta, David Musto, Jonathan Reuter, Sergei

Sarkissian, and Clemens Sialm, from the audiences at the 2016 AFA, 2015 WFA, 2015 EFA,

2015 FIRS, 2016 IPC Winter Research Symposium, 2015 Conference on Advances in the Analysis

of Hedge Fund Strategies, 2015 Finance Down Under conference, 2015 Liquidity Risk in Asset

Management conference, 2015 Nova BPI Asset Management Conference, 2015 Q Group, and 2014

German Finance Association conference, and the following universities and other institutions:

Aalto, BI Oslo, Cass, Cheung Kong, Chicago, Columbia, Copenhagen, Dartmouth, Duke, Georgia

State, Houston, Imperial, Indiana, Mannheim, McGill, Michigan, NBIM, NHH Bergen, SAIF,

Tsinghua PBCSF, Tsinghua SEM, Vanderbilt, and Wharton. We are also grateful to Yeguang Chi

and Gerardo Manzo for superb research assistance. This research was funded in part by two centers

at Chicago Booth, the Fama-Miller Center for Research in Finance and the Center for Research in

Security Prices, and by two centers at Wharton, the Rodney L. White Center for Financial Research

and the Jacobs Levy Equity Management Center for Quantitative Financial Research. Stambaugh

and Taylor have no conflicts of interest to disclose. P´

astor is a member of the governing board of

the National Bank of Slovakia, whose responsibilities include serving as the principal regulator of

mutual funds in Slovakia. Yet, the Bank has no stake in this research, no benefit from it, and no

influence upon it. The views in this paper are the responsibility of the authors, not the institutions

they are affiliated with.

1As of 2013, mutual funds worldwide have about $30 trillion of assets under management,

half of which is managed by U.S. funds. About 52% of U.S. mutual fund assets are held in equity

DOI: 10.1111/jofi.12509

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1484 The Journal of Finance R

trading costs. We take a fresh look at skill by analyzing time variation in active

funds’ trading activity. We explore a simple idea: a fund trades more when it

perceives greater profit opportunities. If the fund has the ability to identify

and exploit those opportunities, then it should earn greater profit after trading

more heavily.

We formalize this idea by developing a model of fund trading in the presence

of time-varying profit opportunities. Each period, funds identify opportunities

to establish positions that yield profits, net of trading costs, in the subsequent

period. A fund’s optimal amount of turnover maximizes its expected profit, con-

ditional on equilibrium prices. Profit opportunities vary over time and jointly

determine turnover and performance. A fund trades more in periods when it

has more profit opportunities. Our model’s key implication is a positive time-

series relation between fund turnover and subsequent fund performance.

Consistent with the model, we find that a fund’s turnover positively predicts

the fund’s subsequent benchmark-adjusted return. This new evidence of skill

comes from our sample of 3,126 active U.S. equity mutual funds from 1979

through 2011. The result is significant not only statistically but also economi-

cally: a one-standard-deviation increase in turnover is associated with a 0.66%

per year increase in the performance for the typical fund. Thus, funds seem to

know when it is a good time to trade.

We focus on the time-series relation between turnover and performance

for a given fund. In contrast, prior studies ask whether there is a turnover-

performance relation across funds. The evidence on this cross-sectional re-

lation is mixed. For example, Elton et al. (1993) and Carhart (1997) find a

negative relation, Wermers (2000), Kacperczyk, Sialm, and Zheng (2005), and

Edelen, Evans, and Kadlec (2007) find no significant relation, and Dahlquist,

Engstr¨

om, and S¨

oderlind (2000) and Chen, Jagadeesh, and Wermers (2000)

find a positive relation. In accord with this mixed message, our sample delivers

a cross-sectional relation that is positive but only marginally significant.

Consistent with the empirical results, our model predicts that the time-

series relation between turnover and performance should be stronger than the

cross-sectional relation. The reason is that a given trade’s cost reduces current

return, whereas its profit increases future return. Trading costs therefore do

not dampen the time-series turnover-performance relation as much as they

dampen the cross-sectional relation, for which the timing of profit and trading

cost is irrelevant.

Our model also predicts that funds trading less-liquid stocks should have a

stronger time-series relation between turnover and performance. The turnover

of such funds optimally responds less to profit opportunities, so a given change

in turnover implies a greater change in profit opportunities. Consistent with

this prediction, we find that funds holding stocks of small companies, or small-

cap funds, have a significantly stronger turnover-performance relation than

do large-cap funds. Similarly, we find a stronger relation for small funds than

funds, and 81.6% of the equity funds’ total net assets are managed actively (Investment Company

Institute (2014)).

Do Funds Make More When They Trade More? 1485

large funds, consistent with the ability of smaller funds to trade less-liquid

stocks, given that smaller funds tend to trade in smaller dollar amounts.

The model also predicts a stronger turnover-performance relation for funds

that are more skilled. Intuitively, if a less-skilledfund trades on profit opportu-

nities that are not really there, then some of the fund’s turnover is unrelated to

future performance. Under the plausible assumption that more-skilled funds

charge higher fees, the turnover-performance relation should be stronger for

more expensive funds. That is indeed what we find.

We find strong evidence of commonality in fund turnover. Turnover’s com-

mon component appears to be related to mispricing in the stock market.

Average turnover across funds—essentially the first principal component of

turnover—is significantly related to three proxies for potential mispricing: in-

vestor sentiment, cross-sectional dispersion in individual stock returns, and

aggregate stock market liquidity. Funds trade more when sentiment or dis-

persion is high or liquidity is low, suggesting that stocks are more mispriced

when funds collectively perceive greater profit opportunities. We also find that

commonality in turnover is especially high among funds sharing similar char-

acteristics, suggesting more comovement in profit opportunities across similar

funds.

Average turnover of similar funds positively predicts a fund’s future return,

even when we control for the fund’s own turnover.This predictive relation is sig-

nificant: a one-standard-deviation increase in similar funds’ average turnover

is associated with a 0.43% per year increase in fund performance. The relation

is weaker when average turnover is computed across all funds, consistent with

less commonality among dissimilar funds.

The predictive ability of average turnover is consistent with the pres-

ence of error in our empirical measure of an individual fund’s turnover.

This measure aims to exclude trades arising from a fund’s inflows and out-

flows, thereby focusing only on trades arising from the fund’s decisions to re-

place some stocks with others, but this objective can be accomplished only

imperfectly. Due to commonality in turnover, average turnover of similar

funds helps capture a fund’s true turnover, thereby helping predict the fund’s

performance.

Average turnover should also predict returns if funds trade suboptimally in

that only a portion of their trading exploits true profit opportunities. If those

opportunities are correlated across funds while funds’ trading mistakes are not,

then higher average turnover indicates greater profit opportunities in general.

Any opportunity identified by a given fund is likely to be more profitable if

there is generally more mispricing at that time, as indicated by other funds’

heavy trading. Our model formalizes this story. Suboptimal trading can also

explain the superior predictive power of similar funds’ average turnover, as

that turnover reflects especially relevant profit opportunities—those shared by

similar funds.

The literature investigating the skill of active mutual funds is extensive.

Average past performance delivers a seemingly negative verdict, since many

studies show that active funds have underperformed passive benchmarks, net