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January 2016
The Dirty Little Secret of Passive Investing
by Michael Aked, CFA
Passive investments have a dirty little secret: Their
transactions in the market. After all, an index is just
gross returns are materially depressed by implicit
a model portfolio, and it cannot be implemented above
implementation costs. You don’t see these costs in
and apart from the laws of managing money. To attract
performance attributions, unbundled management
sellers for stocks you wish to buy, you have to pay
fees, or even standard trading cost analyses. But as
more. To attract buyers of stocks you wish to sell, you
we recently pointed out in a Journal of Trading article
(Aked and Moroz, 2015), the fact that they are
unobserved doesn’t mean they don’t exist, can’t be
measured, or shouldn’t be taken into account when
selecting an index strategy. In particular, the
implementation of popular capitalization-based
indices is not costless; indeed, as a percentage of
aggregate assets, their implicit trading cost is
meaningfully higher than that of well-designed smartbeta offerings.
need to ask for less.
Market players are aware of the practice of paying
indexers to accept the market close price. Blume and
Edelen (2004) explain it this way:
“Counterparties such as hedge funds or dealers
can enter into bilateral agreements with indexers
to trade at a yet unknown closing price on the
change date and agree to share part of their
expected trading profits with the indexers through
a better net price than the closing price.” (Page 41)
Hidden Trading Costs
Implicit trading costs are the loss of performance due
Blume and Edelen’s research confirms that indices
to transactions occurring at prices that would not have
bear implementation costs that are just right to
prevailed if investors didn’t need to enter trades.
compensate liquidity providers for the risks they would
assume by providing tradable securities at the closing
Decades of research have demonstrated that the cost
of changes in the S&P 500 Index is significant and
increasing.1 Consistent with earlier academic findings,
Chen, Noronha, and Singal (2004) determined that,
from announcement day to the effective date, the
additional cost of a new index holding rose from 3%
in the 1976–1989 period to about 9% in the 1989–2000
period. In our own research, for the 2011–2013 period,
the one-year returns earned by additions to the S&P
500 were on average 13% higher than the returns of
price on index rebalance days.
Indices Are Not Passive
Because indices are, to varying degrees, incomplete
market portfolios, index construction amounts to
active management.2 Providers choose index holdings
by size, liquidity, sector, geography, profitability, and
the like. Index designs run the full gamut, from highly
systematic, rules-based procedures to largely
discretionary, committee-based processes. In every
case, the explicit selection criteria, weighting rules,
existing index constituents. Investors pay a substantial
and committee decisions directly affect indices’ active
premium just because a stock becomes a member of
shares. Index construction methodologies may seem
the index.
arcane, but their effects are far from inconsequential.
This outcome is not unique to the S&P 500. It applies
Capitalization-based indices are inherently biased
to the management of any pool of money that requires
toward including more liquid, higher-priced growth
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2) January 2016
SIMPLYSTATED
stocks and stripping low-priced value stocks of their
Appendix: Trading Cost Calculations
index certification. Conversely, indices that are not
Implicit trading costs cannot be observed directly
price-linked trade into depressed stocks and out of
but they can be estimated. As to measure is to
high-flying ones. Over the same 2011–2013 period
manage, let’s outline the drivers behind our implicit
covered by our internal S&P 500 analysis, we find that
securities that our fundamentally weighted RAFI™
indices wish to buy have fallen by approximately 13%
more than their peers. Liquidity providers have no
incentive to pump the price of index holdings that are
not weighted by market cap, because doing so would
reduce—not increase—their potential profits.
trading cost model :
Implicit trading cost = k
With some simplifying assumptions, five factors are
responsible for the implicit costs associated with trading
a strategy:
•
value of shares traded daily across all stocks in
indices is their low market impact. Market capitalization
the universe, scaled by a constant.
closely tracks liquidity. Moreover, cap-weighted indices
•
turnover. This factor reflects the obvious fact
changes. Thus, by design, they minimize this particular
that if there were no trades, there would be no
type of cost.
be viewed as costless, especially in aggregate. Our
Effective turnover, the second factor, is impacted
by both replacement turnover and reweighting
only trades they require are occasioned by index
Nonetheless, capitalization-based indices should not
The first factor is base impact, which is the ratio
of the assets under management to the dollar
One of the attractive features of capitalization-based
are self-adjusting; they do not require rebalancing. The
Base impact × Effective turnover × Tilt
Coverage × Rebalance frequency
implementation cost.
•
The third factor is tilt, the weighted-average ratio
of the actual weight of a fund to the volume
model indicates it would take over $1.1 trillion in assets
weight of the index, with a volume-weighted
for a RAFI index to match the current implicit
index having the lowest implementation cost.
implementation costs of capitalization-based indices.3
•
constituents to the total trading volume of the
Non-capitalization indices have higher implementation
entire universe is the fourth factor, which we call
costs on a dollar-for-dollar basis than capitalization-
coverage. A portfolio that contains every stock
based indices. This we do not contest. But it’s lunacy
in the universe has coverage of 1.
to believe that the implementation of popular
capitalization-based indices is costless, that their
The ratio of the total trading volume of the index
•
The fifth factor is rebalance frequency. More
negative selection and weighting bias is zero, or that
frequent rebalancing, all other things being equal,
their implicit trading cost as a percentage of aggregate
is associated with lower implicit intraperiod market
assets is currently below that of well-designed smart-
impact costs. The rebalance frequency applies at
beta offerings.
the individual stock level, not at the index level.
Endnotes
1.
2.
See Arnott and Vincent (1986); Lynch and Mendenhall
(1996); and Kappou, Brooks, and Ward (2010).
Even broad cap-weighted indices can be considered a
form of active management, not so much against the
capital markets they purport to represent, but against the
macroeconomy. Arnott, Beck, and Kalesnik (2015) write,
“From a macro-economy perspective, the cap-weighted
market is making obvious and sometimes large active bets,
presuming (using a 2014 example) that Apple will be the
© Research Affiliates, LLC
3.
largest source of risk-adjusted profits in the world, delivered
to its shareholders in the decades ahead. Perhaps true. But
it is not yet true. So, from a macroeconomic perspective,
the market is making an active bet on Apple today, relative
to the much smaller current macroeconomic footprint that
it occupies in the U.S. and global economy.” Page 63.
In this example, we do not give credit for the far-superior
incentive alignment for liquidity providers for RAFI
indices, nor for the selection and weighting criteria of the
RAFI indices.
3) January 2016
SIMPLYSTATED
References
Aked, Michael A., and Max Moroz. 2015. “The Market Impact
of Passive Trading.” Journal of Trading, vol. 10, no. 3
(Summer):5–12.
Arnott, Robert, Noah Beck, and Vitali Kalesnik. 2015. “Rip Van
Winkle Indexing.” Journal of Portfolio Management, vol. 41, no.
4 (Summer):50–67.
Arnott, Robert D., and Stephen J. Vincent. 1986. “S&P Additions
and Deletions: A Market Anomaly.” Journal of Portfolio
Management, vol. 13, no. 1 (Fall):29–33.
Blume, Marshall E., and Roger M. Edelen. 2004. “S&P 500
Indexers, Tracking Error, and Liquidity.” Journal of Portfolio
Management, vol. 30, no. 3 (Spring):37–46.
Chen, Honghui, Gregory Noronha, and Vijay Singal. 2004. “The
Price Response to S&P 500 Index Additions and Deletions:
Evidence of Asymmetry and a New Explanation.” Journal of
Finance, vol. 59, no. 4 (August):1901–1930.
Kappou, Konstantina, Chris Brooks, and Charles Ward. 2010.
“The S&P500 Index Effect Reconsidered: Evidence from
Overnight and Intraday Stock Price Performance and Volume.”
Journal of Banking & Finance, vol. 34, no. 1 (January):116-126.
Lynch, Anthony W., and Richard R. Mendenhall. 1996. “New
Evidence on Stock Price Effects Associated with Charges in
the S&P 500 Index.” NYU Working Paper. Available at http:/
/
papers.ssrn.com/sol3/papers.cfm?abstract_id=1298790.
ABOUT THE AUTHOR
Mike Aked is a senior member of the Research and Investment Management group. He concentrates his efforts on research and
implementation of global tactical asset allocation strategies.
Previously, he served as a managing director at the University of Virginia Investment Management Company, where he worked on
portfolio and risk management. He also has worked for Sunsuper, an Australian superannuation fund, and at UBS Global Asset
Management across four continents.
Michael received a BA (with honors) in applied mathematics from the University of Sydney, an MS in statistics from the University
of Virginia, and an MS in financial mathematics from the University of Chicago. He is a member of CFA Institute and of the CFA
Society of Washington DC.
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