Morningstar - Q4 2020 - 59

market typically look quite different from this
theoretical construct.
Disappointing Results
While this theoretical long-short momentum
strategy paid off, most broad, long-only largeand mid-cap U.S. momentum funds have
disappointed. While some have beaten the market,
most have a growth tilt and have fared less
well against the Russell 1000 Growth Index. In fact,
they all lagged that benchmark over the trailing
three- and five-year periods through August
2020 ( E X H IB IT 2 ). During that time, the theoretical
momentum strategy continued to pay off.

As EX H IB IT 2 illustrates, there was a wide range
in returns and active risk (as measured by tracking
error against the Russell 1000 Growth Index)
among these funds. That's because there
are important differences in portfolio construction,
ranging from how they define momentum to
how aggressively they pursue it.
Lost in Translation
Clearly, something is getting lost in translation.
This isn't entirely because of the practical
challenges of implementing momentum,
like transaction costs or these funds' long-only
portfolios, though those factors play a role.
Most of these funds have only modest exposure
to the classic academic factor, which
helped performance but wasn't enough to
overcome other headwinds. These include stylistic
differences between these funds and the
Russell 1000 Growth Index and fund-specific
considerations (alpha).

Stripping out the impact of nonmomentum style
tilts, only two of seven funds would have
outperformed over the trailing five years through
June 2020 (Invesco S&P MidCap Momentum
ETF XMMO and iShares Edge MSCI USA
Momentum Factor ETF MTUM). Only three of 11
would have outperformed over the past three
years (the two aforementioned funds and Invesco
S&P 500 Momentum ETF SPMO).
Many of the other funds underperformed
considerably after controlling for their style tilts
(they had negative alphas). This is partially
attributable to fees, transaction costs, and unique
portfolio construction choices that didn't pay
off during this time. However, it's important not to
read too much into a fund's alpha over a short
period, as alphas tend to fluctuate considerably
over time. Instead, it's better to focus on each
fund's portfolio construction approach and how
well it harnesses the classic momentum effect.
None of the momentum funds in this group
follow the same portfolio construction approach

as the classic momentum factor, which tends
to dilute their exposure to it. For example,
many rebalance less frequently than once a month
and apply buffers to mitigate transaction
costs. Others make risk adjustments in their
stock-selection approach.
That's not necessarily bad. Those adjustments
could improve performance and lead to
more-practical portfolios that investors can stick
with. However, this underscores that it is not
appropriate to assume all momentum funds
equally benefit from the classic momentum effect.
They require further due diligence.
Best Practices
The best momentum funds effectively capture the
standard momentum effect documented in the
literature while taking steps to mitigate transaction
costs and risk. Invesco S&P 500 Momentum
ETF and iShares Edge MSCI USA Momentum Factor
ETF, which has a Morningstar Analyst Rating
of Silver, do well on these fronts. And both charge
low fees.

EXHIBIT 1

Momentum Payoff (in Theory) Buying the fifth of U.S. large-cap stocks with the
strongest momentum each month and shorting the fifth with the worst momentum
would have returned 2.4% annually before transaction costs.
Growth of $1

$2.5

Most of these funds faced stylistic headwinds.
For example, during these periods traditional
growth investing paid off handsomely, but
most of these had less pronounced growth tilts
than the Russell 1000 Growth Index, which
hurt performance.
That said, momentum investors shouldn't
sweat underperformance that comes from
stylistic differences between a fund
and its benchmark, like differences in size and
growth orientation or market risk. Those
differences are largely unrelated to the efficacy
of the momentum strategy.

2.0
1.60

1.5

1.0

0.5
0
10/2000

10/2004

10/2008

10/2012

10/2016

Source: French Data Library, author's calculations. Data as of 06/30/2020.

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