Model Portfolio & SMA Strategists Showcase - Flipbook - Page 26
SMAs & MODEL PORTFOLIOS
methodology applied consistently
across a broad universe of securities.
Dimensional Fund Advisors is the
clearest real-world anchor for this
category. Founded by researchers
trained under Eugene Fama at the
University of Chicago, and still guided
by an investment research committee
co-chaired by Kenneth French,
Dimensional built its entire investment
philosophy around empirically
documented factor premiums, size,
value, and profitability chief among
them, years before “factor investing”
became industry-standard vocabulary.
The firm now offers factor-based
SMAs directly, alongside its longstanding mutual fund and ETF lineup,
distributed through the same thirdparty SMA platforms discussed
elsewhere in this guide.
A factor strategy doesn’t need to
come from Dimensional specifically to
be legitimate, but Dimensional’s track
record and academic grounding make
it a useful reference point for what
disciplined, evidence-based factor
investing is supposed to look like,
against which other factor strategies
can reasonably be compared.
This has become common enough
that it’s worth advisors recognizing on
sight. Earnings-revision-based equity
ADVISOR LENS
Why state matters as
much as the bond
A client in a high-tax state can often
do better in a municipal SMA built
specifically around that state’s own
issuance, capturing both the federal
and state exemption at once. A national
municipal bond fund can’t replicate
this. Worth asking a fixed-income SMA
provider directly whether they build statespecific ladders.
selection, quantitative multifactor
models, and similar approaches are all
factor strategies at their core, whether
or not a given provider markets
them using that specific vocabulary.
Evaluating one means asking which
specific factors the strategy targets,
how those factors are measured and
weighted, and, critically, whether
the strategy has genuine long-term
evidence behind the factor premium
it’s harvesting, or whether it’s chasing a
factor that happened to work well in a
recent, specific market environment.
A manager holds a stock, collects option
premium by selling a call above the
current price, and the client earns extra
income on top of dividends. If the stock
rallies past that strike, the upside above
it belongs to whoever bought the option,
not the client. Income now, capped
upside later: a disclosed trade, not a
hidden one.
That last distinction is exactly the kind
of thing the performance chapter’s
skepticism about performance-chasing
was built to catch (p. 29), applied here
to factor selection rather than manager
selection.
rather than continuously. The appeal
is consistency and transparency. The
rules are the same every rebalance,
removing the discretionary judgment
call that makes some tactical strategies
hard to evaluate in advance.
Tactical strategies are built to make
more significant shifts between asset
classes and sub-classes in response to
changing market conditions, explicitly
aiming to limit losses during downturns
and capture upside during recoveries.
The mechanism varies by provider.
Some use quantitative signals, and
some blend quantitative screens with
discretionary manager judgment, but
the shared premise is that meaningful
deviation from a static allocation,
timed well, can improve risk-adjusted
outcomes over a full cycle.
The trade-off is the same one that
applies to any rules-based system. It will
underperform in market environments
where the specific rules it follows are out
of favor, and a manager can’t override
the system’s signal just because their
judgment disagrees with it that month.
Evaluating one of these strategies
means evaluating the rules themselves,
rather than evaluating a manager’s
individual market calls the way the
performance chapter discusses for
discretionary tactical strategies (p. 29).
A specific and increasingly common
form of tactical strategy is worth
distinguishing from discretionary
tactical management generally: rulesbased sector rotation built entirely
from ETFs. Rather than a manager
making discretionary judgment calls
about which sectors look attractive,
these strategies use a quantitative
ranking system, such as momentum,
relative strength, or earnings trends, to
systematically rotate a portfolio’s sector
or asset-class weightings, typically
rebalancing on a defined schedule
The trade-off between core, factor, and
tactical approaches is not subtle. The
further a strategy moves from core, the
more timing or model risk it introduces.
A tactical manager who correctly
reduces equity exposure ahead of a
downturn looks brilliant. The same
manager reducing exposure ahead of a
rally that never reverses looks like they
cost the client return for no benefit. A
later chapter covers how to evaluate
that trade-off honestly rather than
retroactively (p. 29), which is where
most of the industry’s performance
marketing goes wrong.
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QUICK MATH
The cap,
illustrated
