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GLOBAL ECONOMIC
PERSPECTIVE
Trump Portfolios
February 1, 2017
The “improbable” election of Donald J. Trump as
the 45th President of the United States has had a
significant and positive impact on the financial
markets. The market upswing has led many to
wonder whether investors are getting carried
away or whether the markets see something that
analysts and economists are not seeing. For the
latter, it is hard to explain the recent market
behavior in terms of the economic fundamentals.
After the election, economists surveyed by The
Wall Street Journal added only 0.3 percentage
points to their prior real GDP growth forecast for
the next two years. At its December meeting, the
Fed barely changed its real GDP forecast. In short,
the establishment’s forecast would argue that if
the fundamentals improved after the election, they
did not do so by much. If not the fundamentals,
what has changed?
We believe that the election of Donald Trump
marks a policy inflection point. Even if tax rates
and the regulatory burden do not decline by much,
they denote quite a change in the trend of rising
regulations and rising marginal tax rates produced
by Obamanomics. If incentives matter, that alone
is sufficient to produce an upward revision in the
market’s valuation. The positive valuations also
suggest that the market expects the tax rate
reduction, regulatory relief, and infrastructure
spending to have a positive impact on the pace of
economic activity. One possible area of concern
is foreign trade, where the mercantilist views
expressed by the President are worrisome and we
believe they will tend to offset the benefits of the
other policies.
Identifying the Winners and Losers
At this point, we take the view that the Trump
policies, overall, will have a positive effect on the
economy. As time goes by, the details of the
policies of Trump administration will be revealed
and the policy uncertainty will be reduced. So far
it seems that the president meant what he said and
said what he meant. The uncertainty reduction
removes one possible source of error in the design
of a portfolio aimed at identifying the sectors and
or stocks likely to benefit from the Trump
administration. Where to start? During the
presidential campaigns, it is customary for the
brokerage houses and money managers to develop
portfolios expected to benefit from the policies of
the different candidates. That is a good starting
point and, as suggested earlier, once the details of
the president’s policies become better known, the
portfolio is adjusted accordingly.
Traditionally, the selection of the stocks and asset
classes identified as winners and losers focuses on
the direct impact of the policies on the individual
companies. Let’s take the case of a lower
regulatory burden and a lower corporate tax rate.
Regulatory Burden: One simple approach to
focus on the beneficiaries of the reduction in the
regulatory burden is to identify the companies that
are most affected by the regulations, as well as
those least affected. The latter will be included in
the loser’s groups, while the former will be
designated winners of the regulatory easing. One
can then broaden the analysis to focus on sectors
with the most and least regulated companies. The
ultimate extension—one that we favor—is to take
a macroeconomic perspective and extend the
analysis to an asset class. The lower regulations
will favor U.S. companies relative to the rest of
the world. Within the domestic companies, the
smaller capitalization companies that cannot
avoid the regulations will benefit the most from
the lower regulations. Hence, early on our
approach would favor the smaller capitalization
stocks.
Corporate Tax Rates: A reduction in corporate
tax rates will increase the after-tax cash flows of
corporations and thereby increase their
valuations, even if they do not change their
behavior. The gains will be larger for the
companies with the higher average taxes. Hence,
that is the first step in identifying the stocks that
will benefit from the lower tax rates. Also, to the
extent that the taxation of foreign earnings is
altered, information on the composition of the
earnings may provide an additional screen. If one
believes the “America First” slogan, then it seems
reasonable to assume that the larger the share of
domestic earnings, the greater the benefit from the
America First policies. Putting it all together, the
corporate screen is straightforward: focus on
companies with the highest average tax rates and
the largest share of domestically generated
earnings.
Monetary and Credit Policy: In the aftermath of
the financial crisis, the Fed adopted a policy of
keeping interest rates low as far as the eye can see.
We contend that in doing so, the Fed distorted the
capital and credit markets. Now, as the Fed
returns to normalcy during the Trump
administration, the effects of these distortions will
be reversed and those who benefited the most
from the low interest rate policies are likely to
underperform.
The Dollar and Protectionism: We contend that
during the early stages the pro-growth policies
will increase the expected real rate of return. That,
in turn, will result in a capital inflow, a dollar
appreciation, and an outperforming U.S. stock
market. Unfortunately, the strong dollar will also
fuel the protectionist fires and thereby increase
the likelihood of protectionist policies. In our
opinion, these policies will have a negative impact
on the economy and the markets. The strong
dollar and protectionist forces tend to cancel each
other out. The impact on the economy will be the
net of the two. Whichever one dominates depends
on the portfolio of policies adopted by the Trump
administration. If the economy picks up, we
expect the dollar effect to dominate. In contrast, if
the economy slows down, we expect that the
protectionist forces have won the day.
Portfolio Construction Issues
In the previous section, we outlined several
screens that we believe to be quite useful in the
identification of stocks likely to benefit from the
proposed Trump Administration economic
policies. The screens are focused on the direct
impact of the policy changes on the after-tax
earnings (and thus valuation) of the different
companies and asset classes. To obtain the
individual companies’ estimates, one needs
information on the earnings, their composition,
i.e. domestic versus international, as well as the
nature and amount of taxes paid.
The previous paragraph describes a good first step
toward improving investment results. The
downside is that there are data requirements. That
data may not be readily available to some
investors or they may not have the time to perform
such an analysis. The question is whether there is
a short cut? The answer is an affirmative one. We
believe that a top-down, macroeconomic
approach could provide a short cut that would get
us to a superior portfolio without the need to
collect all the individual company information
required by the direct approach. It must also be
pointed out that the direct approach does not take
into consideration dynamic effects that may
emanate from the policy changes being
contemplated. The lower tax rates will result in an
economic expansion and, all else the same, the
firm that experiences the greater expansion will
also experience the greater gain in profits.
Unfortunately, not everything else is the same.
The ability to pass a price increase forward or
backward will be critical to the ultimate impact on
the profitability of the companies. For example, in
the case of elastic sectors, where there are no
barriers to entry, competition will dissipate the
profits. In this case the consumers of the product
will be the ultimate beneficiary. On the other
hand, for inelastic industries that are shielded
from competition through barriers of entry
resulting from natural or technological reasons,
they will retain the increased profits resulting
from the lower taxes and regulations. These
companies will experience an above-average
performance and should be included in the Trump
Portfolio. The question for the investor will be
how to identify these companies.
There is an easy way to identify the companies
that will potentially benefit from the Trump
policies. One way is to let the market tell us. The
answer can be found by looking at periods in the
past where the economic environment has been
like the one we expect. If a perfect match does not
exist, we can look at time periods where the
different indicators behaved the way we expect
these indicators to behave as a result of the Trump
policies. The rationale is that similar economic
disturbances will have similar responses. Hence,
those who outperformed during the relevant
periods are likely candidates to outperform in the
current environment. Next, we focus on the
information we need to identify the relevant
environment.
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Our outlook calls for a rising slope for the yield
curve and a declining spread for corporate bond
yields. The expected increase in the slope of the
yield curve reduces the likelihood that the long
end of the yield curve will outperform the short
end. The declining spread points to a relative
outperformance of the corporate bonds over fixed
income, suggesting that equities are likely to
outperform fixed income instruments. Yet that
does not answer the issue as to what happens to
the inflation rate relative to the real GDP growth
rate. Again, more information is needed.
The dollar reflects the price of two currencies and,
under some general conditions, one can show that
a dollar appreciation can be generated by one of
three different variables:
1. A declining inflation rate relative to the rest of
the world.
2. A rising real rate of return relative to the rest
of the world.
3. A decrease in the risk premium relative to the
rest of the world.
The dollar appreciation is a blow to the
inflationistas, especially if one considers the fact
that the rest of the world is not exhibiting rising
inflation or rising inflation expectations. Given all
the analysis in the press and recent international
developments, it is hard to argue that the Trump
victory brought calmness to the world economy
and thus lowered the U.S. risk premium relative
to the rest of the world. Thus, the process of
elimination leaves the real rate of return as the
logical explanation for the rising interest rates and
a strong dollar.
The Stock Universe: We obtained total return
information going back to 1993 for the current
constituents of the Russell 1000. We then
proceeded to eliminate the individual stocks that
did not have returns for each year. That process
left us with 284 stocks with a full set of annual
data.
The Time Periods: The sample period for the
different cycles is limited by our access to stock
returns, which only goes back to the early 1990s.
Yet during that time there is a wide range of
experiences that lets us extract the information we
need from mostly non-overlapping cycles.
Looking at the data for the different economic
environment indicators, we identified a mostly
non-overlapping cycle for each of the indicators
in question—the dollar, the slope of the yield
curve, the corporate bond spread, and the Fed as
Table 1: The Cycles
Dollar Cycle
Slope of the Yield Curve
Corporate Bond Spread
Fed Low Interest Rate
Years
Change
2003-08 Falling
1993-99 Falling
1997-2001 Rising
2009-15
Low
far as the eye can see low interest rate policy. The
time periods for the different cycles can be found
in table 1.
The Classification and Performance
Once the cycles were identified, the performance
of the individual stocks during each of the cycles
was calculated and the stocks were ranked in
ascending order and divided into 10 portfolios
consisting of approximately an equal number of
stocks. In cases where the cycle was a mirror
image of our forecast regarding the environment
we foresee during the Trump administration, we
reversed the ranking.
The dollar cycle considered in the classification
method was one of a declining dollar. It is the
mirror image of what we expect early on during
the Trump administration. Our analysis expects
that those stocks that outperformed during the
dollar decline cycle would underperform during
the dollar increase cycle. Therefore, reversing the
decile ranking obtained during the dollar decline
cycle should be a good guide in the identification
of individual stocks likely to outperform as a
result of the dollar surge.
The average return generated by each of the
deciles since November of 2016 suggests that the
dollar screen does not reveal any systematic
pattern. There is no significant difference between
the top 5 deciles and the bottom 5 deciles. Does
this mean that the dollar screen is ineffective? Or
is there a possible explanation for the results? We
lean towards the latter. If the Trump
administration is concerned with competitiveness,
whenever the dollar rises, the propensity of the
administration to adopt protectionist measures
will increase, thereby undoing the effect of a
strong dollar on the economy and financial
markets. The results reported in the first column
of table 2 are consistent with this interpretation.
The slope of the yield curve cycle identified is one
where the slope of the yield curve declined, the
opposite of what we are looking for in the near
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future. Hence, as before, we expect that the stocks
that outperformed during the declining slope
cycle will underperform during the rising slope
cycle. The performance of the decile ranking of
the stocks in the universe are reported in the
second column of table 2. The data is clearly
consistent with our forecast. The half of the stock
universe expected to underperform, i.e. deciles 1
through 5, posted a 9.52% average return versus a
10.77% average gain for the 284 stock universe.
In contrast, the stocks in the decile expected to
outperform gained an average of 12.02%, well
above the sample average. More importantly,
looking at the individual deciles, it is apparent that
the first 4 deciles posted single digit returns, while
the remaining decile posted double digit returns.
The results suggest that there may be something
to our approach.
The corporate bond spread cycle used in the
classification is one where the spread rose, which
is what we expect to see happening during the
early part of the Trump administration. In this
case a simple ranking of the decile will serve as a
good proxy for the ranking of the individual
stocks. The results of the screen are posted in the
third column of table 2. The average performance
is as expected. The first five deciles posted an
average gain of 8.47%, while the portfolio
consisting of the stocks in deciles 6 through 10
gained 13.09%. Comparing the spread results to
the slope results, it is apparent that the spread
portfolio generates a higher differential return,
while the spread appears to produce more
consistent results across deciles.
The return to normalcy cycle should be a mirror
image of the experience of the last few years.
Again the data seems to support this view. The
results reported in column 4, table 2 show that the
portfolio consisting of the stocks in deciles 1
through 5 underperform the portfolio consisting
of the stocks in deciles 6 thorough 10. However,
the differential returns (9.61% versus 11.63%) are
smaller than that produced by the corporate
spread and the slope of the yield curve.
Putting It All Together
During the classification process, we took great
care in making sure that the overlap among the
different cycles was minimized. This way we
hoped to capture the differential impact of the
different environment or factors on the individual
stock returns. We also assume that, to the extent
that the cycles and factors are different, there is
some degree of orthogonality. This is important
because if the factors are different, then the
different factors will characterize different
components of the economic environment. By
combining them, one may be able to replicate the
environment we foresee.
One simple test of this hypothesis is to combine
the different screens into a single screen and
examine the performance of the portfolios. The
results of this exercise are reported in the last
column of table 2. The portfolio consisting of the
stocks in deciles 1 through 5 underperform the
portfolio consisting of the stocks in deciles 6
through 10. More importantly, notice that
combining ranking of the different factors
produces a portfolio of deciles 1 through 5 that
generates a lower return than any of the other
screens, while the decile 6 through 10 portfolio
generates the second highest return of all screens.
T able 2 : Po rtfo lio R e turns D uring D iffe re nt C ycle s
1
2
3
4
5
6
7
8
9
10
D olla r
20.59
11.36
4.56
9.13
8.08
8.20
12.00
10.34
9.40
13.59
Slope
9.71
8.78
5.60
7.21
16.32
14.20
12.14
10.63
10.95
12.19
Sprea d
6.22
7.79
10.63
6.13
11.56
11.14
14.45
13.93
10.33
15.62
FED
6.05
9.59
9.61
10.93
11.88
10.11
11.43
10.73
11.45
15.91
B ottom D e cile s
Top D ec ile s
10.74
10.71
9.52
12.02
8.47
13.09
9.61
11.93
D e cile
D e cile
D e cile
D e cile
D e cile
D e cile
D e cile
D e cile
D e cile
D e cile
A ll C ycle s
Ex-D ollar A ll C ycle s
7.32
4.34
8.72
10.84
8.62
7.90
8.09
13.15
13.25
8.34
11.82
13.44
12.67
13.29
11.77
9.70
10.91
11.24
14.57
15.49
9.20
12.35
8.91
12.63
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This result supports the additivity and value added
of combining the different screens.
One negative aspect of the results reported in the
last column of table 2 is that the rank of decile
performances is not quite what we anticipated.
We expected decile 1 to post the lowest
performance, decile 2 the second lowest, and so
on. Is it possible that the relative ranking is greatly
impacted by noise in the system? Recall that the
dollar screen did not appear to be systematic. In
order to test this possibility, we recalculated the
rankings without the dollar screen. The results are
reported in the next to last column. Notice that
the relative ranking appears to conform to our
expectations. While not perfect, the returns do rise
as the deciles increase. This is reassuring.
However, including the dollar screen produces a
greater differential between the two portfolios in
question. The moral of the story seems to be that
for those interested in the broadest possible
portfolio, the sum of all the screens is better.
Improving the Results
The methodology outlined here uses a top-down
approach and we view it as a short cut to get us to
a universe of stocks likely to benefit from the
environment. The next issue is figuring out how
to improve on these results. We believe that the
answer is a bottom-up one. Knowledge of
individual companies’ average tax rates, cost of
capital, and share of earnings generated outside
the U.S. can be used to significantly improve the
results reported here.
Victor A. Canto, Ph.D.
Chief Economist &
Managing Director Global Strategies
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