EM EQUITY ALLOCATION MODEL FOR Q1 2018

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  • Passage of the US corporate tax cut has boosted the global growth outlook
  • The correlation between EM and DM stocks is currently 0.48
  • Our 1-rated grouping (outperformers) for Q1 2018 remains steady with Hong Kong, Singapore, Czech Republic, Korea, and China
  • Our 5-rated grouping (underperformers) for Q1 2018 consists of Colombia, India, Brazil, Mexico, and South Africa
  • Since our last quarterly model update on October 12, our proprietary EM equity portfolio has risen 9.2%, underperforming MSCI EM (up 12%)

EM EQUITY OUTLOOK

Passage of the US corporate tax cut has boosted the global growth outlook.  The IMF just revised up its US growth forecast for 2018 to 2.7% from 2.3% previously, citing the tax cuts.  The IMF’s global growth forecast for 2018 was revised up to 3.9% from 3.7% previously, and the agency said half of the upward revision was due to the US tax cuts.

MSCI EM made a new cycle high today, and is currently up about 9% YTD.  This follows a 34.4% gain in 2017.  Whilst trading at levels last seen in 2008, MSCI EM is poised to test the all-time high from November 2007 near 1345.  The S&P 500 is making new all-time highs on a seemingly daily basis.

It’s worth noting that the correlation between EM and DM stocks is currently 0.48, edging higher from the low around 0.42 right at the start of the year.  This is still down from a high of 0.60 posted last summer, but the rising correlation suggests that the EM equity outlook will remain dependent on DM performance.

We still believe it is very important for investors to continue focusing on country fundamentals.   Hedging out currency risk does not seem so important now for US investors in this weak dollar environment.  However, we continue to look for potential divergences within EM.  Regionally, Latin America is the best equity performer so far in 2018 (up 11.1% YTD), followed by Asia (up 8.6%) and then EMEA (up 8.4%).

Our 1-rated grouping (outperformers) for Q1 2018 remains steady with Hong Kong, Singapore, Czech Republic, Korea, and China.  We note that of the top 10 countries, 5 are in Asia and 5 are in EMEA.  Poland improved from 3 to 2, pushing Pakistan down from 2 to 3.

Our 5-rated grouping (underperformers) for Q1 2018 consists of Colombia, India, Brazil, Mexico, and South Africa.  Peru improved from 5 to 4, pushing Colombia down from 4 to 5.  We note that of the bottom 10 countries, 5 are in Latin America, 3 are in Asia, and 2 are in EMEA.

Other notable movements include Thailand and Egypt, both of which improved from 4 to 3.  This came at the expense of Indonesia and the Philippines.  Both worsened from 3 to 4.

Our next quarterly update for Q2 2018 will come out at the beginning of April.     

MODEL PERFORMANCE

Since our last quarterly model update on October 12, our proprietary EM equity portfolio has risen 9.2%, underperforming MSCI EM (up 12.0%).  Overweighting Taiwan and Korea hurt, as they underperformed during this period and have relatively large weights in our model portfolio.  Underweighting Russia and Peru also hurt, as they outperformed but with relatively small weights.

What positions helped our model performance during this period?  Our overweight position for China helped the most, as it outperformed with a very large weight.  Overweighting Pakistan and Qatar also helped as they outperformed, albeit with relatively small weights.  Underweighting Brazil and Mexico helped our return, as they underperformed during this period with relatively large weights.

Equity table

MODEL DESCRIPTION

Our equity allocation model is meant to assist global equity investors in assessing relative sovereign risk and optimal asset allocation across countries in the EM universe.  The countries covered include 23 of the 24 countries (excluding Greece) in the MSCI EM Index as well as 2 (Hong Kong and Singapore) from the MSCI DM Index.

A country’s score reflects its relative attractiveness for equity investors – the likelihood that its equity market will outperform the rest of our EM universe over the next three months.  A country’s score is determined as a weighted composite of 15 economic and political indicators that are each ranked against the other 24 countries in our model EM universe.  Categories are industrial production growth, real interest rates, export growth, expected P/E ratio, real bank lending, current account, real money growth, GDP growth, investment/GDP, per capita GDP, inflation, retail sales, political risk (EIU), FDI/GDP, and ease of doing business (World Bank).

A country that is typically ranked first in many of the categories will end up with a low composite score (the lower the better).  Exchange rate fluctuations can have significant effects on the dollar return to foreign investors, and so we have chosen several variables that tend to highlight exchange rate risk (such as current account balance and FDI).  Others were chosen as leading indicators of economic growth.

From a portfolio construction standpoint, we are benchmarking to MSCI Emerging Markets.  As a result, our BBH model portfolio weights will be Underweight/Overweight compared to the MSCI weights.

  • Countries that are rated 1 will have a BBH weight that is 1.5 X MSCI EM weight.
  • Countries that are rated 2 will have a BBH weight that is 1.25 X MSCI EM weight.
  • Countries that are rated 3 will have a BBH weight that is equal to MSCI EM weight.
  • Countries that are rated 4 will have a BBH weight that is 0.75 X MSCI EM weight.
  • Countries that are rated 5 will have a BBH weight that is 0.5 X MSCI EM weight.

In order to have the BBH model portfolio weights add up to 100%, there may be some exceptions to the rules outlined above.  However, we will always try to keep to the parameters as closely as possible.

CHANGE IN METHODOLOGY AND COVERAGE

The move by MSCI to upgrade Pakistan to Emerging Market (EM) status has led us to reformulate our coverage.  We eliminated Israel from our model universe to make room for Pakistan.

In the past, we have taken a simple average of each grouping (1 through 5) to determine model performance.  That allowed small markets such as Egypt or Peru to really skew the results.  We are now taking a weighted approach, with country returns weighted by the BBH model weightings.  Then, we compare our model performance against our benchmark MSCI EM.