EM Equity Allocation Model For Q1 2017 – UPDATE

Blog icons-EM Equity Allocation Model

  • Recent strength in the US economic data and hawkish Fed comments has led the market to price in another 25 bp hike this week
  • Furthermore, technical indicators for many of the EM currencies suggest overbought conditions
  • Whatever the pace and scope of Fed tightening is, we still believe it is very important for investors to continue focusing on country fundamentals
  • Our 1-rated grouping (outperformers) for Q1 2017 consists of Korea, Czech Republic, Poland, China, and Singapore
  • Our 5-rated grouping (underperformers) for Q1 2017 consists of Russia, Mexico, Egypt, South Africa, and Brazil

EM EQUITY OUTLOOK

Recent strength in the US economic data and hawkish Fed comments has led the market to price in another 25 bp hike this week.  Whether the Fed hikes in March or May makes little difference in the long run.  What matters more is that the markets are not fully pricing in the risk of more than two hikes this year.  When that repricing takes place, EM is likely to come under greater pressure.

Furthermore, technical indicators for many of the EM currencies suggest overbought conditions.  With the technical largely lining up with the fundamentals, we believe further EM weakness will be seen in the coming days.

Whatever the pace and scope of Fed tightening is, we still believe it is very important for investors to continue focusing on country fundamentals and also on hedging out currency risk whenever feasible.  Regionally, Asia is the best equity performer so far in 2017 (up 10.9%), followed by Latin America (up 8.3%) and then EMEA (up 1.1%).

Our 1-rated grouping (outperformers) for Q1 2017 consists of Korea, Czech Republic, Poland, China, and Singapore.  China improved from 2 to 1, while Israel worsened from 1 to 2.  We note that of the top 10 countries, 6 are in Asia and 4 are in EMEA.

Our 5-rated grouping (underperformers) for Q1 2017 consists of Russia, Mexico, Egypt, South Africa, and Brazil.   This was the same as last quarter.  The only other changes of note were Qatar improving from 4 to 3 and Malaysia worsening from 3 to 4.  We note that of the bottom 10 countries, 4 are in Latin America and 4 are in EMEA.  The other 2 are in Asia.

Our next model update for Q2 2017 will come out at the beginning of April.

MODEL PERFORMANCE

Since our last quarterly model update on January 10, our proprietary EM equity portfolio has risen 4.0%, slightly underperforming MSCI EM (up 4.4%).  Overweighting Korea and Taiwan hurt our portfolio, as they underperformed during this period and had relatively large weights in our model portfolio.  Our EM portfolio was also hurt by overweighting UAE and the Philippines, as they also underperformed during this period, albeit with relatively small weights.

On the other hand, underweighting Mexico hurt our portfolio as it outperformed and had a fairly large weight.  Underweighting Turkey also hurt, as it outperformed but had a relatively small weight.

What positions helped our model performance during this period?  Our overweight position for China was the biggest positive factor, as it outperformed within EM during this period and had a relatively large weight.  Overweighting Poland also helped, as it outperformed with a relatively small weight.  Our EM portfolio was also helped by underweighting Brazil and Russia, as they underperformed during this period with relatively large weights.

Win Thin March 2017 2

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 22 of the 23 countries (excluding Greece) in the MSCI EM Index as well as 3 (Israel, 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 Qatar and UAE to Emerging Market (EM) status has led us to reformulate our coverage and our model inputs.  We eliminated Argentina and Pakistan from our model universe and included Qatar and UAE.   

We have also introduced “Political Risk” (as measured by EIU) as a model input, and eliminated “Economic Freedom.” We believe that the “Index of Economic Freedom” was already being picked up in the “Ease of Doing Business” input. 

In the past, we have taken a simple average of each grouping (1 through 5) in order 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.

We continue to think that investors will continue to differentiate within EM, favoring those countries with stronger fundamentals.  This environment should make a fundamentally-based allocation model such as ours much more accurate in picking winner and losers.