- Soft US data and delays to fiscal stimulus plans from the Trump administration has led to a rethink of Fed tightening expectations
- The correlation between EM and DM stocks is currently 0.51 and just below the year’s high around 0.53
- One negative factor for EM equities this past quarter has been lower commodity prices
- Our 1-rated grouping (outperformers) for Q3 2017 consists of Hong Kong, Singapore, China, Korea, and Czech Republic
- Our 5-rated grouping (underperformers) for Q3 2017 consists of Colombia, Peru, Mexico, Brazil, and South Africa
EM EQUITY OUTLOOK
Soft US data and delays to fiscal stimulus plans from the Trump administration has led to a rethink of Fed tightening expectations. After the June hike, markets no longer view another hike in H2 as likely. Indeed, only one hike is currently priced in for 2018 followed by only one in 2019. The benign global backdrop has helped propel the S&P 500 to new record highs last week.
It’s worth noting that the correlation between EM and DM stocks is currently 0.51 and just below the year’s high around 0.53. This is still down from a high of 0.85 posted last summer, but rising correlations suggest that the EM equity outlook has become more dependent of DM than it was in the recent past.
One negative factor for EM equities this past quarter has been lower commodity prices. Here, the outlook remains very volatile as markets struggle with the possibility of persistent excess global supply in several industrial commodities. WTI oil is down nearly 15% from the April 12 peak, while iron ore is down nearly 20% from the April 5 high.
MSCI EM is making a new cycle high this week, and is currently up 22.5% YTD. It is trading at levels last seen in May 2015, and is on track to test the May 2015 high near 1069. After that is the September 2014 high near 1104.
As the global backdrop hopefully clears up in the coming months, we still believe it is very important for investors to continue focusing on country fundamentals and on hedging out currency risk whenever feasible. Regionally, Asia is the best equity performer so far in 2017 (up 27.2% YTD), followed by Latin America (up 15.6%) and then EMEA (up 7.9%).
Our 1-rated grouping (outperformers) for Q3 2017 consists of Hong Kong, Singapore, China, Korea, and Czech Republic. Czech Republic improved from 2 to 1, Egypt and Turkey both improved from 3 to 2, and India improved from 5 to 4. We note that of the top 10 countries, 6 are in Asia and 4 are in EMEA.
Our 5-rated grouping (underperformers) for Q3 2017 consists of Colombia, Peru, Mexico, Brazil, and South Africa. Peru worsened from 4 to 5 while Poland worsened from 2 to 3. Pakistan enters our model universe at 3, replacing Israel. We note that of the bottom 10 countries, 5 are in Latin America, 2 are in Asia, and 3 are in EMEA.
Our next quarterly update for Q4 2017 will come out at the beginning of October.
Since our last quarterly model update on April 17, our proprietary EM equity portfolio has risen 10.6%, outperforming MSCI EM (+9.8%). Overweighting Korea and China helped, as they outperformed during this period and had relatively large weights in our model portfolio. Underweighting Brazil, South Africa, Russia, and India also helped our return, as these markets underperformed during this period with relatively large weights.
What positions hurt our model performance during this period? Our overweight positions UAE, Czech Republic, Poland, and the Philippines hurt, as they underperformed but with relatively small weights. Underweighting Peru hurt our performance too, as it outperformed modestly during this period, albeit with a small weight.
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) 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.