EM FX Model for Q3 2018

  • The broad-based dollar rally has taken a pause after Trump’s comments last week
  • MSCI EM and MSCI EM FX are both likely to test their June-July 2017 lows
  • Every EM currency is down in 2018 except for COP and MXN
  • We see continued divergences within the asset class

EM FX OUTLOOK

The broad-based dollar rally has taken a pause after Trump’s comments last week. This has allowed some EM currencies to claw back part of their recent losses. Still, the higher US rate outlook remains a major headwind for EM, as do ongoing trade tensions.

MSCI EM rallied for much of 2017, with the last leg up from early December until late January. It peaked at 1279 on January 29. Since then, it has retraced that entire leg and is trading at levels not seen since last August. MSCI EM tested the August low near 1040 before this pause. We see an eventual break below, which would set up a test of the June 2017 low near 1000.

Similarly, MSCI EM FX rallied for much of 2017, with the last leg up from early December until late March. It peaked at 1732 on March 27. Since then, it has retraced that entire leg and recently traded at its lowest level since last July. Given our negative outlook on EM, we believe MSCI EM FX is on track to test the July 2017 low near 1585, and then the April 2017 low near 1568.

Every EM currency is down against the dollar in 2018 except for COP and MXN. The worst performers YTD are the high beta group ARS, TRY, BRL, RUB, and INR. With US rates likely to march higher and trade tensions still ratcheting up, we believe EM FX is likely to remain under pressure in H2.

We see continued divergences within the asset class. As such, we still believe it is very important for investors to continue focusing on country fundamentals. Hedging out currency risk has become much more important because we strongly believe that this current dollar rally has legs.

SUMMARY

Our FX model is meant to assist global investors in assessing relative FX risk across countries in the EM universe. A country’s score reflects the relative fundamentals. This in turn should tell us something about the likelihood that its currency will outperform the rest of our EM universe over the next three months. We now include the Sri Lankan rupee (LKR) in our model universe, replacing the Uruguayan peso (UYU).

We favor the currencies of Asia and, to a lesser extent, EMEA, while Latin America should continue to underperform. Our 1-rated (strongest fundamentals) grouping for Q3 2018 consists of SGD, THB, RUB, CNY, and TWD. Taiwan improved from 2 to 1, which pushed KRW down from 1 to 2. INR improved from 3 to 2, which pushed CZK down from 2 to 3.

With global financial markets likely to remain volatile, we continue to recommend focusing on fundamentals as opposed to high carry. Note that seven of the ten top currency picks for Q3 2018 are in Asia. This grouping lines up with our long-held view that Asia is best-placed fundamentally in the current environment. Two of the top ten are from EMEA (ILS and RUB), while PEN remains the lone representative from Latin America.

Our 5-rated (weakest fundamentals) grouping for Q3 2018 consists of HUF, LKR, EGP, ARS, and TRY. RON improved from 5 to 4, which push HUF down from 4 to 5. Note that five of the worst ten currency picks for Q3 2018 are in EMEA, while four are in Latin America. The lone representative from Asia remains LKR.

Our next EM FX model update for Q4 2018 will come out in October. However, we will provide monthly performance updates throughout Q3.

MODEL PERFORMANCE

Since our model was last updated on April 17, those currencies with VERY STRONG (1) fundamentals have lost an average of -5.3%, while those with STRONG (2) fundamentals have lost an average of -4.2%. This compares to an average loss of -7.8% during the same period for those with WEAK (4) fundamentals and an average loss of -10.1% for those with VERY WEAK (5) fundamentals. Lastly, an average loss of -5.9% was posted by those with NEUTRAL (3) fundamentals.

For this quarter, currency performances have reflected underlying fundamentals. We have found that our EM FX model works best during periods of stress, as markets tend to punish the currencies with poor fundamentals the most. Still, we note that there were outliers in some groups. A relatively weak showing for CNY (-7.5%) pulled down the performance of the 1 group. Likewise, good performances for LKR (-1.9%) and EGP (-1.1%) boosted the performance of the 5 group.

MODEL DESCRIPTION

Our FX model covers 25 countries, with each country’s score determined by a weighted composite ranking of 15 economic indicators that are each ranked against the rest of our model EM universe for each category. Categories are external debt/GDP, real interest rates, short-term debt/reserves, import cover, external debt/exports, current account/GDP, export growth, GDP growth, nominal M3 growth, budget deficit/GDP, inflation, percentage deviation of the spot rate from Purchasing Power Parity (PPP), political risk, and banking sector risk. We have replaced FDI/GDP with a country’s Net International Investment Position (NIIP/GDP). A country that is typically ranked first in many of the categories will end up with a low composite score (the lower the score, the better the fundamentals).

The 10 countries that are at the top of our table have VERY STRONG (rated 1) or STRONG (rated 2) fundamentals relative to our EM universe, while the 10 at the bottom have WEAK (rated 4) or VERY WEAK (rated 5) fundamentals. Those five in the middle have NEUTRAL (rated 3) fundamentals. These scores do not imply a greater return for those countries with a higher ranking. Rather, our models simply seek to identify those currencies that are backed up by better underlying fundamentals compared to their EM peers. We stress that the composite rankings contained in this model are a relative measure, not an absolute one.

Furthermore, we are making no assertions about the actual currency returns to investors, as that will involve differences in yield across all the currencies. We are simply identifying which currencies have strong fundamentals and which have weak fundamentals.