- The broad-based dollar rally stalled recently following the more dovish market take on the Fed
- We believe markets are vastly underestimating the Fed’s capacity to tighten in 2019
- MSCI EM FX is likely to eventually test the September low
- Every EM currency is down in 2018
- We see continued divergences within the asset class
- Our 1-rated (strongest fundamentals) grouping for Q4 2018 consists of SGD, RUB, THB, CNY, and MYR
- Our 5-rated (weakest fundamentals) grouping for Q4 2018 consists of RON, CLP, LKR, ARS, and TRY
EM FX OUTLOOK
The broad-based dollar rally stalled recently following the more dovish market take on the Fed. However, the dollar is clawing back some of its recent losses. DXY has pushed back above 97 and seems likely to eventually test the November 12 high near 97.69. This has put pressure on EM FX as well, though some idiosyncratic developments have allowed some EM currencies to claw back part of their recent losses.
We believe markets are vastly underestimating the Fed’s capacity to tighten in 2019. When market expectations readjust to a more hawkish take on the Fed, the dollar rally should resume in force. A higher US rate outlook will be a major headwind for EM, as are ongoing global trade tensions and signs of further slowing in China.
In mid-September, MSCI EM FX traded at its lowest level since last May. It has since edged higher but remains near those lows. Given our negative outlook on EM, we believe MSCI EM FX will eventually test that September low near 1575 and then the April 2017 low near 1568. If the EM sell-off continues as we expect, then the March 2017 low near 1546 should come into focus.
Every EM currency is down against the dollar in 2018. The worst performers YTD are the high beta group ARS, TRY, BRL, RUB, and ZAR. With US rates likely to march higher and trade tensions still ratcheting up, we believe EM FX is likely to remain under pressure well into 2019.
We see continued divergences within the asset class. In particular, we see heightened political risk continuing to weigh on high beta group mentioned above. On top of political risk, we also believe it is very important for investors to continue focusing on country-specific fundamentals. Hedging out currency risk has become much more important because we strongly believe that this current dollar rally has legs.
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 Q4 2018 consists of SGD, RUB, THB, CNY, and MYR. Malaysia improved from 2 to 1, which pushed TWD down from 1 to 2. BRL improved from 4 to 2, which pushed PHP 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 six of the ten top currency picks for Q4 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 BRL joins PEN as the two representatives from Latin America.
Our 5-rated (weakest fundamentals) grouping for Q4 2018 consists of RON, CLP, LKR, ARS, and TRY. CLP worsened from 3 to 5, which helped push EGP up from 5 to 4. Note that five of the worst ten currency picks for Q4 2018 are in EMEA, while four are in Latin America. The lone representative from Asia remains LKR.
Our next EM FX model update for Q1 2019 will come out in January. However, we will provide monthly performance updates throughout Q4.
Since our model was last updated on October 29, those currencies with VERY STRONG (1) fundamentals have gained an average of 0.1%, while those with STRONG (2) fundamentals have lost an average of -0.5%. This compares to an average gain of 0.8% during the same period for those with WEAK (4) fundamentals and an average gain of 1.0% for those with VERY WEAK (5) fundamentals. Lastly, an average gain of 2.9% was posted by those with NEUTRAL (3) fundamentals.
For this quarter, currency performances have not reflected underlying fundamentals. We have found that our EM FX model does not work so well during periods of consolidation for the dollar, which is what the shifting Fed outlook has engendered. Still, we note that there were outliers in every group. Relatively weak showings for RUB (-1.5%) and BRL (-4.0%) pulled down the performances of the 1 and 2 groups. Likewise, good performances for ZAR (7.0%) and TRY (7.0%) boosted the performances of the 4 and 5 groups. Same goes for IDR (6.4%) and INR (5.6%) and the 3 group.
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.