- Despite strong Q1 US data reported recently, the dollar is having trouble gaining traction
- We still believe that a hawkish Fed is likely to re-assert itself as the major market driver in 2017
- Our 1-rated (strongest fundamentals) grouping for Q1 2017 consists of SGD, THB, TWD, PEN, and IDR
- Our 5-rated (weakest fundamentals) grouping for Q1 2017 are COP, EGP, UYU, TRY, and ARS
- Our next EM FX model quarterly update for Q2 2017 will come out at the beginning of April
EM FX OUTLOOK
Despite strong Q1 US data reported recently, the dollar is having trouble gaining traction. Bloomberg’s WIRP page shows the odds of a March Fed hike at 40%, down from 44% yesterday but up from the 24% last week. CME’s model shows the odds at 22%, down from 31% yesterday but up from 18% previously.
We still believe that a hawkish Fed is likely to reassert itself as the major market driver in 2017. EM FX rarely does well in a rising US rate environment, and started the year off on its back foot before rallying in recent weeks. We believe this EM bounce will eventually give way to broad-based selling.
Whatever the pace and scope of Fed tightening is, we still believe it is very important for investors to continue focusing on the fundamentals and also on hedging out currency risk whenever feasible. Individual country risk must be monitored closely. We believe investors are being too sanguine on EM, as the current rally is being led by MXN, TRY, and ZAR, all of which face heightened risks.
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. With the recent float of the pound, we now include EGP in our model universe, replacing PKR.
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 Q1 2017 consists of SGD, THB, TWD, PEN, and IDR.
With global financial markets likely remain volatile, we continue to recommend focusing on fundamentals as opposed to high carry. Note that four of the five top currency picks for Q1 2017 are in Asia (SGD, THB, TWD, and IDR). This lines up with our long-held view that Asia is best-placed fundamentally in the current environment. Three others in the top ten are also from Asia (KRW, PHP, and INR), along with two from EMEA (ILS and RON). PEN is again the sole representative from Latin America in the top ten.
Notable positive movements include IDR (from 3 to 1) as well as PHP and INR (both from 3 to 2). CLP and MXN both improved (from 4 to 3), and ZAR also improved (from 5 to 4).
Our 5-rated (weakest fundamentals) grouping for Q1 2017 are COP, EGP, UYU, TRY, and ARS. Note that three of the five worst currency picks for Q1 2017 are in Latin America (COP, UYU, and ARS), while two are in EMEA (EGP and TRY). Others in the bottom ten are also heavily weighted towards EMEA (PLN, CZK, RUB, and ZAR), which also includes BRL.
Notable negative movements include PLN (from 2 to 4) as well as CNY and HUF (both from 2 to 3). ILS also worsened (from 1 to 2), as did CZK (from 3 to 4).
Our next EM FX model update for Q2 2017 will come out at the beginning of April. However, we will provide monthly performance updates throughout Q1.
Since our model was last updated on January 17, those currencies with VERY STRONG (1) fundamentals have gained an average of 1.2%, while those with STRONG (2) fundamentals have gained an average of 1.2%. This compares to an average gain of 5.5% during the same period for those with VERY WEAK (5) fundamentals and an average gain of 2.8% for those with WEAK (4) fundamentals. Lastly, an average gain of 1.8% was posted by those with NEUTRAL (3) fundamentals.
So far this quarter, all five groupings are up as EM is in the midst of a broad-based rally. However, we note that there were some significant outliers in all the groupings. Poor performances for SGD (-0.2%), PHP (-0.5%), and RON (-0.4%) dragged down the performances of the 1 and 2 groups. On the other hand, outsized gains for EGP (+18%), BRL (+5.2%), and ZAR (+4.1%) turbo-charged the performances of the 4 and 5 groups. The 3 group was pulled up by large-scale gains for MXN (6.1%).
We think that many of the outperformers during this period (such as BRL, MXN, and ZAR) will revert to being underperformers again when EM weakness resumes. We will continue monitoring and reporting our model performance in the coming months.
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, FDI/GDP, nominal M3 growth, budget deficit/GDP, inflation, percentage deviation of the spot rate from Purchasing Power Parity (PPP), political risk, and banking sector risk. 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.