- Firmer US data and official comments have led markets to recalibrate their Fed tightening expectations
- Markets have almost fully priced in a third hike for 2017 in December
- We are seeing greater divergence between EM equities and EM FX
- Our 1-rated (strongest fundamentals) grouping for Q4 2017 consists of SGD, TWD, THB, KRW, and PEN
- Our 5-rated (weakest fundamentals) grouping for Q4 2017 are ZAR, MXN, TRY, EGP, and ARS
- Our next EM FX model quarterly update for Q1 2018 will come out at the beginning of January
EM FX OUTLOOK
Firmer US data and official comments have led markets to recalibrate their Fed tightening expectations. The US 2-year yield of 1.56% today is the high for this cycle and the highest since October 2008. The US 10-year yield moved close to 2.0% last month but has since turned higher and moved close to the May/June high near 2.40% and stand at 2.34% today.
Markets have almost fully priced in a third hike for 2017 in December. Yet, only one hike is currently priced in by the markets for 2018 followed by less than one more in all of 2019 and 2020 combined. The latest Fed Dot Plot sees one more hike in 2017, three in 2018, two in 2019, and one in 2020. The Fed Funds futures strip shows that the market still does not fully believe the Fed. EM FX is likely to come under pressure if market expectations move closer to the Fed’s outlook.
We are seeing greater divergence between EM equities and EM FX. While MSCI EM is making new cycle highs and currently up 31% YTD, the corresponding MSCI EM FX index has been lagging this month. The correlation between the two is currently around 0.54, down from the high near .85 back in May and a high above 0.90 back in July 2016.
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.
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 Q4 2017 consists of SGD, TWD, THB, KRW, and PEN. TWD and PEN both improved from 2 to 1. These two pushed down CNY to 2 and PHP to 3.
With global financial markets likely 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 2017 are in Asia. This 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 and BRL are the two representatives from Latin America.
Our 5-rated (weakest fundamentals) grouping for Q4 2017 are ZAR, MXN, TRY, EGP, and ARS. UYU improved from 4 to 5, pushing down ZAR to 5. Note that five of the worst ten currency picks for Q4 2017 are in EMEA, while four are in Latin America. The lone representative from Asia is MYR, which worsened from 3 to 4. Other notable movements are BRL (improved from 3 to 2), CZK and CLP (both improved from 4 to 3), and COP (worsened from 3 to 4).
Our next EM FX model update for Q1 2018 will come out at the beginning of January. However, we will provide monthly performance updates throughout Q4.
Since our model was last updated on July 18, those currencies with VERY STRONG (1) fundamentals have gained an average of 0.4%, while those with STRONG (2) fundamentals have gained an average of 0.8%. This compares to an average gain of 0.1% during the same period for those with WEAK (4) fundamentals and an average loss of -2.7% for those with VERY WEAK (5) fundamentals. Lastly, an average gain of 0.2% was posted by those with NEUTRAL (3) fundamentals.
This past quarter, we saw divergencies across all five groupings. With markets getting a bit more negative on EM FX, it seems that those currencies with relatively bad fundamentals are being sold the most, and that’s the way it should be. Still, we note that there were outliers in all the groupings. Subpar performances for KRW (-0.8%) and PHP (-1.1%) dragged down the performance of the 1 group. On the other hand, outsized gains for CLP (+4.6%) and EGP (+1.8%) pulled up the performances of the 4 and 5 groups. Lastly, the 3 group was pulled up by a big gain for COP (+2.1%).
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.