Global Macro Rules for EM Trading: US Rates, the Dollar, and the Fed
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Book: Trading Fixed Income and FX in Emerging Markets | Authors: Dirk Willer, Ram Bala Chandran, Kenneth Lam | Publisher: Wiley, 2020 | ISBN: 978-1-119-59905-0
This is the first half of Chapter 2, titled “Global Macro Rules.” And honestly, the title kind of says it all. If you want to trade emerging markets, the single most important thing you need to understand is that EM is not really about EM. It’s about the US. It’s about the dollar. It’s about the Fed. Everything else is secondary.
Let’s get into it.
65% Global, 35% Local
Here’s the headline number from the book: roughly 66% of the variation in EMFX returns is explained by global macro forces. Not local politics. Not local central bank decisions. Not local GDP. Global macro.
The authors ran regressions of EM asset class returns on the big macro variables: the dollar index (DXY), 10-year US Treasuries, US high yield credit, the S&P 500, and the Bloomberg Commodity Index. Starting from 2002, they found that EMFX is overwhelmingly driven by these global factors. EM equities and external debt (EMBI) are similarly macro-dominated. The one exception is EM local rates, where only 36% of the variation comes from global macro. That makes sense because local central banks obviously have a lot of control over their own interest rates.
The practical takeaway is pretty brutal: if you’re trading EMFX directionally, you’d better have a view on global macro first and the local story second. Local stories matter for relative value trades (picking one EM currency against another), but they rarely have enough force to fight the global tide.
The Dilma Proof
The book uses Brazil between 2014 and 2016 as a perfect illustration. This was about as dramatic a local story as you could ask for. Dilma Rousseff gets narrowly re-elected, the Lava Jato corruption scandal explodes, the country falls into a deep recession, impeachment proceedings drag on for months, and she eventually gets removed from office. Markets celebrated her ouster.
And yet, if you chart BRL against the broader EMFX index during this entire period, the two charts look almost identical. There was not a single week where BRL sold off meaningfully while EMFX did well. Even during the most dramatic moments of the Rousseff saga, the Brazilian real was hostage to the global dollar. The only real divergence was a brief period of BRL outperformance when impeachment became likely, but even then, the direction was the same as the broader index.
That’s how powerful global macro is. The biggest political crisis in Latin America’s largest economy, and FX traders basically just watched the DXY.
Which Macro Factors Matter Most?
The authors break down the impact of each global factor on EM returns, and a few things stand out.
The S&P 500 has the largest overall impact across EM asset classes. A higher S&P boosts EM returns broadly. The dollar (DXY) comes next for EMFX specifically. Commodities and US high yield credit are also very relevant.
Somewhat surprisingly, US rates are not the most important factor on average. But this changes depending on the time period you look at. In the 2003-2012 period, higher US rates actually coincided with stronger EMFX, because higher rates meant stronger global growth, and the dollar was in a bear market. After the 2013 taper tantrum, the relationship flipped. Higher US rates started to coincide with weaker EMFX, because the stronger growth was mostly a US phenomenon, which also pushed the dollar higher.
That 2013 break in correlations is a big deal. The authors point out that it wasn’t exactly a surprise at the time. Everyone knew Fed tapering would hurt EM. But the episode serves as a reminder that macro correlations can shift, and traders need to stay open-minded about when those shifts happen.
One more finding worth highlighting: US high yield credit turns out to be the single most important macro driver across all EM asset classes when you measure it by information ratios. Periods of rising US HY spreads are the most dangerous times to be long EM, full stop.
When the US Sneezes, the World Catches a Cold
There’s a view out there that EM has “decoupled” from the US. The data says otherwise.
The authors looked at the last two US recessions (2001 and 2007/08) and checked how EM economies responded. The results are stark. During the relatively mild 2001 recession, every single emerging market experienced negative year-over-year GDP growth. Every one. And for every country except Hungary, the negative growth lasted at least two quarters. Every country also experienced a sharper GDP contraction than the US itself.
Asia got hit hardest in 2001 because the Nasdaq bubble was the epicenter, and countries like Taiwan, South Korea, and Singapore were deeply plugged into the US tech cycle. But even countries with no direct connection to the tech bust got hammered, because EM business cycles are inherently more volatile. Manufacturing makes up a bigger share of GDP, services a smaller share, so the swings are amplified.
The 2007/08 recession was worse across the board. The median EM country’s worst GDP print was -4.1% year-over-year, compared to -2.7% in 2001. And this time it wasn’t just Asia. Latin America and CEEMEA had similarly deep downturns. The US housing crisis started as a domestic affair, but it spread through the financial system to the rest of the world. The lesson: even domestically focused US shocks end up hitting EM, because the US is the critical nexus for the global financial system.
Here’s a nuance that’s easy to miss: in 2001, the median EM actually started printing negative GDP growth two quarters before the US formally entered recession. It only takes a minor US slowdown for EM to get hurt badly, especially if the slowdown originates in a sector with strong international links.
There is no decoupling from US recessions. The table in the book is titled exactly that, and the data backs it up completely.
EM Central Banks Follow the Fed
From a trading perspective, US recessions create opportunities in EM rates. If EM central banks can follow the Fed in cutting rates, it often happens with a lag, and lags create opportunities to put on receiver trades (positions that benefit from falling interest rates).
The data on how EM central banks respond to Fed easing cycles is fascinating. In 2001, central banks reacted quickly. The median lag was just two months after the Fed started cutting. Most EM economies were already slowing fast, so there was no reason to delay.
2008 was a completely different story. The median EM central bank waited 15 months before cutting rates. Fifteen months! Why so long? Three reasons. First, many EM countries had inflation problems. Second, there was a widespread “decoupling” narrative: the US housing crisis was seen as a domestic problem that wouldn’t spread. Third, the commodity spike of 2007 kept EM assets stable well after the US had entered recession.
So many EM central banks were actually still hiking rates even after the Fed started cutting. Those hikes turned out to be a policy mistake and were eventually reversed.
The book’s trading rule here is elegant: look for countries that still have inflation problems when the US stops growing. Receiver trades in those countries are often profitable because the lags are long and variable. The market hasn’t priced in the cuts that are eventually coming.
The table title says it perfectly: “Risk Aversion Be Damned: EM Central Banks Follow the Fed.” They always do. It just sometimes takes them a while to get there.
US Rates and EM: It’s Complicated
Now let’s zoom out from recessions and look at how US rates affect EM assets more broadly.
First, some context on when the big sell-offs in US rates happen. The authors identified all major sell-offs (80bp+ over two months in 10-year US swaps) and found they cluster around two specific moments in the Fed cycle: around the last cut and around the first hike. During ongoing hiking cycles, the sell-offs at the back end of the curve are usually much more contained.
The 2004 tightening cycle is a good example. A long Fed hiking cycle caused very little disruption in EM. Once markets have adjusted to the fact that the Fed is hiking, it’s less destabilizing. The dangerous moments are the pivot points.
EM Rates Track US Rates (Mostly)
Here’s the key finding: EM local rates are the only EM asset class with a consistently positive beta to US Treasury returns. On an index level, EM rates basically act like a risk-free UST asset. Yes, individual countries sometimes see their rates spike during risk-off episodes because their currencies are weakening. But on an index level, those episodes are too infrequent to distract from the big picture: lower US yields are good for EM duration.
When you’re bullish on US rates, you should add EM duration and not worry too much about rising risk aversion.
EM Credit Moves the Opposite Way
EM credit spreads have a consistently negative beta to UST returns. When US yields rise (usually during strong growth periods), EM credit spreads tend to tighten. So when you’re bullish on US rates (expecting lower yields), you should actually be cautious on EM credit (hedged for US rates exposure). And when you expect higher US rates, EM external debt (with the rates component hedged) is actually the better bet over local debt.
The practical rule: UST rallies help EM duration but hurt EM credit.
Big Sell-Offs in US Rates Crush EMFX
This one is reliable. When US Treasuries sell off by more than 100 basis points over three months (roughly a 5% negative return in the 7-10 year bucket), EMFX consistently weakens. The book shows this pattern across multiple episodes: the end of Fed cutting in 2003, the start of hiking in 2004, the taper tantrum in 2013, and the Trump election/Fed hike in late 2016.
Smaller sell-offs are much less predictable. A 60bp move like we saw in late 2017 into early 2018 didn’t hurt EMFX at all. During smaller moves, other factors matter. But when US rates blow out by 100bp+ in three months, you want to be out of EMFX.
One more detail: sell-offs in real rates are more dangerous for EMFX than sell-offs in nominal rates. Break-evens are mostly driven by oil, and higher oil prices are actually EM-positive (we’ll get to that). But rising real rates in the US make capital more expensive without offering the oil benefit, so they’re more toxic for EM currencies.
When EM Rates Diverge from US Rates, Pay Attention
The book highlights a useful contrarian signal. The beta of EM rates to US rates is usually positive, but it can go negative during stress periods. When the beta hits extreme negative levels (like -0.4 during the Lehman bankruptcy or in 2018), those tend to be excellent receiving opportunities in EM rates.
The logic is that extreme divergences between EM rates and US rates tend to correct. EM assets eventually recouple with their DM counterparts. So when you see EM rates selling off hard while US rates are rallying, and the beta has gone deeply negative, that’s usually a signal to get long EM duration.
EMFX is All About the Dollar
If you remember one thing from this chapter, make it this: the DXY is the most important global macro driver for EMFX.
The book shows a chart of EMFX versus DXY, and they basically move in lockstep. This isn’t surprising when you think about it. EM currencies are all traded against the dollar, and USD crosses are highly correlated. Some EM currencies are traded explicitly against the euro (Czech koruna, Polish zloty, Hungarian forint) or are linked to a USD basket (Singapore dollar, Chinese yuan). But even currencies with no direct link to the euro have very high sensitivity to the dollar index.
And it’s not just EMFX. All EM asset classes tend to do better when the dollar is weak. For EM rates, a weaker dollar means less inflation pass-through in EM, which lets central banks stay easier. For EM credit, a weaker dollar reduces the burden of USD-denominated debt as a percentage of GDP. For EM equities, a weaker dollar drives capital inflows that turbocharge local credit creation and push stock markets higher.
There’s also the commodity channel: a stronger dollar is typically associated with lower commodity prices, which hurts EM because the asset class includes many commodity exporters.
When Betas to EUR Fall Hard, Be Careful
The authors track the rolling betas of EM asset class returns to the euro. Normally these betas are positive and fairly stable. But when they drop sharply, especially falling into negative territory, that’s a warning sign.
For EM credit, the beta to EUR went negative in mid-2007, late 2008, mid-2015, and early 2018. Each of those was a bad time for EM credit. For EM rates, the beta fell to zero in early 2013, right before the taper tantrum. The takeaway: unusual correlations between EM assets and the euro are worth watching because they often lead to a rapid and violent normalization.
EUR Matters: CEEMEA vs. Asia
Since the EUR is such a big component of the DXY, getting the euro right matters a lot for EM. But there’s a practical way to use this.
Not all EM currencies respond equally to EUR moves. The highest betas to EUR are in CEEMEA and high-beta Latin American currencies: ZAR (78%), TRY (62%), BRL (52%). The lowest betas are in Asia: PHP (14%), TWD (17%), IDR (18%), CNY (5%). Even the EUR crosses like PLN and CZK have positive betas to EUR in USD terms, meaning if EUR strengthens against USD, these currencies strengthen by even more against the dollar.
The trading rule: when you expect EUR strength, overweight CEEMEA FX and underweight Asia FX. The book tests this with a perfect foresight simulation where an investor allocates 100% to CEEMEA when EUR is going up that month and 100% to Asia when EUR is going down. The resulting P&L has very few drawdowns, which shows that even a small edge in forecasting EUR can generate meaningful alpha in EM.
The authors are honest that forecasting EUR is extremely hard, so the practical utility of this rule is limited. But at the very least, you need to understand that when you have big allocation differences between CEEMEA and Asia, you’re implicitly making a bet on the euro. Make sure that’s a bet you want to make.
That’s the first half of Chapter 2. The message is clear: global macro dominates EM. The US drives the bus, the Fed sets the speed, and the dollar determines the road. Local stories are noise relative to these global forces, except when they create relative value opportunities between EM countries.
In Part 2, we’ll cover how commodities and risk aversion affect EM assets, which rounds out the full set of global macro rules.