How to Trade EMFX: Growth, Valuation, Momentum, and Seasonality

Previous: How to Trade EMFX Part 1

In Part 1 we covered carry strategies and how they’ve been slowly dying. Now let’s get into the stuff that actually works better: growth, valuation, momentum, flows, seasonality, and volatility. This is where the chapter gets really interesting.

Carry + Trade Balance Improvement = Better Results

Remember how pure carry strategies have been struggling? The authors found a nice trick: combine carry with improving trade balances.

The logic is simple. High carry alone can be a trap because the countries offering the juiciest yields often have terrible current accounts. And countries with strong current accounts tend to have low rates. Those two factors basically cancel each other out.

But here’s the move. Instead of looking at the level of the current account (which barely changes), look at the change in the trade balance. A country with decent carry whose trade balance is getting better? That’s a much stronger signal than either factor alone. The authors rank currencies by both carry and six-month trade balance improvement, add the ranks together, and go long the top four against the bottom four. The P&L is meaningfully better than a static current account strategy.

India is a perfect example. In 2013, it was one of the “Fragile Five” with a current account deficit around 5% of GDP. The INR got crushed. But then the trade balance started improving, driven by government belt-tightening and a tariff on gold imports. The INR started outperforming even while the current account deficit was still large. The change in trend was enough. By 2015, India’s deficit was down to 1.3%. Fragile no more.

The takeaway: don’t look at where a country is. Look at where it’s going.

Growth Is the Best Factor

This might be the most important finding in the whole chapter. Out of all the fundamental factors the authors tested, growth surprises generated the most consistently profitable strategy.

But it’s not as simple as “EM growth is high, buy EMFX.” The relationship between growth and currency performance has a wrinkle: the Fed. When EM growth is strong, the global economy is usually strong too. And that means the Fed is hiking rates. Those rate hikes can kill the positive effect of good EM growth.

The sweet spot is early in the cycle. EM growth differentials are improving, but the Fed is still being easy. That’s when EMFX rips. As the Fed tightens further, EMFX goes sideways or sells off, even if EM growth is still strong. Only when the Fed pauses does EMFX start rallying again.

The 2004-2006 cycle showed this perfectly. EMFX did great early on as EM growth differentials widened. Then it flatlined as Fed hikes bit. Only when the Fed went on hold in 2006 did the rally resume.

For a more precise approach, the authors use economic surprise indexes. These track whether economic data is beating or missing expectations. The strategy is straightforward: go long EMFX when the EM economic surprise index crosses above zero, go short when it drops back below. The P&L is “meaningfully positive and relatively consistent.” At the time of writing, growth was the single most consistently profitable factor for EMFX trading.

One interesting detail: using the spread between EM and US surprise indexes actually performs worse than using the EM index alone. Sometimes simpler really is better.

Valuation: PPP Beats Everything Else

Valuation in FX is notoriously weak. There’s no P/E ratio for currencies. No book value. The authors are upfront about this: “valuation means very little” for FX. But when currencies get extremely cheap or expensive, it does start to matter.

The two main approaches are REER (real effective exchange rate) and PPP (purchasing power parity). REER basically tracks how a currency has moved after adjusting for inflation, relative to a historical baseline. The problem is that the baseline is arbitrary. Who says the starting point was fair value?

PPP takes a different angle. Similar goods should cost similar amounts across countries. If a Big Mac costs way more in one country than another, the exchange rate is probably out of whack. The authors use IMF PPP data rather than the Big Mac Index (too narrow), and they note that in the age of web scraping, even better PPP measures could be built.

Here’s the key result. When you rank currencies by cheapness using both methods and go long the cheapest four against the most expensive four, PPP generates meaningfully better returns than REER. Across every lookback window tested, PPP was superior. And for both approaches, longer lookback windows work better. The 10-year window produced the best information ratio.

The authors’ view is that investors focus too much on REER and not enough on PPP. That’s a mistake.

One more thing. Valuation alone isn’t really tradable as a standalone strategy. The information ratios are too low. But as one factor among several, it helps.

Terms of Trade Make Valuation Better

If simple REER doesn’t work great, can you fix it? The authors say yes, by adjusting for terms of trade (ToT) shocks.

Terms of trade measure export prices divided by import prices. When commodity prices swing wildly, the competitive position of commodity-exporting (or importing) countries changes fast. A country whose REER looks expensive might actually be fairly valued if its export commodities just surged in price.

The authors use Citi’s commodity terms of trade (CTOT) data to adjust REER valuations. They run a rolling regression of REER on CTOT, then trade the residuals. The result: an information ratio of 0.4, a solid improvement over plain REER. Still not amazing as a standalone strategy. But useful as part of a broader toolkit.

The CTOT-adjusted strategy works particularly well for commodity currencies in Latin America and CEEMEA, which makes sense. If you’re trading the Chilean peso or the South African rand, you’d better be thinking about commodity prices.

Momentum: Still Works, But Not Like It Used To

Short-term momentum in EMFX still generates alpha. The basic idea: buy currencies that went up recently, sell currencies that went down. Herding behavior is the driver. Rising prices create greed, falling prices create fear, and both feed on themselves.

The authors test momentum across different time horizons and find that one-month momentum works best. The volatility-adjusted, long-only version has an IR of 0.86. That’s tradable. But there are meaningful drawdowns, and the strategy clearly worked better before 2008 than after. The golden era of momentum is behind us.

A few specifics from their results. Volatility-adjusted momentum beats raw momentum across every specification. Long-only beats long-short in terms of IR. And combining long-only with long-short helps because they tend to be negatively correlated during drawdowns.

Now here’s the twist. If you extend the lookback period to three years, the long-only momentum strategy starts losing money. That’s mean reversion kicking in. Currencies that went up for three years tend to come back down. But the long-short version still ekes out positive returns even at three years.

In practice, you’d want to combine short-term momentum with long-term mean reversion. Ride the trend in the short run, fade it in the long run.

Breadth: A Quiet But Useful Signal

Breadth is about whether the whole market is moving together or just a few outliers. A healthy rally has most EM currencies going up. If gains are driven by only a few stars, the rally is fragile. One negative shock to a leader, or stretched valuations between leaders and laggards, and it can all unravel.

The authors measure breadth by counting up days versus down days across all EMFX currencies over different periods. When breadth is improving, it pays to be long EMFX. When it’s deteriorating, get out.

It’s not a great tool for calling turns. It won’t tell you exactly when the market is about to flip. But it keeps you on the right side of the trend. Think of it as a health check for the rally rather than a timing tool.

Flows Follow Price. Don’t Follow the Flows.

This section might ruffle some feathers. A lot of people in FX obsess over flow data. The authors are “broadly sceptical” that flows are useful for forward-looking analysis.

Their argument: flows mostly follow or are coincident with price action, not the other way around. They show this with Asia equity flows and Asia FX. At almost every top and bottom, FX moves first and flows follow. If anything, FX leads.

There’s one interesting exception they flag. In 2017, Asia FX rallied strongly but equity flows never confirmed the move. The flows turned out to be right. Asia growth never recovered enough to support the currency strength, and 2018 was a terrible year for Asia FX. So the rare times when flows diverge from price action might actually be worth paying attention to.

On the FX flow side, the same story. Leveraged investor flows are mostly coincident or lagging at peaks and bottoms. The one thing that occasionally works is when leveraged flows accelerate after a turning point and the currency hasn’t caught up yet.

The CitiFX quants found one useful refinement. When leveraged money and real money flows are moving in opposite directions, pay attention. Leveraged accounts tend to move first, and real money eventually follows. That creates some persistence in flows that can be traded.

But overall? Don’t build your EMFX strategy around flow data. Use it as a positioning indicator, not a directional signal.

Trump vs. AMLO: A Lesson in Positioning

Here’s a great case study. Both the election of Trump (November 2016) and AMLO (July 2018) were arguably negative shocks for Mexican fundamentals. Trump threatened to blow up NAFTA. AMLO threatened to reverse energy reforms. Both were bad for the peso.

But the market reactions were completely different. After Trump’s election, USD/MXN exploded higher and kept going for two months. After AMLO’s election, USD/MXN barely moved and then started falling.

Why? Positioning.

Going into the Trump election, leveraged money was massively long MXN. The z-score of cumulative positioning was close to three. Everyone was on the same side of the boat. When Trump won, they all ran for the exit at once.

Going into the AMLO election, leveraged money was only modestly long MXN and had been reducing positions. Real money was actually short. So when AMLO won (as expected), there was no crowded trade to unwind. The initial move was small, and then the peso actually rallied as investors put on new positions.

The lesson: the same fundamental shock can produce completely opposite market reactions depending on how people are positioned. Flow and positioning data won’t tell you which direction a currency should go. But it will tell you how violent the move might be.

Consensus Is Good For You

This one is counterintuitive. Most people think crowded trades are dangerous. If everyone is positioned the same way, you should do the opposite, right?

Wrong. At least for MXN.

The authors bucketed CFTC positioning data into percentiles and looked at three-month forward returns. In 7 out of 10 percentiles, going with the consensus produced positive excess returns. The average excess return across all percentiles was +0.9%. There was no evidence that extreme positioning works as a contrarian indicator.

When speculators are very long MXN (90th percentile), forward returns for being long MXN are still positive. When they’re very short (10th percentile), forward returns for being short MXN are also positive. Consensus tends to be right.

The authors’ conclusion: use positioning as a momentum indicator, not a contrarian one. Go with the crowd, not against it. The one exception is during bear markets. When most real money EM funds are losing money on overweight positions, they’re forced to sell. Losses beget losses. Shorting EMFX during those periods is profitable. This lines up with Kahneman’s finding that losses hurt twice as much as gains feel good. When fund managers are in pain, they cut positions, which drives prices lower, which causes more pain.

Seasonality: Respect the Seasons

Some FX flows are calendar-driven. Corporate dividend payments, year-end liquidity needs, even remittances (Mexico sees a surge in May for Mother’s Day, though that one is too small and well-known to trade).

The authors study weekly seasonals using a 10-year lookback window. They trigger trades when seasonal patterns are more than 1% above or below the median. After volatility-adjusting across all liquid EMFX currencies, the aggregate strategy has an IR of 1.0. That’s really good.

Individually, 15 out of 21 currencies tested have a positive IR from seasonals. The best performer is the South African rand (IR of 0.95). Other tradable seasonal strategies exist for the Israeli shekel, Chilean peso, Singapore dollar, Korean won, and Thai baht.

The authors prefer seasonal patterns that come with a fundamental explanation, like corporate flows or liquidity events. But they keep an open mind about trading seasonals even when they can’t fully explain the underlying reason.

Low Volatility Is Your Friend

Here’s a common misconception: banks blame poor trading results on low volatility. But then they also blame losses on high-volatility events. So which is it?

For EM investors, the answer is clear. Low volatility is good. Period.

When vol is low, you collect carry without big capital losses. And investors respond to low vol by adding more carry trades, which pushes high-carry currencies even higher. It’s a virtuous cycle.

The authors tested this directly. They went long EMFX whenever implied vol dropped to its bottom fifth percentile (over a two-year lookback). Result: it made money, slightly better than the index. Low vol staying low for extended periods is perfectly normal and not a signal to get defensive.

On the flip side, going long EMFX when vol spikes to its top fifth percentile? Still a money loser. You’d think that buying after a vol spike would let you catch the snap-back. But it doesn’t work reliably. High vol is hard to time. Being even one day early can cause major losses. And risk management forces you to size small during volatile periods, so even when you catch the turn, you can’t make much from it.

The practical takeaway: if low vol is your main reason to like EMFX, use options to express that view. You get the upside exposure while limiting the damage if vol suddenly spikes. And when ranking currencies, implied volatility is a better ranking tool than realized volatility.

Putting It All Together

Here’s the hierarchy of what works, roughly from best to worst:

1. Growth surprises are the single best factor. Buy EMFX when EM economic data beats expectations.
2. Short-term momentum (one month, volatility-adjusted) still generates solid alpha.
3. Seasonals quietly deliver consistent returns with an IR of 1.0 in aggregate.
4. Carry + trade balance improvement works better than carry alone.
5. PPP valuation helps at extremes, especially with a long lookback.
6. Breadth keeps you on the right side of trends.
7. Terms of trade improve REER-based valuation models.
8. Positioning works best as a momentum indicator, not contrarian.
9. Flows are mostly a lagging indicator. Useful mainly for detecting extreme positioning.

The overarching theme: EMFX trading is a multi-factor game. No single factor is a money printer. But combining fundamentals (growth, carry, current account trends) with technicals (momentum, breadth, seasonals) and using volatility adjustments everywhere gives you the best shot at consistent returns.

And one more thing the authors keep coming back to: volatility adjustments improve almost everything. Whether it’s carry, momentum, or breadth, adjusting for volatility makes every strategy work better. If you take one mechanical lesson from this chapter, it’s that.

Book Details:

• Title: Trading Fixed Income and FX in Emerging Markets
• Authors: Dirk Willer, Ram Bala Chandran, Kenneth Lam
• Publisher: Wiley
• Year: 2020
• ISBN: 978-1-119-59905-0

Previous: How to Trade EMFX Part 1 Next: EMFX Event Guide