News-driven FX Trading: How to Trade Events Like the FOMC, CPI, and NFP

When I researched this article, I came across a fascinating account from a trader who almost got his face ripped off trading the Non-Farm Payrolls report.

He’d spent the morning watching EUR/USD consolidate in a tight range ahead of the jobs data. His analysis suggested the number would come in strong, strengthening the dollar. He set up a trade: a sell order on EUR/USD to trigger the moment the report hit.

When NFP came in 80,000 jobs above expectations, the dollar surged just as predicted. His position immediately showed a significant profit. He was feeling pretty smug.

Then, within minutes, EUR/USD reversed violently upward, turning his winning trade into a loser.

By the time the dust settled, the dollar had completely given up its NFP-driven gains and actually closed weaker on the day.

The lesson is that being right about the economic data isn’t enough. You need to be more right than the broader market. The market is a ruthlessly efficient expectations-pricing machine, which makes it hard to outpredict in a way that makes you money.

Let me be upfront: news-driven trading isn’t where I’d personally look for edge as an independent trader. There are far easier places to find inefficiencies, like harvesting risk premia or exploiting structural flows from forced traders. But I recognize many beginners are drawn to the excitement of news events, so let’s talk about why it’s challenging and how you might approach it if you’re determined to try.

Why Macro Events Drive Short-Term Volatility (and Directional Drift)

News events like FOMC meetings, CPI releases, and job reports move the market dramatically because they force rapid updates to market expectations.

The market is extremely good at pricing forward expectations. At any given moment, currencies reflect the collective wisdom about future interest rates, inflation, and economic growth. When new information contradicts those assumptions, everyone has to reposition – fast.

This repositioning creates those explosive price moves we see on news releases.

Take inflation data. If CPI comes in much cooler than expected, traders immediately think, “The Fed will need to start thinking about cutting rates.” Lower expected rates make the dollar less attractive, so everyone rushes to sell it at once. The result? A negative dollar spike within seconds of the release.

EURUSD with US CPI release highlighted. Chart: TradingView

But here’s the interesting part. Research suggests that news-driven moves often have two components:

1. The initial spike (from algorithmic trading and quick-reaction traders)
2. The drift or follow-through (as the market fully digests the implications)

This second component – the drift – is where retail traders might actually have a fighting chance.

Why? Because the drift isn’t just about processing the raw data. It’s about how the market ultimately interprets what that data means for the future. And interpretation takes time.

Studies indicate that macro surprises tend to have staying power when they fundamentally shift the narrative. A single hot inflation print might cause an initial spike, but if it changes the entire market view from “inflation is under control” to “inflation is becoming a problem again,” that creates a multi-day or even multi-week trend, as various participants digest that information.

Remember: for an edge to exist, there needs to be an underlying supply/demand imbalance. During news events, these imbalances come from forced repositioning and the human tendency to gradually process new information rather than instantly incorporate it.

The Characters of Major News Events: Fed Day, CPI, and NFP

Each major event has its own personality. Understanding these distinctive behaviors, and why they exist, can be instructive, although of course they only play out on average.

The Fed Day Two-Step

Fed decisions are fascinating because they’re more about nuance than raw numbers. Everyone knows the Fed is raising rates by 25bps or whatever before the announcement. What they don’t know is how the Fed will frame future policy.

This creates a distinctive pattern that research and observation have identified as the “Fed Day Two-Step.”

Step one: The initial reaction to the rate decision and statement
Step two: The reaction to the press conference and nuance

When researching this article, I found countless examples of Fed days where the market jumped one way on the statement release, then completely reversed during the press conference. This happens because the statement gives you the what, but the press conference reveals the why and how of Fed thinking.

A case in point from March 2023: The Fed hiked rates as expected, but during the press conference, Powell sounded cautious about banking sector stress. The dollar initially strengthened on the hike, then sold off sharply as markets interpreted his tone as dovish.

CPI: The Trend Maker

Data analysis suggests that inflation reports behave differently from Fed decisions. When CPI significantly surprises, it tends to create more sustained, directional moves.

Why? Because inflation directly feeds into interest rate expectations, which drive currency values. And unlike Fed language, which requires interpretation, inflation data is concrete. A big CPI miss either changes the rate outlook or it doesn’t.

Several studies indicate that CPI surprises tend to cause less whipsaw than other data. When U.S. inflation comes in hot, the dollar is more likely to rise sharply and keep rising. When it’s cool, it might fall and stay down.

Look at what happened in November 2022. U.S. CPI came in softer than expected, and the dollar didn’t just drop – it started a multi-week downtrend as markets repriced the entire Fed hiking cycle.

Cherry picking CPI data. Chart: TradingView

Of course, this looks an awful lot like cherry-picking examples to fit the narrative. If you look at enough market data, you’ll find a way to tell any story you like. But if you look at what happens on average, you can start to say useful things.

This might make CPI data a good candidate for trend-following strategies, although as markets become more efficient at absorbing information, we’re likely to see more instant repricing rather than sustained trends.

NFP: The Notorious Whipsaw King

Market data suggests that Non-Farm Payrolls has a well-earned reputation for reversals. Research uncovered numerous instances where a currency pair spiked 80 pips in one direction after NFP, only to completely reverse course within 15 minutes.

This happens for several reasons:

1. Positioning: If everyone is positioned for a strong number, and we get it, there’s no one left to buy after the initial spike. Everyone’s already in.
2. Overreaction: Sometimes price gets pushed to an extreme that doesn’t reflect the data’s actual importance.
3. Liquidity gaps: Liquidity vanishes as everyone pulls orders, leading to exaggerated moves that later normalize.

This could potentially make fading NFP an interesting idea – but I haven’t done it, and whether you can do it under retail trading conditions is a big question.

Positioning Around News

Pre-Event Positioning

Research indicates that before major releases, institutional players tend to reduce risk rather than increase it. They know the uncertainty of a surprise is a wild card they can’t fully control.

This is why you often see consolidation and reduced volatility ahead of big events – the professionals are taking chips off the table, not putting them on.

When institutions do position ahead of events, they typically do so because:

1. Their internal analysis suggests consensus expectations are wrong
2. They’re exploiting skewed positioning in the market
3. They have a view on how the market will interpret the data, regardless of the actual numbers

In research for this article, I found examples of traders explaining how they approached NFP. Rather than trying to predict the exact number, they would look at positioning data (like CFTC’s Commitment of Traders report) to see if speculators were overwhelmingly positioned one way. If everyone was long dollars before NFP, they’d look for opportunities to fade dollar strength regardless of the actual job numbers.

This approach recognizes that market reactions depend as much on positioning as on the news itself. If everyone is positioned for scenario A, even a mild scenario B can cause an outsized move.

Post-Event Herding and Rotation

After a surprise, institutional money tends to move in waves.

First wave: Algorithmic and high-frequency traders react instantly
Second wave: Fast discretionary traders adjust positions (minutes)
Third wave: Slower institutional money reallocates (hours to days)

This sequential reaction creates the “drift” we discussed earlier. The third wave is particularly interesting because it represents real money repositioning based on the new information.

For example, after a surprisingly hawkish Fed decision, you might see:

• Immediate spike in USD (algos)
• Brief consolidation or pullback (as fast money takes profit)
• Gradual uptrend over subsequent days (as pension funds, asset managers, and corporate hedgers adjust their exposures)

This final wave is where patient retail traders might find an opportunity. You can’t compete in the first seconds, but maybe you can ride the more sustainable third wave – at least, that’s where I’d look.

Does the smart money know something?

I did some quick analysis on EURUSD returns pre- and post-NFP releases.

This is what we call an “event study” – it looks at average behavior around a particular event, in this case, NFP releases.

First, here’s a plot that shows the cumulative average hourly returns on NFP days (top plot) and a proxy for hourly volatility, the high-low range (bottom plot). The NFP release is marked with a blue dashed line:

Cumulative average daily returns and volatility on NFP days. Source: robotwealth.com

The returns plot isn’t all that interesting. It suggests that, on average, the NFP data was bullish USD (EURUSD went down) over the historical data.

The volatility plot is interesting – you see volatility compress in the hours before the release, then it explodes, and takes a few hours to settle down again.

The next plot is more interesting.

It shows the average cumulative returns before and after the NFP release as if you knew which way it was going to go ahead of time.

The blue line shows the average return on days when the EURUSD went up after the release. And the red line shows the average return on days when it went down post-release.

Pre and post NFP drift by post NFP drift. Source: robotwealth.com

Of course, the post-release returns are very extreme – I’ve literally sorted them by what actually happened.

But the pre-release returns are really interesting.

You see that on days when the NFP was bullish EURUSD, it actually rose ever so slightly on average before the release. And on days when the release was bearish, it actually went down ever so slightly before the release.

What’s going on here?

Does someone know something the rest of us don’t?

This doesn’t have to be due to any criminal leaking of sensitive data. No doubt there are innovative and well-resourced organizations out there that gather their own data and build their own predictive models for forecasting the NFP numbers, which are probably easier to forecast than the markets themselves.

Could the drift we identified above simply be these well-informed traders positioning themselves? If so, would we want to trade with them?

Also, note that the pre-NFP release drift is tiny – it’s a small effect, and I would guess that it only plays out very much on average.

This implies that sometimes (often, probably), you’ll see behavior that is not at all representative of the average behavior. But maybe there’s enough to go on here to justify exploring further.

Managing Risk During High-Volatility Windows

Trading around news is inherently riskier than trading normal market conditions. Your risk management needs to account for this.

Position Sizing: The Primary Risk Control

Position sizing is the primary risk control.

Rather than relying on stop losses, professionals tend to focus on sizing positions to control their risk.

For news events, a reasonable approach is to reduce your normal position size by the change in volatility that you expect.

Why? Because volatility increases the magnitude of potential moves. A position that would normally give you comfortable breathing room might move against you much more severely during NFP or Fed announcements, thanks to that volatility.

I don’t personally use hard stops for risk management in my own trading. I primarily control risk through position sizing, ensuring that even a significant adverse move won’t be devastating. For news events, this approach is particularly appropriate given the likelihood of gaps and extreme volatility.

Time Stops: An Alternative Approach

Instead of price-based stops, consider using time stops if trading news. A time stop simply means exiting a position after a predetermined amount of time if your expected move hasn’t materialized.

For example, if you enter a trade expecting the dollar to strengthen after a hot CPI print, you might decide: “If the dollar hasn’t continued higher within x hours, I’ll exit.”

The Spread Trap: Broker Behavior During News

One of the most significant hazards of news trading is how brokers handle these events. During major releases, many retail forex brokers:

• Widen their spreads dramatically (EUR/USD might go from 1 pip to 10+ pips)
• Reduce available liquidity
• Execute orders more slowly due to volume
• May even temporarily suspend trading or “freeze” pricing

These practices create a situation where trading costs skyrocket precisely when you’re trying to capitalize on market moves. A widened spread essentially creates a much higher hurdle for profitability.

For example, if you’re normally paying one pip to trade EUR/USD but during NFP you’re paying 8 pips, you need the market to move 8 times further just to break even compared to normal conditions.

EUR/USD spread estimated from tick data over a trading week. Source:robotwealth.com

To mitigate these issues:

1. Research your broker’s typical behavior during news events before trading them (you can download tick data from most brokers and use it to calculate a proxy for spread)
2. Consider ECN brokers who may offer more transparent pricing (though be aware they may have other restrictions)
3. Factor these increased costs into your trade planning
4. Avoid trading when spreads are at their widest

Have a “Circuit Breaker” Rule

Not everyone likes this approach, but it’s one that I’ve used in both professional and independent trading scenarios.

This is a personal rule that if you lose more than a certain amount, you stop trading for the day.

Trading can be emotional. After a loss, there’s a natural tendency to want to “make it back” immediately – a recipe for disaster in volatile conditions.

If you really do have an edge, then staying alive and grinding it out over the long term is the only game in town. You want to give yourself the best chance of making that a reality.

Regardless of how you choose to do it, having a plan for handling the very real emotion of large losses is a good idea.

Why Retail Traders Can’t Usually Trade the News as it Happens

Let’s be brutally honest about something: as retail traders, we’re at a significant disadvantage trying to trade the exact moment of a news release.

Here’s why:

The Speed Gap

Modern markets are dominated by algorithmic trading systems that can:

• Parse economic data in microseconds
• Execute trades in milliseconds
• Process more data points simultaneously than any human

By the time you see the number flash on your screen and click “buy,” the market has already moved. It’s like trying to outrun a Ferrari on foot.

Broker Limitations

As mentioned earlier, many retail brokers:

• Widen spreads dramatically during news
• Execute orders more slowly due to volume
• May even “freeze” pricing briefly

This creates a situation where you might click buy at 1.1000, but your order executes at 1.1025 because of slippage and wide spreads. You’re starting the trade at an immediate disadvantage.

Information Access

Institutions subscribe to premium data feeds that deliver information faster and in machine-readable format. Some even have direct feeds from data providers.

As retail traders, we’re often reading delayed headlines or seeing prices move before we even know what the news was.

All these factors make trading the news as it happens akin to playing poker where everyone else can see your cards. It’s theoretically possible to win occasionally, but the deck is stacked against you.

This doesn’t mean we can’t trade around news – it just means we need to be smarter about when and how we engage, and making sure we focus on areas we can actually compete.

The Futility of Trying to Out-Predict the Market

There’s another fundamental problem with news trading that needs addressing: the belief that you can predict economic data better than the consensus, or interpret it better than the market.

The market is an incredibly efficient expectations-pricing machine. It represents the collective wisdom of thousands of professional economists, strategists, and traders, and countless other participants with all sorts of reasons for being there.

When you decide, for instance, that “CPI will come in higher than expected,” you’re essentially saying that you have better information or analysis than this collective intelligence. That’s a very bold claim.

Research consistently shows that even professional forecasters struggle to consistently beat consensus expectations. And even if you did somehow have superior forecasting ability, you’d still need to predict how the market would react to that surprise, which may not always be obvious.

This is why I personally don’t look for edge in predicting news outcomes. The bar is simply too high, and I’m nowhere near smart enough.

Instead, I’d focus on areas where independent traders have the ability to compete:

1. Harvesting risk premia: Taking on risks that institutions avoid due to mandates or investor preferences
2. Exploiting forced flows: Trading against market participants who have to buy or sell regardless of price
3. Nimbleness: The ability to go where the going’s good – to quickly enter and exit markets that large players can’t move in without impact

Final Thoughts

If you’re drawn to news trading, it’s important to be clear-eyed in your approach. You can’t compete on speed or forecasting ability, so don’t waste your time there.

Instead, focus on how the market might process that news, both in the lead up to, and post the event itself.

For example, if you understand that informed traders might position themselves ahead of the event, you might look at the data to see how good they are at outpredicting the market and take action accordingly.

If you understand when information is likely going to take time to translate into action, you might be able to identify when something is more likely to trend.

If you understand when lack of liquidity might lead to markets being pushed further than they should, then you might be able to identify opportunities to fade extreme moves.

The key is to understand that you’re not trading the news itself – you’re trading how the market processes that news.

While I personally wouldn’t focus my trading on news events (there are easier places to find edge), if you’re determined to go this route, approach it with clear eyes about the challenges and a solid framework for managing the risks.

Trading news events successfully isn’t about having supernatural predictive powers or faster reflexes than the market. It’s about having a structured approach to a chaotic environment, understanding the patterns that tend to recur, and managing risk when volatility spikes.