Macro data and the economic calendar

This lesson explains what exactly moves price at the moment macroeconomic data is published, and how to prepare your position for that moment instead of guessing the outcome of the release. It is written for a retail trader who trades currencies, indices or stocks and wants a repeatable protocol for publication days — not for someone looking for an inflation forecast for the coming quarter.

How macro releases move the market

A report on inflation, employment or retail sales does not change the economy straight away, but it does change what the market expects from interest rates and from the pace of growth. That shift in expectations feeds into the spread and into the valuation of a position within seconds, because every participant reads the same release at the same moment. The effect is visible on CFDs on currencies and indices, on bonds, and on the Warsaw exchange mostly through global sentiment and the USD/PLN or EUR/PLN rate — not through the local reading alone.

You do not have to be an economist. You have to know when the release lands and what you do with your position before it.

The publication time depends on the time zone of the institution that puts it out. That is why the first step is not analysing the number, but writing the times down in your own clock.

Which data moves price most often

The order of these releases matters too. A single week can contain several strong readings, and then volatility accumulates and only returns to normal after the last of them. It is worth noting in your week calendar whether the week is “heavy with data”, because that decides whether a smaller position size applies to one day or to the whole week.

How to read a release: consensus, previous value and surprise

In a press release you will usually see four numbers: the reading (the published value), the consensus (the median of analysts’ expectations), the previous value and its revision. The media most often quote the reading and the consensus, but for your position what counts is the difference, not the level.

The basic definition is the surprise, that is the deviation of the reading from the consensus:

surprise          = reading − consensus
relative_surprise = (reading − consensus) / |consensus|

The second formula expresses the surprise as a percentage of the expectation, which lets you compare releases quoted in different units — inflation in percentage points against thousands of jobs. If the release has a history, you can go one step further and relate the surprise to the typical size of surprises from recent months: divide the current surprise by the average absolute surprise over that period. A result close to zero means a release in line with expectations, while a value clearly outside the typical range means a reading that changes valuations.

Two more rules are easy to overlook. First, the previous value is often revised, and the revision alone moves the market even when the current reading matches the consensus. Second, the consensus is not an official parameter — it is an aggregate of institutional forecasts that can be widely dispersed before publication. Check what spread of forecasts your calendar source reports.

Example: the surprise and a reaction template

The table below shows the mechanism, not a forecast. The direction of the move does not come from a “pretty” number, but from the difference against expectations and from whether the market had already priced it in. All values are illustrative figures:

The first minute after publication contains the most noise and the worst liquidity. A plan to wait “until the spread calms down” is therefore healthier than trying to catch the first move — and when a release matches the consensus, there is often nothing to trade.

A worked example with illustrative numbers. The consensus expects 2.4 per cent and the reading comes in at 2.7 per cent. Surprise: 2.7 − 2.4 = 0.3 percentage points. Relative surprise: (2.7 − 2.4) / |2.4| = 12.5 per cent of the expectation. If your notes from recent months show that the typical surprise for this release is 0.1 percentage points, then the current one is three times the typical size — and that is information about the scale of the reaction, still without saying anything about direction. The figures in this paragraph are illustrative; you check the real consensus and reading in the calendar and in the release from the publishing institution.

A protocol for preparing for a release

Carry out these steps in this order, before the session, not during the release.

1. List the week’s releases from a source, in your local time. Write down the day, the time and the publishing institution. Times are sometimes changed, so check them before every session, not once a quarter.
2. Write down the consensus, the previous value and the spread of forecasts. These values change every month — check them at the source, not from memory.
3. Calculate the surprise after the release, not before. Before a release there is no surprise; there is only a plan for three variants (in line, higher, lower).
4. Assign the release an exposure class. Add one of three labels to each event: flat before publication, smaller size with a wider stop, or entry only after the spread calms down. The label has to exist before the session.
5. Write down the maximum loss in R. If you stay in a position through the release, work out the exit condition and the loss limit in advance — the starting point is the 1–2 per cent of capital rule, not “it will somehow work out”.
6. Record the spread around the release. Comparing the spread on a publication day with the spread on an ordinary day shows whether the cost ate part of your edge. You will find the method for calculating cost in the lesson on round-trip costs.

Steps 3 and 4 happen at two separate moments: the plan before the release, the measurement after it. Without the second stage you do not know whether the rule works or merely sounds sensible.

Worksheet: your own plan for releases

Copy the table into a spreadsheet and fill it in every week. The columns are deliberately empty — value comes from what you enter based on your own sources and your own instrument.

Fill in the columns from “Plan” to “Spread” before publication and the “Result” column after the trade is closed. After a dozen rows or so you will see on which releases your rules actually protect capital and on which they merely step around it. You carry the metrics from such records forward according to the rules described in the lesson Journaling and metrics.

When the calendar says “do not trade”

Four conditions, each in the form of a rule. Meeting any one of them means skipping the trade or postponing entry — not “a smaller size to give it a try”.

1. You do not know the publication time, or you cannot point to its source. If you cannot show where the date and time came from, you do not have a plan — you have a guess. A decision without a source gets skipped along with the setup.
2. You intend to enter inside a window of a few minutes around the release without a written news playbook. Entering into the worst liquidity of the day is a bet on volatility, not a strategy.
3. Your position needs a tight stop in order to fit inside your risk limit. A release regularly exceeds the typical range of movement from recent sessions, so a stop set “below a round number” will be taken out by noise. Instead of stretching it, reduce size or stay out.
4. You trade during hours when your instrument is illiquid. A release at dawn in your local time will not turn a thin market liquid — quite the opposite, it will widen the spread and deepen slippage.

The order of action is the reverse of intuition: first you reject, then you plan. You write the rejections down too, because without them you cannot tell discipline from fear.

The most common mistakes with macro data

• Maximum leverage “because I know how it will come out”. A release cannot be predicted in advance, and a lucky guess is not an edge.
• Ignoring the calendar on the instruments you follow. This also applies to ETFs tracking global indices, which breathe with US readings even if you settle them in another currency.
• Confusing a media comment with your own risk plan. The headline describes what happened; the plan answers what you do with your position.
• Entering on the first candle after publication without a defined rule. The first candle contains the most noise and the worst liquidity.
• Treating local data as irrelevant. A global move towards safe assets reaches the local market through the currency rate as well.
• Forgetting the revision of the previous value. A correction to the earlier reading can move valuations while the current number sits exactly on the consensus.

Measurable exercise

Open the calendar for the coming week and list the three releases with the greatest impact on the instruments you actually trade. For each of them, complete a row of the table above before publication: the time, the consensus, the previous value and the plan label. After publication add the reading, calculate the surprise and the relative surprise, and compare the spread with the typical spread of a day without a release.

After three weeks, count two things: how many times the reading fell inside the typical range of surprises, and how many times the spread around the release exceeded your planned cost. This is not a test of how well the strategy works — it is a test of whether your exposure rule rests on measurement or on impression.

Check yourself

Common questions

Do I have to trade on a day when data is published?

No. No edge in releases means you do not trade them. The calendar is there to protect capital and to make a conscious decision about exposure, not to find an opportunity in every event.

Why is the consensus more important than the reading itself?

Because the market prices expectations in advance. A number in line with the consensus brings no new information, while a deviation from it changes the valuation of rates and of the pace of growth. The new information is the surprise, not the level.

Does local data matter if I only trade a pair with the US dollar?

With a pure dollar pair the impact of local readings is smaller, but not zero: it works through the local currency rate, through local stocks and through credit. A global move towards safe assets arrives by that route as well.

Why calculate the surprise and normalise it instead of judging the release by eye?

Because a judgement like "a strong reading" changes with the mood, while a number does not. The surprise in percentage points lets you compare the reading with the expectation, and dividing it by the typical size of surprises from recent months brings different releases onto one common scale. That way you know whether the reading is large against its own history or merely large in the headline. Only from recorded numbers can you work out whether your exposure rule works or just looks cautious — without measurement you have nothing to compare. Always check the current consensus and reading at the source, because they change every month.