Trading Growth and the Business Cycle: GDP, PMIs, Retail Sales and Sentiment

What do growth data show?

Growth data describe how strongly an economy is expanding or shrinking. The most comprehensive measure is gross domestic product (GDP), the value of all goods and services of a country. Because it is published only quarterly and with a delay, traders also look at faster figures: surveys of purchasing managers and consumers, retail sales and industrial production.

For the central bank, growth is the second side next to inflation. If the economy grows strongly, it can keep rates high, and if it weakens, cuts become more likely. Economic data therefore move currencies through rate expectations, and stocks directly through companies' earnings prospects.

The most important economic data and their dates

Leading indicators: purchasing managers' indices and sentiment surveys

Purchasing managers' indices ask companies whether orders, output, employment and prices are rising or falling compared with the previous month. A reading above 50 means more companies report an improvement than a deterioration, a reading below 50 the opposite. Because the surveys are conducted during the current month, they are among the earliest economic signals.

There are separate indices for manufacturing and services and a combined figure (composite). In the US two series come out: the PMIs from S&P Global and the indices of the Institute for Supply Management (ISM), which the market usually watches more closely. The sub-indices provide further hints: new orders show coming demand, prices paid the cost pressure that can later feed into inflation.

Sentiment surveys such as the Ifo business climate index, the ZEW economic expectations, the University of Michigan consumer sentiment or the Conference Board consumer confidence measure expectations rather than results. They are therefore called "soft data", as opposed to "hard data" such as sales and output. If the two diverge, caution is warranted.

Consumption and industry: the hard monthly data

Private consumption is the largest part of GDP in most major economies. Monthly retail sales are therefore an important release, in the US especially the control group excluding autos, gasoline, building materials and restaurants, which feeds directly into the GDP calculation. Added to this is personal spending, which in the US comes out together with the PCE price index.

On the industry side, industrial production and factory orders show how much is actually produced and ordered. In the US, orders for durable goods are watched closely because they reflect business investment. Aircraft orders make this figure volatile, however, which is why there is a version excluding transportation.

How do you read growth data?

As always, what counts for all economic data is the surprise against the consensus. Beyond that, each figure has its own pitfalls.

• GDP annualised or not: the US reports quarterly growth scaled up to a full year, the euro area and the UK do not. A US figure of 2% is roughly 0.5% for the quarter.
• First estimate and revisions: US GDP comes in three estimates, the first about a month after the end of the quarter. Later estimates usually move prices less.
• Composition: strong GDP driven by inventory building or government spending says less than growth driven by consumption and investment.
• PMI: level and direction: a reading of 49 is contraction, but after 46 it is an improvement. The market reacts to the distance from the consensus and from 50.
• Flash and final PMI: the flash estimate moves prices, the final figure at the start of the following month usually hardly at all.
• Real or nominal: retail sales are usually reported in nominal terms. If they rise 0.5% while prices rise 0.5%, nothing has grown in real terms.

The chain of effects: what an economic surprise moves

Stronger economic data than expected raise rate expectations and improve earnings prospects, weaker data lower both. Unlike with inflation, stocks therefore often benefit from good figures.

• Bonds: strong data lift yields, weak data lower them, especially at short maturities.
• Currency: strong growth tends to strengthen a currency. Commodity currencies such as the Australian dollar also react to economic data from China.
• Stocks and indices: a good economy helps earnings, especially in cyclical sectors. It can, however, mean higher rates, which weighs on valuations.
• Gold: strong US data and a firmer dollar tend to weigh on gold. Growth worries tend to support it.
• Cryptocurrencies: Bitcoin often reacts to major US economic data like other risk assets, depending on whether the market currently fears rates or growth more.

When the chain breaks

• Good news, bad prices: if the market mainly fears higher rates, a strong figure pushes stocks lower.
• Soft vs hard data: if sentiment falls but sales and output hold, the market often reacts only briefly.
• Revisions and special effects: strikes, weather or holidays distort individual months.
• Stagflation: weak growth with high inflation leaves the central bank little room. The currency then reacts inconsistently.

GDP or purchasing managers' index: which moves more?

Usually the purchasing managers' index. GDP is comprehensive, but it comes out weeks after the end of the quarter and describes a period the market already knows from many monthly figures. The PMI comes out in the same month and shows a turn earlier. Large GDP surprises still move prices, especially when they signal a recession.

Teaching examples

The following cases are teaching examples with round numbers, not real releases, and give no price moves in pips or percent.

Teaching example 1: the PMI falls below 50

For the manufacturing PMI of a major currency area, the consensus expects 50.5, and 48.9 is reported. The index falls not only below the consensus but also below the threshold of 50. The new orders sub-index drops even more. The market reads this as a sign of cooling, rate expectations fall, and the currency tends to weaken.

Teaching example 2: strong GDP with a weak core

GDP grows 3% annualised instead of the expected 2%. The components show, however, that almost all of the increase comes from inventory building, while private consumption stagnates. The first reaction follows the headline, then the market puts the figure into perspective. Anyone trading only the surprise often ends up on the wrong side.

Teaching example 3: sentiment slumps, hard data hold

The economic expectations of a financial market survey fall sharply, but retail sales for the same month are in line. The sentiment figure moves prices briefly, the hard data dampen the reaction. If sentiment stays weak in the following months, it gains importance, because it can herald a turn in the hard data.

Economic data in each trading style

Economic data come out almost every day. Short-term traders have to choose which ones really count, long-term traders watch the trend over months.

Economic data in scalping (15m, 30m)

In scalping on 15m and 30m, the flash PMIs and US retail sales are the most important economic releases. The PMIs for Germany, the euro area and the UK come out on the same morning in quick succession, moving EUR and GBP pairs in short bursts. Before every high-impact release the scalper is flat.

The earliest entry is after the first closed 15m candle. A breakout from its range or the pullback to the breakout level are common approaches, with the stop behind the range. The European PMIs fall into the London session, the US data at 8:30 a.m. New York time into the overlap with New York. In crypto, mainly the major US releases have an effect.

Economic data in day trading (1h, 2h)

In day trading on 1h and 2h, it pays to sort the day's economic releases in advance: which carry high impact, and which currency do they belong to? A weak Ifo index in the morning can weigh on the euro into the afternoon if US data do not override it.

After the release, the closed 1h candle is the yardstick. An entry follows the close beyond the range of the release candle, with the stop on the other side. Before the release, positions are reduced or protected, and they are closed before the end of the session.

Economic data in swing trading (4h, 8h)

In swing trading on 4h and 8h, you hold through most economic releases. What matters are the weeks in which several major figures come together, such as PMIs, retail sales and GDP. The stop sits behind a real structure, and the position size can absorb a spike.

After the release, what counts is whether the 4h and 8h candles confirm the trend. A series of weak data from one currency area can start a swing against that currency. A single surprise that the other data do not confirm is often unwound again.

Economic data in position trading (12h, 1d)

In position trading on 12h and 1d, the business cycle counts. If PMIs fall over months, consumption weakens and sentiment readings decline, the economy is cooling. That makes rate cuts more likely and changes the broad direction of a currency relative to others.

Single releases are milestones at this level. The stop is far enough away that a single figure does not reach it. In the FinScans cockpit, the news situation counts for more than the technicals on the long horizon, as the methodology on horizons explains.

Economic data and technical signals

Around high-impact economic data, more false signals appear. A break of a trendline or of a support and resistance level in the first minute is often just a spike. Only the closed candle after the release shows whether it holds.

FinScans signals exist for forex and crypto pairs. They are updated candle by candle and are often closed early when the market turns, as the methodology describes. Read a signal that appeared shortly before an important economic release with caution.

How to use FinScans for economic data

In the FinScans calendar, economic data are spread across four categories: "Growth" for GDP, "Industry" for purchasing managers' indices, industrial production and orders, "Consumption" for retail sales and personal spending, and "Sentiment" for Ifo, ZEW and the US consumer surveys. The GDP releases in the calendar and the purchasing managers' indices and industry data in the calendar can be filtered on their own, and consumption and sentiment likewise via the category filter.

Among others, the GDP of the major currency areas, the PMI and ISM indices of the major countries, retail sales, Ifo and ZEW and the US consumer surveys carry three dots for high impact. In the cockpit, a heads-up appears at the overall assessment when such a release is due or has just been published, and the box "Economic data for …" rates the figure as better or worse than expected for the currency. How economic reports feed into the news situation is described in the methodology on the news situation.

The next GDP releases and the most recently published values from the FinScans calendar:

Purchasing managers' indices and industry data:

Hybrid checklist: what the machine reports, what you check yourself

FinScans provides the release, consensus, actual value and the assessment for the currency. How reliable an economic figure is, you judge yourself, as described in hybrid trading. Around economic data, check:

1. Is the figure a leading indicator or hard data, and is it a flash estimate?
2. Is a PMI above or below 50, and has the direction changed compared with the previous month?
3. Where does the growth come from: consumption and investment, or inventories and government?
4. Do other data from the same currency area confirm the picture?
5. Is my position small enough and my stop set so that a spike remains bearable? More on this in risk management.
6. Does the reaction fit the news situation in the cockpit and the trend of the higher timeframe?

Frequently asked questions

What does a purchasing managers' index of 50 mean?

A reading of 50 is the threshold between growth and contraction. Above it, more of the surveyed companies report an improvement than a deterioration compared with the previous month, and below it deteriorations predominate. For prices, besides the threshold, the distance from the consensus and the direction compared with the previous month count.

Why does GDP often move prices less than expected?

Because it comes out late. When the first estimate arrives, the quarter has been over for weeks, and the market knows most of the components from monthly data such as retail sales, industry and purchasing managers' indices. Large surprises still move prices, especially when they hint at a recession or when the composition of growth is different than thought.

What is the difference between soft and hard data?

Soft data are surveys of sentiment and expectations, such as purchasing managers' indices, Ifo or consumer sentiment. Hard data measure actual results such as sales, output or GDP. Soft data come earlier but fluctuate more and can be driven by mood. If the two diverge for months, they usually converge again at some point.

Which economic data matter most for the euro?

Above all the flash purchasing managers' indices for the euro area and Germany, the Ifo business climate index, the ZEW economic expectations and euro-area GDP. Inflation data also matter because they act on the euro through the ECB. In the FinScans calendar, these releases can be filtered by the currency EUR and the categories.

Sources

• U.S. Bureau of Economic Analysis: Gross Domestic Product, quarterly release with explanations.
• Institute for Supply Management: Manufacturing ISM Report On Business, monthly release.
• ifo Institute: ifo Business Climate Germany, monthly release.