Dollar rebounds as US payrolls beat forecasts: what a data surprise is
US payrolls rose 165K vs 65K expected while Canada lost jobs. We use USD/CAD's ECB fixing at 1.4066 to explain consensus forecasts and data surprises.
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The US dollar rebounded on 6 November as US jobs data came in far stronger than expected. According to investingLive, US non-farm payrolls rose by 165,000 in October against a forecast of 65,000, while Canada lost 4,700 jobs when economists expected a gain.
Since our overnight lesson on the yen and the tech-stock sell-off, the focus has shifted from stocks to jobs. The ECB reference rates for 6 November show a firmer dollar. The USD/CAD fixing rose 0.72% to 1.4066, from 1.3966 on 5 November. AUD/USD fell 1.85% to 0.6871 and EUR/USD fell 0.53% to 1.1165. Investing.com reports that the tech rout and strong US jobs data lifted safe-haven demand for the dollar. For a wider market wrap, see fxcash's report on the US payrolls beat and Canada's jobs miss.
What is a data surprise?
Before a major economic report, economists publish their forecasts. The typical forecast is called the consensus (often shown as the "expected" figure). Traders set prices partly around that number before the release.
A data surprise is the gap between the actual number and the consensus:
- Surprise = actual minus consensus
Markets tend to react to the surprise, not to the number on its own. A strong figure that everyone expected may barely move a currency. A modest figure that nobody expected can move it a lot.
The spread of forecasts matters too. investingLive explains that when data deviates from expectations it creates a surprise effect, and that how forecasts cluster inside the range also shapes the reaction.
A worked example
US payrolls. The consensus was +65K, within a range of +50K to +125K, according to investingLive's preview.
- Surprise: 165K minus 65K = +100K
- Distance above the highest forecast: 165K minus 125K = 40K
Other parts of the report also beat expectations. Unemployment was 4.1% against 4.2% expected, 0.1 point lower. Average hourly earnings rose 3.1% from a year earlier against 2.9% expected, 0.2 point higher. The prior month was also revised up, from +29K to +60K.
Canada jobs. The consensus was +13.6K.
- Surprise: minus 4.7K minus 13.6K = minus 18.3K
- Unemployment: 6.7% against 6.5% expected, 0.2 point worse
The currency move. USD/CAD puts both surprises in one price, because a strong US number and a weak Canadian number point the same way.
- Change: 1.4066 minus 1.3966 = 0.0100, or 100 pips (a pip is 0.0001 here)
- Percentage: 0.0100 divided by 1.3966, times 100 = about 0.72%
One caution: the ECB fixing is a single official rate per day, not a live quote. From the fixings alone we cannot tell how much of this 100-pip move happened after the jobs releases.
A smaller surprise. investingLive reports US consumer sentiment at 51.0 against 48.0 expected, a +3.0 surprise. The same source notes that this survey has lost some of its weight in markets, because its readings often do not match actual spending.
Why it matters for new traders
- The gap drives the reaction. "165K jobs" means little without knowing that 65K was expected.
- Size matters. A result outside the whole forecast range, as with US payrolls, is a bigger shock than one inside it.
- Reports have many parts. Jobs, unemployment, wages and revisions can point in different directions. Today most pointed the same way.
- Not all data is equal. Markets weight payrolls more heavily than some surveys.
- Pairs have two sides. USD/CAD reacted to surprises from both countries on the same day.
Key terms
- Consensus forecast: the typical economist estimate published before a data release.
- Data surprise: the actual figure minus the consensus.
- Forecast range: the lowest to highest estimates submitted.
- Revision: a later correction to a previously published figure.
- Non-farm payrolls (NFP): the monthly count of US jobs added outside farming.
- Fixing: the ECB's official daily reference rate, not a live market price.
How we make this article: software gathers the market data and the news from the sources linked in the article, then cross-checks them. AI writes the text. People choose the sources, set the rules and run the process. Not investment advice.