Direct answer
A worked example of “Actual vs Forecast” compares what was released (Actual) with what was expected ahead of time (Forecast), then quantifies the difference as an “error” or “surprise.” The goal is to explain the comparison clearly and help you verify the numbers yourself.
Mechanism and definitions
- Actual: the officially released figure for an economic data item (for example, an inflation rate for a specified period). Treat it as the final, published value.
- Forecast: an expected value published before the release, typically produced by an analysis house, consensus, or internal model.
- Surprise (difference): the simple numerical gap between Actual and Forecast.
- Percent surprise (optional): the gap scaled by the Forecast, to compare relative magnitude.
A reliable worked example must state assumptions about the exact measure, including units (percent vs index), the time window (month, quarter, year), and whether numbers are seasonally adjusted or not. If these do not match between Actual and Forecast, the comparison can be misleading.
Evidence or example (transparent numbers)
Assume an economic release with these shared definitions:
- Measure: “annual inflation rate” (percent)
- Time window: the same reporting period for both values
- Units: percent per year
Given assumptions
- Forecast value published before release: 2.40%
- Actual value released: 2.65%
Compute the surprise
- Absolute surprise = Actual − Forecast = 2.65% − 2.40% = +0.25 percentage points
- Percent surprise = (Actual − Forecast) / Forecast = 0.25% / 2.40% = +0.1042, or about +10.42% relative to the forecast.
Interpretation (non-predictive)
- A positive surprise means the released value was higher than expected.
- The size of the surprise depends on the metric and units; percent surprises and percentage-point surprises are not the same.
Limitations and risks (what can go wrong)
- Mismatch in definitions: Forecast providers may use different adjustments, revisions, or measurement conventions. If the definitions differ, the computed “surprise” is not a true comparison.
- Forecast choice: Using a single forecast number can differ from a consensus average. Two Forecasts can produce different surprise sizes for the same Actual.
- Market and execution complexity: Even if you compute a surprise correctly, real-world outcomes can depend on liquidity, transaction costs, timing, and other news released around the same time.
- No guaranteed relationship: Historically, markets sometimes react to surprises, but the relationship is not fixed; future reactions can differ.
- Revisions: Some datasets are revised later, which can change what “Actual” effectively means for long-term analysis.
Verification or next question
To independently verify, check two items for the same data series and time window:
- What was released (the official “Actual”)—confirm units and adjustments.
- What was expected (the “Forecast”)—confirm the forecast source and its definition.
Next, ask: “Do my Actual and Forecast values refer to the same measure, time window, and unit?” If not, redo the worked example with compatible definitions.