The Forecast Error Significance (FES)
The Forecast Error (FE) is self-explanatory – it simply represents the difference between the event’s actual and expected values.
The Forecast Error Significance (FES) is a ratio of the current forecast error (in absolute form) to the average of all past forecast errors (in absolute form).
In a nutshell, a value greater than 1 or less than -1 means that economists’ predictions in respect of the current release were less accurate than usual, while a value between -1 and 1 means that economists’ predictions in relation to actual outcomes were more precise than usual.
A value significantly greater than 1 or less than -1 in conjunction with a high Reaction Correlation Coefficient (RCC) reading may indicate that the currency in question has a better chance of trending in the direction of its initial breakout.