Since consensus forecast number becomes well-known some time prior to the release date, the market usually prices it in before the moment of release. So the major potential fluctuations on the market at the moment of release will depend on how large difference will be between actual data and expected number. It’s obvious that the greater the difference the greater the moves and volatility and the faster the market will swing on the way in a row with that difference. Unfortunately it almost impossible to predict, how much the market has priced in and has it priced in something at all. That’s why many traders skip the moment of release, stay flat and open positions only after the first fast reaction. Usually a trader passes through heavy thoughts as “what will happen if…” and keeps an eye on data and market sentiment right before the release. Still, there could be very accurate work to be done, that will allow you to increase accuracy significantly. And that work is statistics. What the major issues of that work are: 1. Categorize macro data in groups, for example “extremely important”, “medium importance” and “low importance”. This is necessary, because far less macro data is very important to make the greater difference that we need to shift market; 2. Make an observation for all major macro statistics past moments of releases, what difference has taken place and what market move was. This will tell you, what the smallest difference should happen to move market with particular data – GDP or, say Retail sales etc.. For instance, if Non-farm Payrolls will release 10% lower it historically moves EUR/USD up for 50 pips. Also you will find the borders “as expected” results, say, if data releases with less than 5%, the difference from consensus market usually does not show any respect to that. And when you will see that Payrolls has been released just 3 % higher – you will skip this trade and save a lot of money. Felix Homogratus and Stavro D'Amore do excellent work with this.