How To Read The Economic Calendar
Macroeconomic data is the lifeblood of the world's financial markets because it can, and does, influence prices and investor sentiment.
The data releases highlighted in the calendar allow traders to form a picture of how the world's economies are performing and changing, and whether those changes are for better or worse.
These data releases are ranked or rated by their importance and expected market impact. Generally, high-level top-down data releases from developed economies have the biggest impact while low-level data releases and those from the developing economies will have a smaller market impact.
The Anatomy Of The Calendar
There are many economic calendars available to traders, however, all of them tend to follow a similar format and layout.
The image below is shows Pepperstone’s own economic calendar, which can be found here.
The labels highlight the key information in the calendar, which can be filtered by currency and impact. You can also adjust the timezone of the calendar to tie in with your location or particular market sessions you wish to trade.
Why not try opening the calendar using the link above and filtering the contents for yourself? You can do this by clicking on the drop-down menu (located on the right of the time zone tab) under the heading ‘More'.
Understanding the Data
Now we’ve seen the layout and contents of the calendar we can move on to the information contained within it. Economic data releases follow a predetermined schedule and are reported over regular periods eg. weekly, monthly or quarterly etc.
This type of reporting is known as time series, and it allows us to keep track of changes in the data within individual releases, such as unemployment or rates of inflation.
Those data changes can be collected and displayed in charts that provide easy to interpret visual images of trends in the data. We can also plot related time series data against each other. For example in the chart below we can see a steady decline in unemployment in Australia and at the same time an increasing number of new job vacancies in the country.
Surprises Move Markets
Because economic data is released in time series under a known schedule and format, financial analysts can try and forecast what that data and changes in it. For many data points, these forecasts are gathered together and averaged to form what is called the consensus forecast. This average shows what the market's expectations for a specific data release are.
Economic data moves markets and prices when it deviates from previous trends and/or the consensus forecast for the release. These deviations are known as surprises. That is, the bigger the deviation, the bigger the surprise and the bigger the likelihood of a significant market reaction to that surprise.
Markets are forward-looking, and they tend to have bigger reactions to what are known as leading indicators (data that moves ahead of the underlying economy, rather than lagging indicators) which are reported after the underlying economy has moved.
Leading indicators such as PMIs are forward-looking and indicate what's to come, while lagging indicators such as GDP calculations are very backwards-looking and report on what has already happened over say the last three months.
To get the best from the economic calendar you should set the time zone to reflect your location, or the timezone of the instruments you regularly trade and filter the list of currencies and countries the calendar displays to suit your needs and interests.
You can then scroll through the schedule of releases noting the dates and times that are directly relevant to you and plan accordingly. nbsp;
Some releases such as key central bank interest rate decisions and growth data from China or the USA can have a global impact, so it's a good idea to keep track of the dates for these as well.
Macro data tends to be broken down and categorised based on whether that data is forward or backwards looking. Remember, markets are always forward-looking and they price instruments based on their future expectations rather than what has gone, before meaning forward-looking data can have a larger impact on market prices.