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Seasonality Chart

Energy prices move with the seasons: gas rises into winter and falls in spring, power follows demand and weather. The Seasonality Chart turns a price history into a heatmap of percentage changes so the pattern stands out. It answers questions like:

  • In which months does German day-ahead power usually rise or fall?
  • Was this March unusual compared with other years?
  • How did the front month TTF contract change over each whole year?

At Northgate Energy, Tom Clarke opens it on the German day-ahead base price NGE.POWER.DE:DA_BASE to check whether the autumn rise this year looks like other years.

The Seasonality Chart for German day-ahead base power, with a row per month and a column per year

Opening the report​

The report works on one item, so you open it from the item's insights on the Data screen. It is registered as Seasonality Chart (#SEASONALITY) in the Data Insights category and is hidden from the Reports list.

Item typeWhat happens
Timeseries, smart timeseries, event timeseriesThe chart is drawn straight away
Curve, smart curve, event curveA Select a tenor list appears with the curve's tenors. The first tenor is charted; choose another to chart that one.
Anything elseNothing is drawn

The Seasonality Chart for the M01 tenor of the TTF mid curve

Reading the chart​

PartWhat it shows
ColumnsOne per year, from the first year of data
Rows Jan to DecThe percentage change over that month: the value at the end of the month compared with the end of the previous month
Row Year (outlined)The percentage change over the whole year, from year end to year end
ColoursDark red for the biggest falls, pink for small falls, dark green for small rises and light green for the biggest rises. The legend on the right shows the ranges.

The values are calculated on the platform from the item's data with the expressions pct(scale(BASE,'MONTHLY','end'))*100 and pct(scale(BASE,'YEARLY','end'))*100, rounded to 2 decimal places. The current year shows the months so far.

tip

The colour bands are set from the largest fall and the largest rise in the chart, split at a quarter of each. One extreme month can make every other change look small, so read the numbers as well as the colours.