# How to de-seasonalize natural gas term structure data?

I need to de-seasonalize Nat Gas futures data for a project and am hoping to get good suggestions. As we all know natural gas futures are priced higher for the winter months and to analyze/model the term structure we need to de-seasonalize the data.

Any ideas how would one do it?

• Section 5.2.1 of the book "Commodity Option Pricing - A practioner's guide", by Iain Clark, have provided one such approach for deseasonalizing the natural gas forward curves. – Gordon Aug 14 '14 at 17:33

i) Take several years of historical spot price time series, e.g. TTF spot prices. For year $$i$$ work out a yearly price $$p_{yr,i}$$ by taking the arithmetic average of daily spot prices. Do the same in respect of month number $$j$$ of the same year to get a monthly price $$p_{mth,i}^{j}$$. The monthly shaping factors $$f_{i}$$ are then $$f_{i}=\frac{p_{mth,i}^{j}}{p_{yr,i}}$$. Determine the $$f_{i}$$ for a number of years (where possible i use at least 3, but that is a judgement call), and use their average. As you say, winter will be more expensive, i.e. you expect $$f_{i}>1$$ for $$i\in\{1,2,3,10,11,12\}$$ and $$f_{i}<1$$ for $$i\in\{4,5,6,7,8,9\}$$
Having determined the seasonality factors, one can turn them into a seasonality-related drift term $$\mu(t)$$ to describe W/S term structure.