In this post (Lean Hogs: Forward Curve) I received a request from a reader about deseasonalized forward curves. I have deepened on these type of charts, and I want to share what I have learned.
Forward curves can be used to search for opportunities in trading with spread futures.
Forward curves can be used to search for opportunities in trading with spread futures.
We can compare actual forward curve with arithmetic average of past years. In SeasonAlgo, they include a different calculation for past years´ average.
This calculation is made of the average forward price together with a convenience yield. This convenience yield introduces a seasonal forward premium.
The seasonal forward premium is a stochastic meaningful quantity estimated from historical data. It is defined with respect to the average forward price rather than the spot price. This model works better in commodity markets where spot prices are not readily available (absence of a reliable index).
The stochastic behavior in forward curves includes external factors such as extreme weather circumstances (outside the average seasonal pattern) and political crisis within producing countries.
Deseasonalized forward curve removes all seasonal effects from the forward curve. Seasonal features may bring noise to a commodity price´s evolution from an economic perspective.
Commodities prices from an economic perspective (excluding seasonality) are affected by many factors. Some of these factors are: supply and demand balance, inventory levels, transportation and storage costs and strategic and political reasons.
As I mentioned earlier, this model is more appropriate for commodities lacking an index for spot prices. A good application is energy markets.
Let´s see a couple of examples in the energy markets. First one is Gasoline. This chart includes actual forward curve (black) and deseasonalized forward curve (red):
The seasonal forward premium is a stochastic meaningful quantity estimated from historical data. It is defined with respect to the average forward price rather than the spot price. This model works better in commodity markets where spot prices are not readily available (absence of a reliable index).
The stochastic behavior in forward curves includes external factors such as extreme weather circumstances (outside the average seasonal pattern) and political crisis within producing countries.
Deseasonalized forward curve removes all seasonal effects from the forward curve. Seasonal features may bring noise to a commodity price´s evolution from an economic perspective.
Commodities prices from an economic perspective (excluding seasonality) are affected by many factors. Some of these factors are: supply and demand balance, inventory levels, transportation and storage costs and strategic and political reasons.
As I mentioned earlier, this model is more appropriate for commodities lacking an index for spot prices. A good application is energy markets.
Let´s see a couple of examples in the energy markets. First one is Gasoline. This chart includes actual forward curve (black) and deseasonalized forward curve (red):
Next example features Natural Gas actual forward curve vs. deseasonalized forward curve.
I will post my progress in these type of charts.
Deseasonalized forward curves charts shown from SeasonAlgo.
Gracias por la explicacion a mi pregunta y por el post. Pero sinceramente sigo sin verle utilidad.
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