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Gas Storage Fair Price | online Calculator

I haven't read the article but what do you mean by "correct" model? How is it correct?
Correct model is the one, which makes no implausible assumptions.
In this sense I wanted to emphasize that the perfect foresight, which is surprisingly often (mis)used by the energy suppliers, is certainly incorrect.

Another point (besides model correctness) is the model robustness. As I have demonstrated, this simple model from QuantLib gives a pretty broad confidence interval. There are methods to make it narrower (at no cost or at cost of a slight bias) but this is technical know-how :)
 
"All models are wrong, some are useful".

Correct model is the one which makes no implausible assumptions.
Scary remark. How many times have we heard that in the last years?
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"All models are wrong, some are useful".
A practical application of a model is more art and [gut] feeling of the market rather than science.
Even more it makes sense to yield from mathematics and logic what can be yielded from them.

Concrete in this case study: one does not need to be a natgas expert in order to understand that the perfect foresight approach will give (very) upper bound of the storage price.
However, esp. small energy companies still use this approach due to the lack of tools (but first of all lack of understanding the problem). Respectively, they often pay above the fair price.
 
one does not need to be a natgas expert in order to understand that the perfect foresight approach will give (very) upper bound of the storage price.

What is prefect foresight (in a nutshell)? What are the typical use cases? Is that Pareto efficiency?
 
What is prefect foresight (in a nutshell)?
An assumption that the (spot) gas prices are though random, but once you know (at time t as your storage contract begins) which path was realized, you assume know it completely (to the end of contract T).

In a sense, assuming a perfect foresight is just like pricing an American put option just by simulating paths from issue date t to maturity date T and then retrospectively finding the optimal stopping time for each path.
 
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