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Natural gas storage valuation is a challenging
topic. It requires both appropriate price models and
optimization models.
We assume that each forward price follows a
geometric Brownian motion process. Spot price also
follows a geometric Brownian motion process, but its
expectation changes from month to month. Since
optimization models are independent of price
simulations, alternative price models can be
implemented in the valuation.
Various models are used for storage valuation,
including "intrinsic rolling with spot and forward",
Monte Carlo simulation with ordinary least square
regression, and Monte Carlo simulation with
stochastic dual dynamic programming. The first
methodology takes both forward and spot prices into
account, while the other two methodologies only use
spot price.
The results show that many factors can impact the
value of a storage, including the term structure of
the forward prices, volatilities of forward and spot
prices, and the operational flexibility of the
storage.
topic. It requires both appropriate price models and
optimization models.
We assume that each forward price follows a
geometric Brownian motion process. Spot price also
follows a geometric Brownian motion process, but its
expectation changes from month to month. Since
optimization models are independent of price
simulations, alternative price models can be
implemented in the valuation.
Various models are used for storage valuation,
including "intrinsic rolling with spot and forward",
Monte Carlo simulation with ordinary least square
regression, and Monte Carlo simulation with
stochastic dual dynamic programming. The first
methodology takes both forward and spot prices into
account, while the other two methodologies only use
spot price.
The results show that many factors can impact the
value of a storage, including the term structure of
the forward prices, volatilities of forward and spot
prices, and the operational flexibility of the
storage.