Natural Gas Storage Valuation
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In this thesis, one methodology for natural gas storage valuation is developed and two methodologies are improved. Then all of the three methodologies are applied to a storage contract. The first methodology is called "intrinsic rolling with spot and forward", which takes both the spot and forward prices into account in the valuation. This method is based on the trading strategy by which a trader locks the spot and forward positions by solving an optimization problem based on the market information on the first day. In the following days, the trader can obtain added value by adjusting the positions based on new market information. The storage value is the sum of the first day's value and the added values in the following days. The problem can be expressed by a Bellman equation and solved recursively. A crucial issue in the implementation is how to compute the expected value in the next period conditioned on the information in current period. One way to compute the expected value is Monte Carlo simulation with ordinary least square regression. However, if all of the state variables, spot, and forward prices are incorporated in the regression there are too many terms, and the regression becomes uncontrollable. To solve this issue, three risk factors are chosen by performing principle component analysis. Dimension of the regression is greatly reduced by only incorporating the three risk factors. Both the second methodology and the third methodology only consider the spot price in the valuation. The second methodology uses Monte Carlo simulation with ordinary least square regression, which is based on the work of Boogert and Jong (2006). The third methodology uses stochastic dual dynamic programming, which is based on the work of Bringedal (2003). However, both methodologies are improved to incorporate bid and ask prices. Price models are crucial for the valuation. Forward prices of each month are assumed to follow geometric Brownian motions. Future spot price is also assumed to follow a geometric Brownian motion but for a specific month its expectation is set to the corresponding forward price on the valuation date. Since the simulation of spot and forward prices is separated from the storage optimization, alternative spot and forward models can be used when necessary. The results show that the value of the storage contract estimated by the first methodology is close to the market value and the value estimated by the Financial Engineering Associates (FEA) provided function. A much higher value is obtained when only spot price is considered, since the high volatility of the spot curve makes frequent position change profitable. However in the reality traders adjust their positions less frequently.