Developed countries increasingly rely on gas storage for security of supply. Widespread deregulation has created markets that help assign an objective value to existing and new to build storages. Storage valuation is nevertheless a challenging task if we consider both the financial and physical aspects of storage. In this paper we develop a Monte Carlo valuation method, which can incorporate realistic gas price dynamics and complex physical constraints. In specific we extend the Least Squares Monte Carlo method for American options to storage valuation. We include numerical results and show ways to improve computational speed.

In this paper we discuss an extension to a popular gas storage valuation method called the spot approach. Least-Squares Monte Carlo, which is the basis for the spot approach, allows for multi-factor price processes. Such price processes can capture more realistically the actual price behavior present in energy markets. In this paper we demonstrate the application of multi-factor Least-Squares Monte Carlo to gas storage valuation. We study the impact of using multi-factor price processes on different aspects of the valuation such as convergence, average storage value and distribution of storage values in a numerical example. We find a counter example to the idea that an increase in market volatility leads to an increase in storage value. As well, we find a counter example to the idea that the natural hedging strategy of the spot approach is no hedge: a simple static financial hedge can reduce the inherent risk of the spot approach. Finally, we study the impact of model error related to the price process.

We use a supply-demand framework to model the hourly day-ahead spot price of electricity based on publicly available information. With the model we can forecast the level and the probability of a spike in the spot price defined as the spot price being above a certain threshold. Several European countries have recently started publishing day-ahead forecasts of the available supply. In this paper we show potential uses of such indicators and test their forecasting power in an hourly spot price model. We conclude that a forecast of the available supply can be part of a useful indicator and discuss ways to further improve the forecasts.

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