Valuing virtual production capacities on flow commodities

As a result of storability restrictions, the price risk management of flow commodities (such as natural gas, oil, and electrical power) is by no means a trivial matter.To protect price spikes, consumers purchase diverse swing-type contracts, whereas contract writers try to hedge themselves by appropriate physical assets, for instance, using storage utilities, through transmission and/or production capacities. However, the correct valuation of such contacts and their physical counterparts is still under lively debate. In this approach, an axiomatic setting to discuss price dynamics for flow commodity contracts is suggested. By means of a minimal set of reasonable assumptions we suggest a framework where the standard change-of-numeraire transformation converts a flow commodity market into a market consisting of zero bonds and some additional risky asset. Utilizing this structure, we apply the toolkit of interest rate theory to price the availability of production capacity on a flow commodit

Valuing virtual production capacities on flow commodities

ISSN:1432-2994ISSN:1432-521

The Evaluation of Gas Sales Agreements

A gas sales agreement, also called a gas swing contract, is an agreement between a supplier and a purchaser for the delivery of variable daily quantities of gas, between specified minimum and maximum daily limits, over a certain number of years at a strike price. The main constraint of such an agreement is that there is a minimum volume of gas for which the buyer will be charged at the end of the year, regardless of the actual quantity of gas taken. For multiple year contracts, there are also features called the make-up and carry-forward banks which add another level of complexity to the analysis. We propose a framework for pricing such multiple year contracts where both the gas price and strike price are stochastic processes. With the help of a two-dimensional trinomial tree, we are able to price such swing contracts with both make-up and carry-forward banks, and find the optimal daily decisions and the optimal yearly usage of the make-up and carry-forward banks. We also provide a detailed analysis of the different features that these contracts possess. Furthermore, another feature, called the indexation principle, is popular in real markets, under which the strike price is called the index. In each month, the value of the index is determined by the weighted average price of some energy products in the previous month. We design a lattice-based algorithm to price such swing contracts and find optimal daily decisions by using graphics processing units. Since the least-squares Monte Carlo method is well-known to handle sophisticated models, such as multi-factor models, models with regime-switching, or models with jumps, we build this method for the pricing of gas sales agreements and analyze the performance of it, especially the impacts of explanatory variables. With the help of concrete numerical examples, various features of such contracts with indexation are demonstrated