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Gas Storage Valuation in Incomplete Markets

Nils Löhndorf (nils.loehndorf***at***uni.lu)
David Wozabal (david.wozabal***at***tum.de)

Abstract: Natural gas storage valuation is an important business problem in energy trading, yet most valuation approaches are based on heuristics or ignore that gas markets are incomplete. We propose an exact valuation model for incomplete markets based on multistage stochastic programming. The model requires analysis of a combined control problem of storage operation and futures trading that takes an agent’s risk preferences into account. As the problem is subject to the curse of dimensionality, we propose a second-order learning algorithm that discretizes the price process to a scenario lattice and then approximate the problem using stochastic dual dynamic programming. We prove convergence of the learning algorithm and show that our solution is near-optimal by comparing it with a known upper bound from the literature. We also show that the intrinsic value of storage corresponds to the value under perfect risk aversion and that the rolling intrinsic value - which is popular among practitioners - is not suitable for valuation in incomplete markets.

Keywords: multistage stochastic programming, asset pricing, natural gas industry, Markov processes

Category 1: Applications -- OR and Management Sciences

Category 2: Stochastic Programming

Citation: Löhndorf N, Wozabal D (2019) Gas storage valuation in incomplete markets, working paper.

Download: [PDF]

Entry Submitted: 02/15/2017
Entry Accepted: 02/15/2017
Entry Last Modified: 02/13/2019

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