Valuation Of Swing Options With Supplier
Flexibility – Switching And Recall Features:
A Methodology Note
Author(s)
S. Persad
Abstract
This paper presents a method for valuation and risk/sensitivity analysis of swing
contracts with switching and/or recall features. Standard swing options allow
natural gas customers to exercise a limited number of call features over a period
(month) to select the optimal amount of energy to receive each period (day) at a
given strike price. More complex versions of these instruments also allow the
supplier some flexibility. Two supplier-friendly features are discussed in this
paper: (1) Switching features: the supplier must fulfil the buyer’s nomination in
full, but has a choice of which commodity/delivery location to supply (2) Recall
Features: the supplier may recall some of the buyer’s nomination amount. This
paper offers an algorithm for backward solution. The method draws from Jaillet,
Ronn and Tompaidis (2004, Valuation of commodity based swing options.
Management Science Vol. 50, Iss. 7, pp. 909–921) by using a forest of trees to
represent remaining swing rights, but extends it to a two player (customer and
supplier) setting. At each stage the players gather the relevant nodes to which
they can transition and engage in a Stackelberg game to determine the optimal
action. At each point, the game’s outcome is determined employing the game
theoretic concept of subgame perfect Nash equilibrium. Because different
locations for gas delivery are essentially separate but related markets, the
underlying prices to be constructed are two gas locations with a specified
correlation. This paper employs Rubenstein’s (\“Somewhere Over the Rainbow”,
RISK 4 (November 1991), pp. 63–66; \“Return to Oz”, RISK 7 (November 1994),
pp. 67–71) pyramid methodology for modelling correlated asset price processes.
In addition, we adapt the Hull and White (1994, Numerical Procedures for
Implementing Models I: Single Factor Models, Journal of Derivatives Vol 2, pp
37–48) procedure for incorporating drift so that our price pyramid captures the
mean reversion feature of natural gas. Finally we make adjustments so that the
simulation captures seasonality of natural gas prices.
Keywords: path-dependent option pricing, correlated trinomial tree, lattice,
swing options, energy options.
Keywords
path-dependent option pricing, correlated trinomial tree, lattice,
swing options, energy options.
Related Book
Other papers in this volume
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