Pricing Energy Spread Options

Benth, Fred Espen; Zdanowicz, Hanna

doi:10.1002/9781119011590.ch17

Cited by 1 publication

(1 citation statement)

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“…Siegel (1995) explains how exchange options can be used to estimate the "implicit beta" between an underlying stock and a given market index. The exchange option framework may be adapted to investigate real options (Kensinger 1988;Carr 1995), outperformance options (Cheang and Chiarella 2011) 3 , energy market options (surveyed in Benth and Zdanowicz 2015), and the option to enter/exit an emerging market (Miller 2012), among others. Ma, Pan, and Wang (2020) provide additional examples of financial contracts which can be priced under the exchange option framework.…”

Section: Introductionmentioning

confidence: 99%

A numerical approach to pricing exchange options under stochastic volatility and jump-diffusion dynamics

Garces

Cheang

2021

Quantitative Finance

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We consider a method of lines (MOL) approach to determine prices of European and American exchange options when underlying asset prices are modelled with stochastic volatility and jump-diffusion dynamics. As the MOL, as with any other numerical scheme for PDEs, becomes increasingly complex when higher dimensions are involved, we first simplify the problem by transforming the exchange option into a call option written on the ratio of the yield processes of the two assets. This is achieved by taking the second asset yield process as the numéraire. We also characterize the near-maturity behavior of the early exercise boundary of the American exchange option and analyze how model parameters affect this behavior. Using the MOL scheme, we conduct a numerical comparative static analysis of exchange option prices with respect to the model parameters and investigate the impact of stochastic volatility and jumps to option prices. We also consider the effect of boundary conditions at far-but-finite limits of the computational domain on the overall efficiency of the MOL scheme. Toward these objectives, a brief exposition of the MOL and how it can be implemented on computing software are provided.

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