Kao, Edward P. C.2019-09-10December 22018-12December 2https://hdl.handle.net/10657/4437We use a multivariate variance gamma process developed by Jun Wang (2009) and a similarly constructed multivariate normal inverse Gaussian process to price multi-asset options and calculate greeks with the Fourier space time-stepping (FST) method introduced by Jackson, Jaimungal, and Surkov (2007). The prices are checked against Monte Carlo simulations to demonstrate their accuracy, and we see a marked improvement in computational efficiency. Included are options on the spark spread, the crack spread, and the crush spread, as well as other exotic options that are difficult to price with existing methods. We also adopt a parameter estimation method by Cervellera and Tucci (2016) for variance gamma processes, and adapt it for use with normal inverse Gaussian processes, to make parameter estimates for the marginal processes that are robust with respect to small perturbations of the data.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).Lévy processesVariance gammaNormal inverse gaussianMulti-assetOptionsPricingHedgingMonte CarloGreeksMultivariateFourier space time-steppingPricing Multi-Asset Options with Multivariate Variance Gamma and Normal Inverse Gaussian Processes Using the Fourier Space Time-Stepping Method2019-09-10Thesisborn digital