A Multivariate Variance Gamma Model for Financial Applications
A Multivariate Variance Gamma Model for Financial Applications

Author: Patrizia Semeraro

Publisher:

Published: 2009

Total Pages: 0

ISBN-13:

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In this paper we subordinate a multivariate Brownian motion with independent components by a multivariate gamma subordinator. The resulting process is a generalization of the bivariate variance gamma process proposed by Madan and Seneta [7], mentioned in Cont and Tankov [4] and calibrated in Luciano and Schoutens [5] as a price process. Our main contribution here is to introduce a multivariate subordinator with gamma margins. We investigate the process, determine its Lévy triplet and analyze its dependence structure. At the end we propose an exponential Lévy price model.

Advances in Financial Risk Management
Advances in Financial Risk Management

Author: Jonathan A. Batten

Publisher: Springer

Published: 2015-12-04

Total Pages: 434

ISBN-13: 1137025093

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The latest research on measuring, managing and pricing financial risk. Three broad perspectives are considered: financial risk in non-financial corporations; in financial intermediaries such as banks; and finally within the context of a portfolio of securities of different credit quality and marketability.

Mathematical and Statistical Methods for Actuarial Sciences and Finance
Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author: Cira Perna

Publisher: Springer Science & Business Media

Published: 2012-03-08

Total Pages: 402

ISBN-13: 8847023424

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The book develops the capabilities arising from the cooperation between mathematicians and statisticians working in insurance and finance fields. It gathers some of the papers presented at the conference MAF2010, held in Ravello (Amalfi coast), and successively, after a reviewing process, worked out to this aim.

On Numerical Methods for Spread Options
On Numerical Methods for Spread Options

Author: Mesias Alfeus

Publisher:

Published: 2018

Total Pages: 31

ISBN-13:

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Spread options are multi-asset options whose payoffs depend on the difference of two underlying financial variables. In most cases, analytically closed form solutions for pricing such payoffs are not available, and the application of numerical pricing methods turns out to be non-trivial. We consider several such non-trivial cases and explore the performance of the highly efficient numerical technique of Hurd and Zhou (2010), comparing this with Monte Carlo simulation and the lower bound approximation formula of Caldana and Fusai (2013). We show that the former is in essence an application of the two-dimensional Parseval Identity.As application examples, we price spread options in a model where asset prices are driven by a multivariate normal inverse Gaussian (NIG) process, in a threefactor stochastic volatility model, as well as in examples of models driven by other popular multivariate Lévy processes such as the variance Gamma process, and discuss the price sensitivity with respect to volatility. We also consider examples in the fixed-income market, specifically, on cross-currency interest rate spreads and on LIBOR/OIS spreads. In terms of FFT computation, we have used the FFTW library (see Frigo and Johnson (2010)) and we document appropriate usage of this library to reconcile it with the MATLAB ifft2 counterpart.

Multi-asset Option Pricing Problems
Multi-asset Option Pricing Problems

Author: Chienmin Chuang

Publisher:

Published: 2012

Total Pages:

ISBN-13:

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Options are important and frequently traded products in the modern financial market. How to price them fairly and reasonably is always an interesting issue for academia and industry. This research is performed under the classical multi-asset Black-Scholes-Merton (BSM) model and can be extended to other exotic models. We show how to reformulate the multi-asset Black-Scholes-Merton partial differential equation/inequality (BSM PDE/PDI) and provide theorems to justify the unique solution of reformulations. In terms of discretization, we adopt the finite element method (FEM) in space and finite difference method (FDM) in time. Moreover, we develop the closed-form formulas for the elemental matrices used in the finite element assembly process in a general high-dimensional framework. The discrete systems of option pricing problems are presented in the form of linear system of equations (LSE) and linear complementary problems (LCP) for European and American/perpetual options respectively. Up to six different algorithms for the LCP are introduced and compared on the basis of computational efficiency and errors. The option values of European, American and perpetual types are calibrated when given various payoffs and up to three assets. Particularly, their numerical free boundaries are identified and presented in the form of (d - 1)-dimensional manifold in a d-assetframework. In the last chapter, we conclude our research with our contributions and potential extension.