Chapter2007

Variance-Gamma and Monte Carlo

56 citations0/0 files storedBirkhäuser Boston eBooks

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Stochastic processes and financial applications Financial Risk and Volatility Modeling Markov Chains and Monte Carlo Methods

Abstract

The Variance-Gamma (VG) process was introduced by Dilip B. Madan and Eugene Seneta as a model for asset returns in a paper that appeared in 1990, and subsequently used for option pricing in a 1991 paper by Dilip and Frank Milne. This paper serves as a tutorial overview of VG and Monte Carlo, including three methods for sequential simulation of the process, two bridge sampling methods, variance reduction via importance sampling, and estimation of the Greeks.

Citations in this library

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References

2005Stochastic Integration and Differential Equations 2003Monte Carlo Methods in Financial Engineering 1999Option valuation using the fast Fourier transform 1998The Variance Gamma Process and Option Pricing 2002The Fine Structure of Asset Returns: An Empirical Investigation 1990The Variance Gamma (V.G.) Model for Share Market Returns 2003Stochastic Volatility for Lévy Processes 1997Monte Carlo methods for security pricing

Cited by

2008What you should know about simulation and derivatives 2012Simulating Lévy Processes from Their Characteristic Functions and Financial Applications 2012A New Stochastic Derivative Estimator for Discontinuous Payoff Functions with Application to Financial Derivatives

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