scholarly journals Pricing of basket options using univariate normal inverse Gaussian approximations

2010 ◽  
Vol 30 (3) ◽  
pp. 355-376 ◽  
Author(s):  
Fred Espen Benth ◽  
Pål Nicolai Henriksen
Keyword(s):  
Inverse Gaussian ◽  
Basket Options ◽  
Normal Inverse Gaussian

Closed-form valuations of basket options using a multivariate normal inverse Gaussian model

2009 ◽  
Vol 44 (1) ◽  
pp. 95-102 ◽  
Author(s):  
Yang-Che Wu ◽  
Szu-Lang Liao ◽  
So-De Shyu
Keyword(s):  
Closed Form ◽  
Gaussian Model ◽  
Inverse Gaussian ◽  
Multivariate Normal ◽  
Basket Options ◽  
Normal Inverse Gaussian

A normal inverse Gaussian model for a risky asset with dependence

2012 ◽  
Vol 82 (1) ◽  
pp. 109-115 ◽  
Author(s):  
N.N. Leonenko ◽  
S. Petherick ◽  
A. Sikorskii
Keyword(s):  
Gaussian Model ◽  
Risky Asset ◽  
Inverse Gaussian ◽  
Normal Inverse Gaussian

A novel shrinkage technique based on the normal inverse Gaussian density model

2006 ◽  
Vol 28 (1) ◽  
pp. 109-119 ◽  
Author(s):  
Li Shang ◽  
Kang Li ◽  
Tat-Ming Lok ◽  
Michael R. Lyu
Keyword(s):  
Density Model ◽  
Inverse Gaussian ◽  
Gaussian Density ◽  
Normal Inverse Gaussian

Processes of normal inverse Gaussian type

1997 ◽  
Vol 2 (1) ◽  
pp. 41-68 ◽  
Author(s):  
Ole E. Barndorff-Nielsen
Keyword(s):  
Inverse Gaussian ◽  
Gaussian Type ◽  
Normal Inverse Gaussian

CALIBRATING THE SMILE WITH MULTIVARIATE TIME-CHANGED BROWNIAN MOTION AND THE ESSCHER TRANSFORM

2014 ◽  
Vol 17 (04) ◽  
pp. 1450023 ◽  
Author(s):  
GIAN LUCA TASSINARI ◽  
MICHELE LEONARDO BIANCHI
Keyword(s):  
Time Series ◽  
Brownian Motion ◽  
Correlation Matrix ◽  
Asset Returns ◽  
Inverse Gaussian ◽  
Esscher Transform ◽  
Pricing Models ◽  
Simple Correlation ◽  
Complex Dependence ◽  
Normal Inverse Gaussian

In this study, we investigate two multivariate time-changed Brownian motion option pricing models in which the connection between the historical measure P and the risk-neutral measure Q is given by the Esscher transform. The models incorporate skewness, kurtosis and more complex dependence structures among stocks log-returns than the simple correlation matrix. The two models can be seen as a multivariate extension of the normal inverse Gaussian (NIG) model and the variance gamma (VG) model, respectively. We discuss two possible approaches to estimate historical asset returns and calibrate univariate option implied volatilities. While the first approach considers only time series of log-returns, the second approach makes use of both time series of log-returns and univariate observed volatility surfaces. To calibrate the models, there is no need of liquid multivariate derivative quotes.

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