The article introduces a new model called Extended Normal Inverse Gaussian Distribution (ENIGDM) which is used to approximate unknown risk-neutral density. This model is an extension of the Normal Inverse Gaussian Distribution and has five parameters to represent mixtures of inverse Gaussian distributions. The research discusses the properties and applications of ENIGDM, showing its potential for modeling and analyzing statistical data, especially in a wide range of observations and applications.