References

THE APPLICATION OF MONTE CARLO SIMULATION BASED ON NORMAL INVERSE GAUSSIAN DISTRIBUTION IN OPTION PRICING


[1] D. Karlis, An EM type algorithm for maximum likelihood estimation of the normal-inverse Gaussian distribution, Statistics & Probability (2002), 43-52.

[2] Ribeiro Claudia and Nick Webber, A Monte Carlo Method for the Normal Inverse Gaussian Option Valuation Model using an Inverse Gaussian Bridge, Working Paper, 2003.

[3] Zhiguang Cao, Financial Computation and Programming, Shanghai University of Finance and Economics Press, Shanghai, 2013.

[4] Junhai Ma and Yan Wang, Monte Carlo simulation methods and its improved technique for pricing warrants, Journal of Industrial Engineering Management (3) (2010), 75-81.

[5] Yineng Ouyang and Yun Xu, The pricing of basket default swaps based on normal inverse Gaussian distribution, Mathematics in Practice and Theory 43(19) (2013), 1-9.

[6] Fuyan Luo and Zhen Jia, Numerical pricing Asian option on stocks driven by the NIG-Levy process, Mathematics in Practice and Theory 38(15) (2008), 75-80.

[7] Zhiguang Cao, Anxing Wang and Junmin Yang, The test of non-normal distribution of stock returns with Monte Carlo simulation and the explanation, Journal of Finance and Economics 31(10) (2005), 34-41.

[8] Lihong Zhang, Monte-Carlo methods for pricing European-style options, Economic Research Guide (15) (2015), 104-112.

[9] John Hull, Options, Futures, and other Derivatives (Fifth Edition), Tsinghua University Press, Beijing, 1997.

[10] Lishang Jiang, Mathematical Modeling and Method of Option Pricing, Higher Education Press, Beijing, 2003.

[11] Tao Wu, Songlin Liu and Shanshan Li, Monte Carlo method for pricing of warrants in China, Statistics and Decision (8) (2009), 128-129.