This dissertation is devoted to multivariate analytic characteristic functions inversion and applications in option pricing, option sensitivities estimation, and some electronic engineering problems. We will show that under certain analytic conditions for characteristic functions, the underlying pdfs and cdfs have exponential tails. The inversion from multivariate characteristic functions to the corresponding pdfs and cdfs can be approximated by the trapezoidal rule conveniently with great accuracy. Monte Carlo methods can be applied for option sensitivity analysis. Under multi-dimensional models, acceptance-rejection method is desirable. Simulating from a distribution without explicit pdf or CDF is then transformed to sampling from an easy-to-simulate distribution. Detailed algorithms are provided and comparisons against classical methods in terms of accuracy and efficiency are included
