Abstract：The purpose of this paper is to provide an efficient calibration algorithm of the Pareto-Beta jump-diffusion option pricing model. Firstly, the approach exploits the connection between the Pareto-Beta jump-diffusion model and the double exponential jump-diffusion model to reduce the number of parameter to be estimated. Then, the reduced model is calibrated by minimizing the square error between the European option price and the corresponding market price. Regularization by adding a penalty function to the square error term assures uniqueness and stability of the solution. European option price is calculated by fast Fourier transform method that helps greatly in the speed-up of the recursion. At last, the model and calibration algorithm are applied to the S&P 500 index options. Results show that the proposed calibration algorithm has better stability.