MA Aiqin, GUO Jingjun, WANG Yubing, ZHANG Cuiyun
Considering the uncertainty of financial market data volatility, a new logmean reversion jump diffusion 4/2 random volatility (LMRJ-4/2-SV) model was proposed in this paper. Firstly, the LMRJ-4/2-SV model was constructed, and the European option pricing formula based on LMRJ-4/2-SV model was obtained by using FFT and other methods. Secondly, descriptive statistical analysis of the actual market data was carried out to discuss the price change characteristics of the underlying asset and the applicability of the LMRJ-4/2-SV model, and the model parameters were estimated by particle swarm optimization algorithm. Finally, European options were priced based on the option pricing formula and parameter estimates under the LMRJ-4/2-SV model, and the pricing results were compared with the 4/2, 3/2, Heston model estimates and market prices. The results show that the pricing error of European option based on LMRJ-4/2-SV model is minimal, and the pricing results have obvious advantages over other stochastic volatility models.