Synthesis of Analyses on the Optimization of Pricing Strategies for Financial Derivatives

Abstract

: This paper focuses on the stochastic volatility model, the stochastic interest rate model, and the expansion path of introducing market friction factors, and analyzes the impact of changes in different trading systems on market liquidity and risk pricing structure in combination with the main foundation model (ABM). Secondly, at the quantitative level of technology, this paper summarizes the advantages of the multi-factor pricing model and the Monte Carlo simulation method in the pricing of complex derivatives, emphasizing its effectiveness in dealing with nonlinear return structure and path dependency problems. Through the comparative analysis of multiple typical cases, this paper points out that different methods have their own characteristics in terms of risk control ability, computational efficiency, and applicable scenarios, and it is difficult for a single model to fully adapt to the complex and changeable financial market environment. The study believes that the optimization of derivatives pricing strategies should develop in the direction of multi-model integration, dynamic risk characterization, and full empirical testing to improve the stability and practical applicability of pricing results.