Option pricing is one of the core research topics in the field of financial engineering. As a classical option pricing method, the Black-Scholes model provides a significant foundation for both theory and practice in modern financial markets. This paper first elaborates on the theoretical foundation and mathematical derivation of the Black-Scholes model, analyzes its practical applications in option pricing, and explores its limitations, including the strict assumptions about market conditions and its applicability in environments with fluctuating volatility or sudden market jumps. To address these issues, this study improves the Black-Scholes model from two perspectives: stochastic volatility and jump-diffusion models. The improved models are validated through experimental designs, and their effectiveness is compared with the traditional model. The experimental results demonstrate that the improved models can provide more accurate pricing results in complex market environments. This research not only deepens the understanding of the Black-Scholes model but also offers new insights and approaches for pricing complex financial instruments.
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