Research on Pricing of SSE STAR 50ETF Options Based Monte Carlo Simulation

The SSE STAR 50ETF options, as pivotal financial derivatives in China’s capital market, are critical for investors and regulators. Traditional pricing models (e.g., Black-Scholes) assume market efficiency and log-normal asset returns, often failing to capture the high volatility and risks of the STAR market. This study proposes an enhanced pricing framework using Monte Carlo simulation to address these gaps. This paper analyze the market traits of SSE STAR 50ETF options and highlight the limitations of conventional models. To better reflect the underlying asset’s volatility, we integrate stochastic volatility (HESTON) and jump-diffusion models. Our experimental design compares Monte Carlo-simulated Black-Scholes (BS), HESTON, and GARCH models (treatment group) against standard BS, HESTON, and GARCH models (control group). By simulating STAR 50ETF price paths under no-arbitrage principles, we derive option prices and validate them empirically. Results show that Monte Carlo-based models outperform the control group in fitting market prices, offering investors more accurate pricing and risk management tools. This research contributes to the understanding of derivatives pricing in emerging high-volatility markets.