This study proposes a volatility-surface projection (PSP) framework for forecasting option prices.

The method first extracts the daily implied volatility surface, then applies historical volatility shocks to generate projected future surfaces.

Combined with Monte Carlo simulations of the underlying asset price, these projected surfaces are fed into the Black–Scholes model to forecast next-day option prices.

Empirical tests show that the PSP approach outperforms benchmark methods, especially at high confidence levels.

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