Option pricing using time series models as market price of risk Pt.3

A third installment in a series on option pricing using time series models as the market price of risk. The approach constructs a risk-neutral measure by fitting ARIMA or AR(1) filters to discounted price increments, extracting martingale innovations, and resampling them via stationary bootstrap. The reconstructed discounted process satisfies the martingale condition, enabling Monte Carlo pricing of European calls and puts. Full R code is provided using esgtoolkit, forecast, and tseries packages, with validation checks including martingale verification, put-call parity, normality tests on log-returns, and comparison against Black-Scholes prices across multiple strike levels.