by Ryan Dutton
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Start with the foundations, then use the reading focus to connect the paper to further study.
Understand convergence, sampling error and confidence intervals.
Generate reproducible samples and distinguish randomness from model assumptions.
Build replication and risk-neutral probabilities in a tractable model.
Distinguish pricing probabilities from physical forecasts.
Turn a discounted payoff into an estimator.
Study dependence and alternatives to independent sampling.
Connect the pricing equation, closed-form value and implied volatility.
Start in discrete time, move to Brownian motion, then read the original pricing argument and simulate it.
Study simulation accuracy and convergence in a related SMQ project.
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