An investor uses Bayesian methods to model AAPL stock volatility, updating beliefs with daily returns and forecasting future risk.
The full Jupyter Notebook for this scenario (including all code cells and outputs)
is rendered below. It’s auto-built with nbconvert --to html --template lab
and deployed into the /notebooks_html/ folder on GitHub Pages.