The notebook applies a 60-month rolling CAPM to technology-industry excess returns using Ken French’s factor and industry data. It displays coefficient tables, confidence-interval plots, and an expanding-window example.
The tutorial concatenates NO2 and particulate-measurement tables, shows row-count checks, and joins station coordinates and parameter descriptions. Displayed tables trace how the measurement dataset gains metadata.
Using Australian quarterly beer-production data, the book compares mean, naïve, and seasonal-naïve forecasts against later observations. Its displayed example shows the seasonal baseline following the observed pattern more closely.
Published byRob J Hyndman and George Athanasopoulos / OTexts
Robert Andrew Martin’s guide transforms historical share prices into return and covariance estimates, prints optimized portfolio weights, and demonstrates regularization and integer-share allocation. Its performance figures are model estimates.
Published byRobert Andrew Martin / PyPortfolioOpt
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