Chapter 5: Extensions of Multiple Regression

In this section

• Influence Analysis: Detecting Outliers and Leverage Points
  Learn how to spot and handle data points that exert disproportionate impact on multiple regression models, including methods such as Cook’s Distance and leverage statistics.
• Regression with Qualitative (Dummy) Variables
  Learn how to incorporate categorical variables in multiple regression using dummy variables, interpret their coefficients, avoid the dummy variable trap, and apply these methods to real financial contexts from industry classification to credit ratings.
• Logistic Regression: Probability Modeling in Finance
  Explore the foundations of logistic regression for binary outcomes in finance, including log-odds, odds ratios, goodness-of-fit measures, and real-world applications such as default prediction and classification of profitable trades.
• Special Topics: Structural Breaks, Interaction Terms
  Learn how to detect and handle structural breaks in regression using the Chow Test, plus master the use of interaction terms to capture synergy or offsetting effects. Includes real-world finance examples, diagrams, glossary, and practice questions.
• Test‑Style Examples Integrating Advanced Regression Concepts
  Step-by-step integrated advanced regression examples for CFA Level II exam success, focusing on outliers, dummy variables, logistic models, and structural breaks