Chapter 10: Nonlinear and Advanced Regression Methods

In this section

• Polynomial, Interaction, and Step Functions
  Deepen your understanding of polynomial regression, interaction terms, and step functions. Learn how to capture nonlinear relationships, interpret model coefficients, and avoid overfitting in a CFA® Level II context.
• Probit and Other Nonlinear Models
  Explore Probit regression and other nonlinear models for binary or limited-dependent variables, including Tobit, Heckman, and logistic approaches, with practical finance applications.
• Time‑Varying Coefficients and Regime‑Switching Regressions
  Discover how to handle evolving relationships and structural shifts in financial markets using time‑varying parameter models and regime‑switching techniques.
• Mixed Models and Hierarchical Structures
  Explore how mixed (multilevel) models handle nested investment data, combining fixed and random effects for robust financial insights.
• Vignette Scenarios with Nonlinear Applications
  Explore advanced nonlinear regression frameworks—such as logistic, probit, polynomial, and piecewise models—through realistic CFA® 2025 Level II vignettes. Understand how to interpret model outputs, handle threshold effects, and implement regime-switching strategies to enhance portfolio decision-making.