Chapter 9: Extensions of Risk and Return Concepts

In this section

• Multi-Factor Models and Portfolio Return Drivers
  Discover how multiple risk factors—like style, macro, and fundamental drivers—converge to explain portfolio returns and shape investment strategies in advanced multi-factor models.
• Evaluating Downside Risk Measures
  Discover key methods to assess and manage downside risk, focusing on metrics like semi-variance, Value at Risk (VaR), and Expected Shortfall (CVaR), as applied in modern portfolio management.
• Non-Linearity and Tail Risk
  Explore how non-linear payoff structures, skewness, and kurtosis can magnify the probability of extreme events, and learn strategies to manage and hedge tail risk in portfolios.
• Portfolio Efficiency Metrics Beyond Traditional Mean–Variance
  Explore advanced efficiency metrics like the Sortino Ratio, Omega Ratio, and more. Discover how they expand upon classic mean–variance analysis by focusing on asymmetry and downside risk, offering deeper insights for portfolio construction and risk management.
• Return-Based Style Analysis
  Explore how return-based style analysis (RBSA) aids in understanding and decomposing a portfolio’s returns into style exposures, revealing potential style drift and improving performance insights.
• Factor Tilts and Style Rotation
  Explore how deliberate factor tilts and style rotation strategies can enhance portfolio returns while navigating timing challenges and transaction costs.
• Multi-Factor Model Construction and Validation
  A detailed exploration of multi-factor models, from factor selection and data collection to out-of-sample validation, showing how to build and assess robust multi-factor portfolios.
• Conditional Factor Exposures in Changing Market Regimes
  Explore how factor exposures evolve across varying economic climates, using Markov switching models, dynamic allocation, and real-time indicators to capture changing market regimes and optimize portfolio strategies.
• Incorporating Transaction Costs in Multi-Factor Strategies
  Learn how to factor in transaction costs into multi-factor investment strategies. Explore practical methods to reduce impact on net returns and enhance portfolio efficiency.
• Estimating Marginal Contributions to Risk
  Understand how each asset or factor contributes incrementally to total portfolio risk, using marginal contribution to risk concepts and formulas.
• Reversals and Momentum in Factor Portfolios
  Explore how short-term reversals and longer-term momentum can be combined within multi-factor portfolios to manage risks, capture trends, and harness behavioral dynamics.
• Regime Switching and Machine Learning in Factor Allocation
  An in-depth exploration of how dynamic regime-switching models and machine learning methods combine to adapt factor allocations in varying market environments.
• Alternative Factor Definitions and Data Sources
  Explore how technology and big data have reshaped factor investing, introducing non-traditional data sources, novel factor definitions, and the potential benefits and pitfalls of these emergent strategies.
• Shifts Between High Beta and Defensive Factors
  Explore the cyclicality of high-beta and defensive factors, their performance in varying market conditions, and practical portfolio applications for CFA® candidates.
• Factor Interaction Effects in Portfolio Management
  Explore how multiple factors combine and interact in a portfolio, covering correlations, overlaps, synergies, conflicts, weighting schemes, and advanced optimization techniques.
• Practical Limitations of Factor Approaches
  Explore the main challenges and constraints of factor investing, including data mining bias, time-varying factor performance, and real-world implementation hurdles.