Chapter 2: Portfolio Risk and Return – Part I

In this section

• Characteristics of Major Asset Classes
  A comprehensive exploration of the main asset classes—equities, fixed income, cash, real estate, commodities, and alternatives—covering their risk, return, correlation, and roles in portfolio construction.
• Risk Aversion, Utility Theory, and Portfolio Selection
  Discover how risk aversion guides investors’ portfolio decisions, delve into the fundamentals of utility theory, and learn to apply these core concepts in constructing optimal portfolios under uncertainty.
• Calculating Mean Returns, Variance, Covariance, and Correlation
  Master essential techniques for calculating arithmetic and geometric mean returns, variance, covariance, and correlation. Learn to interpret these statistics in real-world portfolio decisions to optimize risk and return.
• Building and Interpreting the Minimum-Variance Frontier
  Learn how to construct and interpret the minimum-variance frontier, exploring its mathematical derivation, real-world constraints, and practical applications in portfolio optimization.
• Effects of Correlation on Portfolio Risk
  Learn how correlation affects portfolio risk, explore detailed examples, and discover how to manage correlation effectively for optimal diversification.
• Risk Premium Concepts and Market Segmentation
  Explore how risk premium arises, its common types, and the role of market segmentation in shaping expected returns. Includes historical insights, behavioral angles, and practical examples.
• Incorporating Leverage in Basic Return Analysis
  Explore how leverage magnifies both portfolio returns and risks. Learn about margin accounts, leverage ratios, the cost of borrowing, and how to analyze performance under various leveraged scenarios. Understand the practical constraints and best practices for incorporating leverage in portfolios.
• Downside Deviation and Expected Shortfall
  Explore downside deviation and expected shortfall as advanced risk measures that focus on adverse outcomes, illustrating how they complement traditional standard deviation in portfolio management.
• Semi-Variance and Partial Moments
  Explore semi-variance and partial moments in portfolio management, focusing on downside risk measures that refine traditional variance approaches.
• Limitations of Mean-Variance Analysis
  Explores the core assumptions of mean-variance optimization, its practical challenges, and how alternative models address the estimation limitations and non-linear risk factors in portfolio management.
• Reliability of Historical Data for Risk Estimation
  This section explores how historical data influences risk estimation, the pitfalls of sampling error and survivorship bias, and strategies for adapting data to reflect changing market conditions.
• Scenario and Sensitivity Analyses in Portfolio Return
  Explore how scenario and sensitivity analyses help investors evaluate portfolio returns under various macroeconomic environments and single-variable shocks, supporting robust risk management and decision-making.
• Role of Time Horizon in Estimating Return and Risk
  Discover how investment horizons shape risk and returns, from short-term market volatility to long-term smoothing effects, exploring path dependency and real-world allocation strategies for diverse client profiles.
• Impact of Liquidity on Asset Class Risk
  Explore how market depth, lock-up periods, and liquidity constraints shape risk profiles across different asset classes, drawing insights from past crises and best practices for managing illiquid positions.
• Effects of Macroeconomic Variables on Asset Class Returns
  Learn how GDP growth, inflation, interest rates, and more shape returns across equities, bonds, and other asset classes, and discover practical frameworks for analyzing macroeconomic data in portfolio management.
• Diversification Across Geographical Regions
  Discover how diversifying across global markets can optimize portfolio risk and return, including currency, political, and regulatory considerations.