Class Notes Ch 16

Module Overview

• FIN 4303 Investment Strategies

• Focus on Factor Investing

• Key concepts and implementation strategies outlined in Chapter 16

History of Alpha

• Focus on how stock market picks have evolved:

  • Importance of stock picker returns

Historical Context

Evolution of Alpha

• Comparing absolute return versus stock picker skills:

  • Idiosyncratic risk as a key driver

  • Idiosyncratic risk is specific to individual assets and contributes to unsystematic risk.

  • Example: A company's stock performance remains unassociated with the broader market trends.

Capital Asset Pricing Model (CAPM)

• Developed by William Sharpe in 1964

• A single-factor model focused on relative performance

  • Formula:

    • Actual Return = Risk-free Rate + Beta x Market Risk Premium + Alpha

    • Alpha = Actual Return - (Risk-free Rate + Beta x Market Risk Premium)

    • Market Risk Premium defined as Market Return - Risk-free Rate

Development of Additional Factors

• Limitations of CAPM:

  • Access to information parallels among investors

  • Behavioral biases absent among investors

  • Risk assumptions are static (e.g., betas constant and returns normally distributed)

• Discovery of “alternative betas” to address CAPM limitations

Understanding Factors

Key Factors in Investment

• Stock Picker's Performance Evaluation:

  • CAPM evaluates stock performance contributions from the broad market and individual selection

  • Comparison of performance contributions:

    • Factors contribute to stock selection returns, impacting fee structures and evaluations of stock picker success

Investment Factors Overview

• Main Factors Identified:

  • Value

  • Size

  • Momentum

  • Low Volatility

  • Profitability/Quality

Value Factor

• Introduced by Fama and French (1992):

  • Cost-effectiveness of cheaper stocks outperforming expensive counterparts

  • Key metrics: Market Value to Book Value comparison

  • Historical performance: Strong pre-2007-08, inconsistent thereafter

Size Factor

• Findings by Banz (1981) and Fama and French (1992):

  • Smaller firms typically yield higher returns than larger counterparts

  • Measured via SMB (Small Minus Big)

  • Investment risk characteristics differ due to leverage and volatility

Momentum Factor

• Research by Jegadesh and Titman (1993), Carhart (1997):

  • Performance trends persist (both good and bad)

  • Performance measure UMD (Up Minus Down), focused on prior 12 months

  • Psychological factors impacting behavior: anchoring bias, herding, FOMO

a### Low Volatility Factor

• Studies conducted by Ang et al. (2006):

  • Low-volatility stocks show higher performance relative to high-volatility stocks

  • Investment dynamics: High volatility stocks may signal higher risks

  • Historical track record remains positive, with a decreasing premium

Profitability/Quality Factor

• Contributions by Fama and French (2006), Novy-Marx (2013):

  • Higher profitability in firms correlates with superior performance

  • Examination of sustainable earnings versus unsustainable growth

  • Variability in track record due to definitions of “quality”

Implementation Strategies

Portfolio Design Considerations

• Challenges in defining "cheap" versus "expensive" stocks

• Weighing sector or industry considerations in factor investing

• Multifactor Portfolio Construction:

  • Combining single-factor portfolios to counteract cyclicity

  • Top-down vs. Bottom-up strategies combining factors

Summary & Rationale for Factor Existence

• Investigating the pervasiveness of factors across markets and time

• Assessing the rationale behind factor performance

• Evaluating investability of factors considering liquidity, transaction costs, and management fees

Examples of Factor ETFs

• iShares MSCI USA Momentum (MTUM)

• FLEXSHARES MORNINGSTAR U.S. MARKET FACTOR TILT INDEX FUND