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Alpha and Beta

  • Compare the definitions of alpha and beta:
    • Alpha: measures excess returns of a relative-return investor above or below a market benchmark.
    • Positive alpha: portfolio outperforms its benchmark index.
    • Negative alpha: portfolio underperforms its benchmark index.
    • Beta: Measure of risk or volatility contribution of a stock or portfolio to a diversified portfolio.
    • Average market beta is 1.0.
  • Alpha takes beta into account.
    • Formula: 𝛼 = Rp − (Rf + 𝛽 × (Rm − Rf))
    • Where:
    • 𝛼 = alpha
    • 𝛽 = beta
    • Rp = return of the portfolio
    • Rm = return of the benchmark
    • Rf = risk-free rate (10-year note yield)
      Example Calculation (Growth-Stock Portfolio):
    • Rp = 34\%, Rm = 17\%, Rf = 4.6\%, 𝛽 = 1.24
    • 𝛼 = (.34 − (.046 + 1.24 × (.17 − .046))) × 100 = 14.02\%
      Example Calculation (Utility-Stock Portfolio):
    • Rp = 24.5\%, Rm = 17\%, Rf = 4.6\%, 𝛽 = 0.53
    • 𝛼 = (.245 − (.046 + .53 × (.17 − .045))) × 100 = 13.13\%
  • Utility stocks, despite lower gains, can show almost as much alpha as growth stocks due to lower beta.
  • Quest for alpha involves identifying trends.
    • Technical analysts use moving averages, oscillators, and price envelope tools (Bollinger Bands, Donchian channels, Keltner channels).
    • Fundamental investors are rarely persuaded by such tools.
  • Efficient Markets Hypothesis (EMH) suggests price action studies won't likely lead to predictable trends.
  • Combining technical studies with qualified anomalies (challenges to EMH) is more persuasive.
    • Worthwhile research reconciles findings with hypothetical market models.
  • Adaptive Market Hypothesis (AMH):
    • Financial markets aren't efficient due to investors' evolving attitudes and behaviors.
    • Investors adapt based on expectations and biases.
    • Markets alternate between informational efficiency and inefficiency.
    • Lo suggests tracking and targeting excess returns during informational inefficiency.
  • Volume Patterns at 52-Week Highs and Lows:
    • Investors' trading decisions are affected by extreme prices in a stock’s past.
    • Volume is higher above 52-week highs or below 52-week lows.
    • It is an excellent example of informational inefficiency.
    • Investors modify behaviors, so professional investors should adapt.
  • Trading in Pakistan:
    • Pakistan's KSE-100 Index isn't weak form efficient.
    • Above-market returns can occur via technical analysis.
    • Conforms to Adaptive Market Hypothesis (AMH).
    • Requirements for investors to act rationally isn't always met.
    • Strong trends in markets more slowly incorporating new information more likely to continue, not reverse.
  • The Fractal Market Hypothesis (FMH):
    • Investor behavior in crisis periods is explained by the FMH.
    • Differing decision horizons and risk tolerance cause diverse reactions.
    • Investors don't make decisions based on all historical prices but on differing information sets.
    • Diverse investor behaviors and information cause market uncertainty.
    • Predictions of future price action are possible.
    • Wavelet power spectra can analyze stock markets.
    • Markov regime switching models can identify high and low risk periods.
    • Additional study is warranted, specifically regarding memory associative prices.
  • Supply and Demand:
    • This is coupled with anomalies the EMH can't explain.
    • Investor demand implies a willingness to buy securities, increasing prices.
    • Supply implies selling securities, which drives prices lower.
    • Investors use supply and demand to interpret markets.
  • Anomalies Related to Supply and Demand:
    • Correlations of returns in related securities: Prices don't adjust efficiently, and certain trends are likely to continue.
    • Mean reversion: High-return portfolios underperform, while low-return portfolios may outperform.
    • Underreaction to news: Prices continue predictably following good and bad news because news is deemed unimportant.
    • Size effect: Small stocks outperform large stocks, with relative volume increases.
    • P/E ratio (value investing): Low P/E scores predict greater outperformance due to long-period higher supply and suppressed demand.
    • January effect: Small cap stocks outperform early in the year due to high demand.
    • Patterns in volatility: Bear markets are more volatile, while excess supply increases volatility.