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Why Extra Risk Earns No Extra Reward?

Posted in Volatility Effects

Why does the widely cited and intuitive Capital Asset Pricing Model (CAPM) prediction that extra risk (beta) earns extra reward (rate of return) not work for stocks? In their May 2013 paper entitled “Explanations for the Volatility Effect: An Overview Based on the CAPM Assumptions”, David Blitz, Eric Falkenstein and Pim van Vliet organize research on potential explanations according to the following CAPM assumptions:

  1. Investors are unconstrained regarding leverage, short selling and solvency (regulatory capital requirements).
  2. Investors are risk-averse, focus on absolute return and care only about return mean and variance (such that returns are normally distributed).
  3. There is only one return measurement interval and therefore no compounding effect (ignoring the difference between arithmetic and geometric means).
  4. Investors have complete information and process it rationally.
  5. Investors have no liquidity constraints, transaction costs or taxes.

Based on a review of research on potential explanation for the empirical failure of CAPM, they find that:

  • Borrowing constraints may cause investors to demand (and thereby overprice) high-volatility stocks as a substitute for leverage.
  • Short-selling constraints may inhibit arbitrageurs from correcting inflated prices of high-volatility stocks.
  • Both envy and fund manager incentives (beating a benchmark rather than achieving absolute return) may drive investments toward (and thereby overprice) high-volatility stocks.
  • Some investors may irrationally like the lottery-like aspect (potentially big, life-changing pay-off) of volatile stocks and thereby overprice them.
  • A combination of strong crash aversion and the tendency of stock return correlations to rise during crashes tends to flatten the risk-return relationship.
  • By ignoring the compounding effect, CAPM views high-volatility stocks more favorably than do investors considering multiple return intervals.
  • High-volatility (low-volatility) stocks tend to grab (escape) investor attention, thereby becoming irrationally overpriced (underpriced).
  • High-volatility stocks tend to generate favorable anecdotes of dramatic success (during upswings), leading investors to overweight them irrationally.
  • Investors who are overconfident about their stock-picking or market timing ability may create irrational excess demand for high-volatility stocks through attempts to exploit their self-perceived superiority.

In summary, there are variety of potential explanations for the failure of CAPM to describe the actual relationship between stock beta and future return, generally deriving from overpricing of high-volatility stocks.

More general potential lessons from this examination include:

  • Investors and academics may widely believe, cite and teach financial market models that are not usefully predictive.
  • Financial markets are very complex systems (many interacting parts) that are very difficult to model, hence leaving the field to empirical analysis (and false discoveries via snooping of model adjustments, parameter settings and data samples).
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