Fat tails

A distribution putting more probability on extreme outcomes than the normal does, which is positive excess kurtosis. Risk measures that assume normality then understate how often large losses occur.

Where you will meet it

Fat tails appears in 15 learning outcomes on the CFA syllabus. A few of them:

• Explain what skewness and kurtosis say about a return distribution
  CFA Level I · Quantitative Methods

  “Kurtosis measures tail weight relative to the normal distribution: excess kurtosis above zero means fat tails, so extreme outcomes are more likely than a normal distribution implies.”

• Set out how the main asset classes have performed historically in terms of risk and return
  CFA Level I · Portfolio Management

  “Equity returns show fat tails and negative skewness rather than a normal distribution.”

• Set out risk measures suited to return distributions that are not normal
  CFA Level I · Alternative Investments

  “Many alternative strategies produce returns that are not normally distributed: option-like payoffs, credit strategies and short-volatility positions generate negative skew and fat tails, where many small gains are punctuated by rare large losses.”

• Contrast three ways to estimate VaR: Monte Carlo simulation, historical simulation, and the parametric (variance–covariance) method
  CFA Level II · Portfolio Construction

  “The parametric method assumes normally distributed returns and uses expected returns, volatilities and correlations; it is quick but misstates risk for fat-tailed returns and for options, whose payoffs are non-linear.”

See also

Kurtosis

Practise it

• Today's practice question One question, with every wrong option explained.
• Free Level I diagnostic test Twelve questions that show which topics to start with.
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