Math & Analytics

Standard Deviation

A statistical measure of the dispersion of returns around the mean; used to quantify total investment risk.

S65S66CFP

Standard deviation (σ) measures the dispersion of investment returns around their average (mean). In finance, it is the primary measure of total risk (both systematic and unsystematic).

Interpretation: - A higher standard deviation = wider spread of returns = more volatile/riskier investment. - A lower standard deviation = returns cluster closer to the mean = less volatile.

Normal distribution properties: - ~68% of returns fall within ±1 standard deviation of the mean. - ~95% of returns fall within ±2 standard deviations. - ~99.7% of returns fall within ±3 standard deviations.

Example: A fund has an average annual return of 10% with a standard deviation of 15%. - There's a 68% chance annual returns fall between −5% and +25% (10% ± 15%). - There's a 95% chance annual returns fall between −20% and +40% (10% ± 30%).

Standard deviation vs. beta:

| Measure | Measures | Risk Type | |---|---|---| | Standard deviation | Total volatility | Total risk (systematic + unsystematic) | | Beta | Relative market volatility | Systematic risk only |

Coefficient of variation (CV): Standard deviation ÷ Mean return = risk per unit of return. Useful for comparing investments with different expected returns.

> Exam tip: Standard deviation = total risk; beta = systematic risk. For a well-diversified portfolio, unsystematic risk is largely eliminated, so standard deviation approaches beta-driven risk. Sharpe ratio uses standard deviation; Treynor ratio uses beta.

Instructor Login