Skewness
Calculates the skewness (third moment) of portfolio returns, measuring the asymmetry of the return distribution.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| Portfolio | string | Yes | Comma-separated list of ticker symbols |
| Period | string | Yes | Time period (1Y, 3Y, 5Y, etc.) |
Interpretation
- Skewness = 0: Symmetric distribution
- Skewness < 0: Left-skewed (negative), longer left tail
- Skewness > 0: Right-skewed (positive), longer right tail
Notes
- Negative skewness indicates higher probability of extreme negative returns
- Important for risk management beyond standard deviation
Syntax
=mxls.Skewness(Portfolio, Period)Examples
When to Use
- Risk analysis beyond standard deviation
- Understanding return distribution shape
- Evaluating tail risk
- Portfolio optimization considerations
- Risk-adjusted performance analysis
When NOT to Use
| Scenario | Use Instead |
|---|---|
| Need kurtosis (fat tails) | Kurtosis() |
| Need average returns | MeanReturns() |
| Need drawdown analysis | Drawdowns() |
| Need efficient frontier | PortfolioEfficientFrontierChartReport() |
Common Issues & FAQ
Q: What does negative skewness mean? A: Negative skewness indicates a longer left tail, meaning higher probability of extreme negative returns.
Q: What is a normal skewness value? A: Normal distribution has skewness of 0. Equity returns typically show slight negative skewness.
Q: How does this help with risk management? A: Skewness helps identify asymmetric risks that standard deviation alone doesn't capture.
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