The Standard Deviation indicator is a statistical calculation used to measure the variability. In trading this value is known as volatility. A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values.

**Period**: Number of bars to use in the calculations.-
**Field**: Price or combination of prices to use as the base for average calculations. Possible values include:- Open
- High
- Low
- Close
- Adjusted Close
- HL/2 \( \left ( \frac{High + Low}{2} \right ) \)
- HLC/3 \( \left ( \frac{High + Low + Close}{3} \right ) \)
- HLCC/4 \( \left ( \frac{High + Low + Close + Close}{4} \right ) \)
- OHLC/4 \( \left ( \frac{Open + High + Low + Close}{4} \right ) \)

**Standard Deviations**: TBD-
**Moving Average Type**: Type of moving average to use in the calculations:**Simple**: Mean (average) of the data.**Exponential**: Newer data are weighted more heavily geometrically.**Time Series**: Calculates a linear regression trendline using the “least squares fit” method.**Triangular**: Weighted average where the middle data are given the most weight, decreasing linearly to the end points.**Variable**: An exponential moving average with a volatility index factored into the smoothing formula. The Variable Moving average uses the Chande Momentum Oscillator as the volatility index.**VIDYA**: An exponential moving average with a volatility index factored into the smoothing formula. The VIDYA moving average uses the Standard Deviation as the volatility index. (Volatility Index DYnamic Average).**Weighted**: Newer data are weighted more heavily arithmetically.**Welles Winder**:The standard exponential moving average formula converts the time period to a fraction using the formula EMA% = 2/(n + 1) where n is the number of days. For example, the EMA% for 14 days is 2/(14 days +1) = 13.3%. Wilder, however, uses an EMA% of 1/14 (1/n) which equals 7.1%. This equates to a 27-day exponential moving average using the standard formula.**Hull**: The Hull Moving Average makes a moving average more responsive while maintaining a curve smoothness. The formula for calculating this average is as follows: HMA[i] = MA( (2*MA(input, period/2) – MA(input, period)), SQRT(period)) where MA is a moving average and SQRT is square root.**Double Exponential**: The Double Exponential moving average attempts to remove the inherent lag associated to Moving Averages by placing more weight on recent values.**Triple Exponential**: TBD

- Simple
- Exponential
- Time Series
- Triangular
- Variable
- VIDYA
- Weighted
- Welles Winder
- Hull
- Double Exponential
- Triple Exponential

**Color Selectors**: Colors to use for graph elements.**Display Axis Label**: Whether to display the most recent value on the Y axis.

\[ s = \sqrt \frac{\sum (X -\bar X)^2}{(N-1)} \]

where:

- s = Standard deviation
- X = Each value in the sample
- X = Mean of the values
- N = Number of values (sample size)