The Weighted Moving Average function computes the average of a set of input values over a specified number of time periods.
The Forecasting and Exponential Smoothing functions use exponential smoothing models to predict future values based on an analysis of historical time series data.
The Correlation Matrix function calculates the strength of the relationships between possible pairings of the specified data series.
The Correlation function calculates the strength of the relationship between two input data series.
The Normal Distribution function calculates the standard normal cumulative distribution for an input data series.
The Percentile function returns a scalar value below which the specified percentage of input data values fall.
The Histogram function assigns numeric values to bins and returns the counts.
The Percent Rank function calculates the percent rank for each value in a set of input values.
The Sample Standard Deviation function measures volatility as the difference between values and their moving average. A larger difference implies a larger standard deviation value.
The Population Standard Deviation function measures volatility as the difference between values and their average. A larger difference implies a larger standard deviation value.
The Variance function calculates the volatility of a set of input data values, such as stock prices over a period of time.
The Minimum Subset function returns the smallest or bottom value(s) in an input data series.
The First Subset function returns the value(s) appearing first in an input data series.
The Last Subset function returns the value(s) appearing last in an input data series.
The Middle Subset function returns the middle value(s) in an input data series.
The Maximum Subset function returns the largest or top value(s) in an input data series.
The Zig Zag Subset function returns the input data values that show movement greater than the specified sensitivity percentage value.
The Accumulation Distribution function is a technical indicator that considers both stock price and volume. Accumulation Distribution can be used to detect divergences between stock price movement and volume movement.
The Aroon Oscillator function is calculated as the difference between the Aroon Up and Aroon Down indicators, with resulting values ranging from -100 to 100.
The Average Directional Index was developed by J. Welles Wilder. It combines two other indicators, the Positive Directional Indicator and the Negative Directional Indicator, which were also developed by Wilder.