experimental.kaufmansAMA() function
experimental.kaufmansAMA() is subject to change at any time.
experimental.kaufmansAMA() calculates the Kaufman’s Adaptive Moving Average (KAMA) of input
tables using the _value column in each table.
Kaufman’s Adaptive Moving Average is a trend-following indicator designed to account for market noise or volatility.
Function type signature
(<-tables: stream[{A with _value: B}], n: int) => stream[{A with _value: float}] where B: Numeric
For more information, see Function type signatures.
Parameters
n
(Required) Period or number of points to use in the calculation.
tables
Input data. Default is piped-forward data (<-).
Examples
Calculate the KAMA of input tables
import "experimental"
import "sampledata"
sampledata.int()
|> experimental.kaufmansAMA(n: 3)
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