experimental.kaufmansAMA() function
The experimental.kaufmansAMA() function is subject to change at any time.
By using this function, you accept the risks of experimental functions.
The experimental.kaufmansAMA() function calculates the Kaufman’s Adaptive Moving Average (KAMA)
of input tables using the _value column in each table.
import "experimental"
experimental.kaufmansAMA(n: 10)
Kaufman’s Adaptive Moving Average is a trend-following indicator designed to account for market noise or volatility.
Parameters
n
The period or number of points to use in the calculation.
tables
Input data.
Default is piped-forward data (<-).
Examples
import "experimental"
from(bucket: "example-bucket"):
|> range(start: -7d)
|> experimental.kaufmansAMA(n: 10)
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