Weighted Moving Average

WMA assigns different weights to different prices, giving more importance to recent data.

Method

tm.ta.wma(source, timeperiod)

Inputs

Parameter	Argument type	Description	Default Value
source	pd.Series	Input data series	-
timeperiod	int	Number of periods for the indicator	30

Outputs

Output	Type
wma	np.ndarray

Example usage

strategy.py

import tradomate as tm

@tm.strategy()
def my_strategy(config: tm.TradomateConfig, data: tm.TradomateData):

    # Trying out Weighted Moving Average
    wma = tm.ta.wma(data.close, timeperiod=30)

    # Get the last value and print
    last_value = wma.iloc[-1]
    tm.log(f"Last value of Weighted Moving Average is {last_value}")

    # Plot the values of wma
    tm.plot(wma, title="Weighted Moving Average", overlay=False)