Stochastic Relative Strength Index

STOCHRSI combines elements of Stochastic and RSI to identify overbought and oversold conditions.

Method

tm.ta.stochrsi(source, timeperiod, fastk_period, fastd_period, fastd_matype)

Inputs

Parameter	Argument type	Description	Default Value
source	pd.Series	Input data series	-
timeperiod	int	Number of periods for the indicator	14
fastk_period	int	Fast %K period for the indicator	5
fastd_period	int	Fast %D period for the indicator	3
fastd_matype	int	Fast %D Moving Average type	0

Outputs

Note

The outputs are returned as a tuple of objects. Make sure to unpack them as shown in the example usage.

Output	Type
fastk	np.ndarray
fastd	np.ndarray

Example usage

strategy.py

import tradomate as tm

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

    # Trying out Stochastic Relative Strength Index
    fastk, fastd = tm.ta.stochrsi(data.close, timeperiod=14, fastk_period=5, fastd_period=3, fastd_matype=0)

    # Get the last value and print
    last_value = fastk.iloc[-1]
    tm.log(f"Last value of Stochastic Relative Strength Index is {last_value}")

    # Plot the values of fastk
    tm.plot(fastk, title="Stochastic Relative Strength Index", overlay=False)