# stochrsi#

API documentation for pandas_ta.momentum.stochrsi Python function.

stochrsi(close, length=None, rsi_length=None, k=None, d=None, mamode=None, offset=None, **kwargs)[source]#

Stochastic (STOCHRSI)

“Stochastic RSI and Dynamic Momentum Index” was created by Tushar Chande and Stanley Kroll and published in Stock & Commodities V.11:5 (189-199)

It is a range-bound oscillator with two lines moving between 0 and 100. The first line (%K) displays the current RSI in relation to the period’s high/low range. The second line (%D) is a Simple Moving Average of the %K line. The most common choices are a 14 period %K and a 3 period SMA for %D.

Sources:
Calculation:
Default Inputs:

length=14, rsi_length=14, k=3, d=3

RSI = Relative Strength Index SMA = Simple Moving Average

RSI = RSI(high, low, close, rsi_length) LL = lowest RSI for last rsi_length periods HH = highest RSI for last rsi_length periods

STOCHRSI = 100 * (RSI - LL) / (HH - LL) STOCHRSIk = SMA(STOCHRSI, k) STOCHRSId = SMA(STOCHRSIk, d)

Args:

high (pd.Series): Series of ‘high’s low (pd.Series): Series of ‘low’s close (pd.Series): Series of ‘close’s length (int): The STOCHRSI period. Default: 14 rsi_length (int): RSI period. Default: 14 k (int): The Fast %K period. Default: 3 d (int): The Slow %K period. Default: 3 mamode (str): See ``help(ta.ma)``. Default: ‘sma’ offset (int): How many periods to offset the result. Default: 0

Kwargs:

fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method

Returns:

pd.DataFrame: RSI %K, RSI %D columns.