Stochastic RSI

get_stoch_rsi(quotes, rsi_periods, stoch_periods, signal_periods, smooth_periods=1)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`rsi_periods`	int	Number of periods (`R`) in the lookback period. Must be greater than 0. Standard is 14.
`stoch_periods`	int	Number of periods (`S`) in the lookback period. Must be greater than 0. Typically the same value as `rsi_periods`.
`signal_periods`	int	Number of periods (`G`) in the signal line (SMA of the StochRSI). Must be greater than 0. Typically 3-5.
`smooth_periods`	int, default 1	Smoothing periods (`M`) for the Stochastic. Must be greater than 0.

The original Stochastic RSI formula uses a the Fast variant of the Stochastic calculation (smooth_periods=1). For a standard period of 14, the original formula would be indicators.get_stoch_rsi(quotes, 14, 14, 3, 1). The “3” here is just for the Signal (%D), which is not present in the original formula, but useful for additional smoothing and analysis.

Historical quotes requirements

You must have at least N periods of quotes, where N is the greater of R+S+M and R+100 to cover the warmup periods. Since this uses a smoothing technique in the underlying RSI value, we recommend you use at least 10×R periods prior to the intended usage date for better precision.

quotes is an Iterable[Quote] collection of historical price quotes. It should have a consistent frequency (day, hour, minute, etc). See the Guide for more information.

Return

StochRSIResults[StochRSIResult]

This method returns a time series of all available indicator values for the quotes provided.
StochRSIResults is just a list of StochRSIResult.
It always returns the same number of elements as there are in the historical quotes.
It does not return a single incremental indicator value.
The first R+S+M periods will have None values for stoch_rsi since there’s not enough data to calculate.

⚞ Convergence warning: The first 10×R periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods. We recommend pruning at least R+S+M+100 initial values.

StochRSIResult

name	type	notes
`date`	datetime	Date
`stoch_rsi`	float, Optional	%K Oscillator = Stochastic RSI = Stoch(`S`,`G`,`M`) of RSI(`R`) of Close price
`signal`	float, Optional	%D Signal Line = Simple moving average of %K based on `G` periods

Utilities

See Utilities and Helpers for more information.

Example

from stock_indicators import indicators

# This method is NOT a part of the library.
quotes = get_historical_quotes("SPY")

# calculate StochRSI
results = indicators.get_stoch_rsi(quotes, 14, 14, 1, 1)

About Stochastic RSI

Created by by Tushar Chande and Stanley Kroll, Stochastic RSI is a Stochastic interpretation of the Relative Strength Index. It is different from, and often confused with the more traditional Stochastic Oscillator. [Discuss] 💬