# 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_history_from_feed("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] 💬