# ConnorsRSI

get_connors_rsi(quotes, rsi_periods=3, streak_periods=2, rank_periods=100)

## 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, default 3 | Lookback period (`R` ) for the close price RSI. Must be greater than 1. |

`streak_periods` | int, default 2 | Lookback period (`S` ) for the streak RSI. Must be greater than 1. |

`rank_periods` | int, default 100 | Lookback period (`P` ) for the Percentile Rank. Must be greater than 1. |

### Historical quotes requirements

`N`

is the greater of `R+100`

, `S`

, and `P+2`

. You must have at least `N`

periods of `quotes`

to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least `N+150`

data points 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

```
ConnorsRSIResults[ConnorsRSIResult]
```

- This method returns a time series of all available indicator values for the
`quotes`

provided. `ConnorsRSIResults`

is just a list of`ConnorsRSIResult`

.- 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
`MAX(R,S,P)-1`

periods will have`None`

values since there’s not enough data to calculate.

⚞

Convergence warning: The first`N`

periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

### ConnorsRSIResult

name | type | notes |
---|---|---|

`date` | datetime | Date |

`rsi_close` | float, Optional | RSI(`R` ) of the Close price. |

`rsi_streak` | float, Optional | RSI(`S` ) of the Streak. |

`percent_rank` | float, Optional | Percentile rank of the period gain value. |

`connors_rsi` | float, Optional | ConnorsRSI |

### 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 ConnorsRsi(3,2.100)
results = indicators.get_connors_rsi(quotes, 3, 2, 100)
```

## About ConnorsRSI

Created by Laurence Connors, the ConnorsRSI is a composite oscillator that incorporates RSI, winning/losing streaks, and percentile gain metrics on scale of 0 to 100. See analysis. [Discuss] 💬