Relative Strength Index (RSI)

get_rsi(quotes, lookback_periods=14)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`lookback_periods`	int, default 14	Number of periods (`N`) in the lookback period. Must be greater than 0.

Historical quotes requirements

You must have at least N+100 periods of quotes to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least 10×N 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.

Returns

RSIResults[RSIResult]

This method returns a time series of all available indicator values for the quotes provided.
RSIResults is just a list of RSIResult.
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 N-1 periods will have None values since there’s not enough data to calculate.

⚞ Convergence warning: The first 10×N periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

RSIResult

name	type	notes
`date`	datetime	Date
`rsi`	float, Optional	RSI over prior `N` lookback 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 RSI(14)
results = indicators.get_rsi(quotes, 14)

About Relative Strength Index (RSI)

Created by J. Welles Wilder, the Relative Strength Index measures strength of the winning/losing streak over N lookback periods on a scale of 0 to 100, to depict overbought and oversold conditions. [Discuss] 💬