Relative Strength Index (RSI)
get_rsi(quotes, lookback_periods=14)
Parameters
name | type | notes |
---|---|---|
quotes |
Iterable[Quote] | Iterable(such as list or an object having __iter__() ) of the Quote class or its sub-class. • Need help 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 ofRSIResult
. - 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 haveNone
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_history_from_feed("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.
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