On-Balance Volume (OBV)

get_obv(quotes, sma_periods=None)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame
`sma_periods`	int, Optional	Number of periods (`N`) in the moving average of OBV. Must be greater than 0, if specified.

Historical quotes requirements

You must have at least two historical quotes to cover the warmup periods; however, since this is a trendline, more is recommended.

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

OBVResults[OBVResult]

This method returns a time series of all available indicator values for the quotes provided.
OBVResults is just a list of OBVResult.
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 period OBV will have 0 value since there’s not enough data to calculate.

ObvResult

name	type	notes
`date`	datetime	Date
`obv`	float	On-balance Volume
`obv_sma`	float, Optional	Moving average (SMA) of OBV based on `sma_periods` periods, if specified

🚩 Warning: absolute values in OBV are somewhat meaningless. Use with caution.

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
results = indicators.get_obv(quotes)

About On-Balance Volume (OBV)

Popularized by Joseph Granville, On-balance Volume is a rolling accumulation of volume based on Close price direction. [Discuss] 💬