Source code for pandas_ta.volume.obv
# -*- coding: utf-8 -*-
from pandas_ta import Imports
from pandas_ta.utils import get_offset, signed_series, verify_series
[docs]def obv(close, volume, talib=None, offset=None, **kwargs):
"""Indicator: On Balance Volume (OBV)"""
# Validate arguments
close = verify_series(close)
volume = verify_series(volume)
offset = get_offset(offset)
mode_tal = bool(talib) if isinstance(talib, bool) else True
# Calculate Result
if Imports["talib"] and mode_tal:
from talib import OBV
obv = OBV(close, volume)
else:
signed_volume = signed_series(close, initial=1) * volume
obv = signed_volume.cumsum()
# Offset
if offset != 0:
obv = obv.shift(offset)
# Handle fills
if "fillna" in kwargs:
obv.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
obv.fillna(method=kwargs["fill_method"], inplace=True)
# Name and Categorize it
obv.name = f"OBV"
obv.category = "volume"
return obv
obv.__doc__ = \
"""On Balance Volume (OBV)
On Balance Volume is a cumulative indicator to measure buying and selling
pressure.
Sources:
https://www.tradingview.com/wiki/On_Balance_Volume_(OBV)
https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/on-balance-volume-obv/
https://www.motivewave.com/studies/on_balance_volume.htm
Calculation:
signed_volume = signed_series(close, initial=1) * volume
obv = signed_volume.cumsum()
Args:
close (pd.Series): Series of 'close's
volume (pd.Series): Series of 'volume's
talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib
version. Default: True
offset (int): How many periods to offset the result. Default: 0
Kwargs:
fillna (value, optional): pd.DataFrame.fillna(value)
fill_method (value, optional): Type of fill method
Returns:
pd.Series: New feature generated.
"""