Source code for pandas_ta.volume.aobv

# -*- coding: utf-8 -*-
from pandas import DataFrame
from .obv import obv
from pandas_ta.overlap import ma
from pandas_ta.trend import long_run, short_run
from pandas_ta.utils import get_offset, verify_series

[docs]def aobv(close, volume, fast=None, slow=None, max_lookback=None, min_lookback=None, mamode=None, offset=None, **kwargs): """Indicator: Archer On Balance Volume (AOBV)""" # Validate arguments fast = int(fast) if fast and fast > 0 else 4 slow = int(slow) if slow and slow > 0 else 12 max_lookback = int(max_lookback) if max_lookback and max_lookback > 0 else 2 min_lookback = int(min_lookback) if min_lookback and min_lookback > 0 else 2 if slow < fast: fast, slow = slow, fast mamode = mamode if isinstance(mamode, str) else "ema" _length = max(fast, slow, max_lookback, min_lookback) close = verify_series(close, _length) volume = verify_series(volume, _length) offset = get_offset(offset) if "length" in kwargs: kwargs.pop("length") run_length = kwargs.pop("run_length", 2) if close is None or volume is None: return # Calculate Result obv_ = obv(close=close, volume=volume, **kwargs) maf = ma(mamode, obv_, length=fast, **kwargs) mas = ma(mamode, obv_, length=slow, **kwargs) # When MAs are long and short obv_long = long_run(maf, mas, length=run_length) obv_short = short_run(maf, mas, length=run_length) # Offset if offset != 0: obv_ = obv_.shift(offset) maf = maf.shift(offset) mas = mas.shift(offset) obv_long = obv_long.shift(offset) obv_short = obv_short.shift(offset) # # Handle fills if "fillna" in kwargs: obv_.fillna(kwargs["fillna"], inplace=True) maf.fillna(kwargs["fillna"], inplace=True) mas.fillna(kwargs["fillna"], inplace=True) obv_long.fillna(kwargs["fillna"], inplace=True) obv_short.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: obv_.fillna(method=kwargs["fill_method"], inplace=True) maf.fillna(method=kwargs["fill_method"], inplace=True) mas.fillna(method=kwargs["fill_method"], inplace=True) obv_long.fillna(method=kwargs["fill_method"], inplace=True) obv_short.fillna(method=kwargs["fill_method"], inplace=True) # Prepare DataFrame to return _mode = mamode.lower()[0] if len(mamode) else "" data = { obv_, f"OBV_min_{min_lookback}": obv_.rolling(min_lookback).min(), f"OBV_max_{max_lookback}": obv_.rolling(max_lookback).max(), f"OBV{_mode}_{fast}": maf, f"OBV{_mode}_{slow}": mas, f"AOBV_LR_{run_length}": obv_long, f"AOBV_SR_{run_length}": obv_short, } aobvdf = DataFrame(data) # Name and Categorize it = f"AOBV{_mode}_{fast}_{slow}_{min_lookback}_{max_lookback}_{run_length}" aobvdf.category = "volume" return aobvdf