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76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
# -*- coding: utf-8 -*-
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from .ad import ad
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from ..overlap.ema import ema
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from ..utils import get_offset, verify_series
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def adosc(high, low, close, volume, open_=None, fast=None, slow=None, offset=None, **kwargs):
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"""Indicator: Accumulation/Distribution Oscillator"""
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# Validate Arguments
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high = verify_series(high)
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low = verify_series(low)
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close = verify_series(close)
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volume = verify_series(volume)
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fast = int(fast) if fast and fast > 0 else 3
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slow = int(slow) if slow and slow > 0 else 10
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offset = get_offset(offset)
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# Calculate Result
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ad_ = ad(high=high, low=low, close=close, volume=volume, open_=open_)
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fast_ad = ema(close=ad_, length=fast, **kwargs)
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slow_ad = ema(close=ad_, length=slow, **kwargs)
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adosc = fast_ad - slow_ad
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# Offset
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if offset != 0:
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adosc = adosc.shift(offset)
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# Handle fills
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if 'fillna' in kwargs:
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adosc.fillna(kwargs['fillna'], inplace=True)
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if 'fill_method' in kwargs:
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adosc.fillna(method=kwargs['fill_method'], inplace=True)
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# Name and Categorize it
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adosc.name = f"ADOSC_{fast}_{slow}"
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adosc.category = 'volume'
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return adosc
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adosc.__doc__ = \
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"""Accumulation/Distribution Oscillator or Chaikin Oscillator
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Accumulation/Distribution Oscillator indicator utilizes
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Accumulation/Distribution and treats it similarily to MACD
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or APO.
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Sources:
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https://www.investopedia.com/articles/active-trading/031914/understanding-chaikin-oscillator.asp
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Calculation:
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Default Inputs:
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fast=12, slow=26
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AD = Accum/Dist
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ad = AD(high, low, close, open)
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fast_ad = EMA(ad, fast)
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slow_ad = EMA(ad, slow)
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ADOSC = fast_ad - slow_ad
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Args:
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high (pd.Series): Series of 'high's
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low (pd.Series): Series of 'low's
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close (pd.Series): Series of 'close's
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open (pd.Series): Series of 'open's
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volume (pd.Series): Series of 'volume's
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fast (int): The short period. Default: 12
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slow (int): The long period. Default: 26
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offset (int): How many periods to offset the result. Default: 0
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Kwargs:
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fillna (value, optional): pd.DataFrame.fillna(value)
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fill_method (value, optional): Type of fill method
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Returns:
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pd.Series: New feature generated.
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""" |