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77 lines
2.3 KiB
Python
77 lines
2.3 KiB
Python
# -*- coding: utf-8 -*-
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from ..utils import get_drift, get_offset, verify_series
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def efi(close, volume, length=None, drift=None, mamode=None, offset=None, **kwargs):
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"""Indicator: Elder's Force Index (EFI)"""
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# Validate arguments
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close = verify_series(close)
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volume = verify_series(volume)
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length = int(length) if length and length > 0 else 13
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min_periods = int(kwargs['min_periods']) if 'min_periods' in kwargs and kwargs['min_periods'] is not None else length
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drift = get_drift(drift)
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mamode = mamode.lower() if mamode else None
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offset = get_offset(offset)
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# Calculate Result
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pv_diff = close.diff(drift) * volume
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if mamode == 'sma':
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efi = pv_diff.rolling(length, min_periods=min_periods).mean()
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else:
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efi = pv_diff.ewm(span=length, min_periods=min_periods).mean()
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# Offset
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if offset != 0:
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efi = efi.shift(offset)
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# Handle fills
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if 'fillna' in kwargs:
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efi.fillna(kwargs['fillna'], inplace=True)
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if 'fill_method' in kwargs:
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efi.fillna(method=kwargs['fill_method'], inplace=True)
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# Name and Categorize it
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efi.name = f"EFI_{length}"
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efi.category = 'volume'
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return efi
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efi.__doc__ = \
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"""Elder's Force Index (EFI)
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Elder's Force Index measures the power behind a price movement using price
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and volume as well as potential reversals and price corrections.
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Sources:
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https://www.tradingview.com/wiki/Elder%27s_Force_Index_(EFI)
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https://www.motivewave.com/studies/elders_force_index.htm
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Calculation:
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Default Inputs:
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length=20, drift=1, mamode=None
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EMA = Exponential Moving Average
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SMA = Simple Moving Average
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pv_diff = close.diff(drift) * volume
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if mamode == 'sma':
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EFI = SMA(pv_diff, length)
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else:
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EFI = EMA(pv_diff, length)
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Args:
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close (pd.Series): Series of 'close's
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volume (pd.Series): Series of 'volume's
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length (int): The short period. Default: 13
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drift (int): The diff period. Default: 1
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mamode (str): Two options: None or 'sma'. Default: None
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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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""" |