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pandas-ta/pandas_ta/volume/mfi.py
T
2019-05-20 13:25:33 -07:00

89 lines
2.6 KiB
Python

# -*- coding: utf-8 -*-
from pandas import DataFrame
from ..overlap.hlc3 import hlc3
from ..utils import get_drift, get_offset, verify_series
def mfi(high, low, close, volume, length=None, drift=None, offset=None, **kwargs):
"""Indicator: Money Flow Index (MFI)"""
# Validate arguments
high = verify_series(high)
low = verify_series(low)
close = verify_series(close)
volume = verify_series(volume)
length = int(length) if length and length > 0 else 14
drift = get_drift(drift)
offset = get_offset(offset)
# Calculate Result
typical_price = hlc3(high=high, low=low, close=close)
raw_money_flow = typical_price * volume
tdf = DataFrame({'diff': 0, 'rmf': raw_money_flow, '+mf': 0, '-mf': 0})
tdf.loc[(typical_price.diff(drift) > 0), 'diff'] = 1
tdf.loc[tdf['diff'] == 1, '+mf'] = raw_money_flow
tdf.loc[(typical_price.diff(drift) < 0), 'diff'] = -1
tdf.loc[tdf['diff'] == -1, '-mf'] = raw_money_flow
psum = tdf['+mf'].rolling(length).sum()
nsum = tdf['-mf'].rolling(length).sum()
tdf['mr'] = psum / nsum
mfi = 100 * psum / (psum + nsum)
tdf['mfi'] = mfi
# Offset
if offset != 0:
mfi = mfi.shift(offset)
# Handle fills
if 'fillna' in kwargs:
mfi.fillna(kwargs['fillna'], inplace=True)
if 'fill_method' in kwargs:
mfi.fillna(method=kwargs['fill_method'], inplace=True)
# Name and Categorize it
mfi.name = f"MFI_{length}"
mfi.category = 'volume'
return mfi
mfi.__doc__ = \
"""Money Flow Index (MFI)
Money Flow Index is an oscillator indicator that is used to measure buying and
selling pressure by utilizing both price and volume.
Sources:
https://www.tradingview.com/wiki/Money_Flow_(MFI)
Calculation:
Default Inputs:
length=14, drift=1
tp = typical_price = hlc3 = (high + low + close) / 3
rmf = raw_money_flow = tp * volume
pmf = pos_money_flow = SUM(rmf, length) if tp.diff(drift) > 0 else 0
nmf = neg_money_flow = SUM(rmf, length) if tp.diff(drift) < 0 else 0
MFR = money_flow_ratio = pmf / nmf
MFI = money_flow_index = 100 * pmf / (pmf + nmf)
Args:
high (pd.Series): Series of 'high's
low (pd.Series): Series of 'low's
close (pd.Series): Series of 'close's
volume (pd.Series): Series of 'volume's
length (int): The sum period. Default: 14
drift (int): The difference period. Default: 1
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.
"""