# -*- coding: utf-8 -*-
from pandas import DataFrame
from pandas_ta import Imports
from pandas_ta.overlap import hlc3
from pandas_ta.utils import get_drift, get_offset, verify_series
[docs]def mfi(high, low, close, volume, length=None, talib=None, drift=None, offset=None, **kwargs):
"""Indicator: Money Flow Index (MFI)"""
# Validate arguments
length = int(length) if length and length > 0 else 14
high = verify_series(high, length)
low = verify_series(low, length)
close = verify_series(close, length)
volume = verify_series(volume, length)
drift = get_drift(drift)
offset = get_offset(offset)
mode_tal = bool(talib) if isinstance(talib, bool) else True
if high is None or low is None or close is None or volume is None: return
# Calculate Result
if Imports["talib"] and mode_tal:
from talib import MFI
mfi = MFI(high, low, close, volume, length)
else:
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
talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib
version. Default: True
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.
"""