Source code for pandas_ta.momentum.pgo

# -*- coding: utf-8 -*-
from pandas_ta.overlap import ema, sma
from pandas_ta.volatility import atr
from pandas_ta.utils import get_offset, verify_series

[docs]def pgo(high, low, close, length=None, offset=None, **kwargs): """Indicator: Pretty Good Oscillator (PGO)""" # 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) offset = get_offset(offset) if high is None or low is None or close is None: return # Calculate Result pgo = close - sma(close, length) pgo /= ema(atr(high, low, close, length), length) # Offset if offset != 0: pgo = pgo.shift(offset) # Handle fills if "fillna" in kwargs: pgo.fillna(kwargs["fillna"], inplace=True) if "fill_method" in kwargs: pgo.fillna(method=kwargs["fill_method"], inplace=True) # Name and Categorize it = f"PGO_{length}" pgo.category = "momentum" return pgo
pgo.__doc__ = \ """Pretty Good Oscillator (PGO) The Pretty Good Oscillator indicator was created by Mark Johnson to measure the distance of the current close from its N-day Simple Moving Average, expressed in terms of an average true range over a similar period. Johnson's approach was to use it as a breakout system for longer term trades. Long if greater than 3.0 and short if less than -3.0. Sources: Calculation: Default Inputs: length=14 ATR = Average True Range SMA = Simple Moving Average EMA = Exponential Moving Average PGO = (close - SMA(close, length)) / EMA(ATR(high, low, close, length), length) Args: high (pd.Series): Series of 'high's low (pd.Series): Series of 'low's close (pd.Series): Series of 'close's length (int): It's period. Default: 14 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. """