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Ultimate Oscillator

One of the goals when the development of backtrader was kickstarted was to make it very easy (at least for the author himself) to develop new Indicators to test ideas both mathematically and visually.

Ticket #102 is about adding the UltimateOscillator to the arsenal of backtrader

Note

It will be added in the next release, meanwhile it can be used, using the code below.

The reference as indicated in the ticket:

and also at:

No need to repeat it here.

Quoting from the reference:

BP = Close - Minimum(Low or Prior Close)

TR = Maximum(High or Prior Close)  -  Minimum(Low or Prior Close)

Average7 = (7-period BP Sum) / (7-period TR Sum)
Average14 = (14-period BP Sum) / (14-period TR Sum)
Average28 = (28-period BP Sum) / (28-period TR Sum)

UO = 100 x [(4 x Average7)+(2 x Average14)+Average28]/(4+2+1)

Summary:

  • First subclass from bt.Indicator to make sure the entire machinery works:

    class UltimateOscillator(bt.Indicator):
    
  • It has 1 output line: we’ll name it uo:

    lines = ('uo',)
    
  • It has 3 parameters which define 3 periods with default values 7, 14 and 28. To be named p1, p2 and p3:

    params = (('p1', 7),
              ('p2', 14),
              ('p3', 28),
    )
    
  • The calculations use some things already built-in backtrader

    • Minimum(Low or Prior Close): this is TrueLow as defined by Welles Wilder for the RSI indicator. As such the BP or Buying Pressure can be calculated:
    bp = self.data.close - TrueLow(self.data)
    
    • Maximum(Low or Prior Close) - Minimum(Low or Prior Close): this is TrueRange as defined by Welles Wilder for the RSI indicator (which can be expressed as TrueHigh - TrueLow. The next calculation is therefore as easy as:
    tr = TrueRange(self.data)
    
    • The rest are pure math operations, using SumN to add up the latest p1, p2, p3 periods of bp and tr, plus the weighted calculation:
    av7 = SumN(bp, period=self.p.p1) / SumN(tr, period=self.p.p1)
    av14 = SumN(bp, period=self.p.p2) / SumN(tr, period=self.p.p2)
    av28 = SumN(bp, period=self.p.p3) / SumN(tr, period=self.p.p3)
    
    uo = 100.0 * (4.0 * av7 + 2.0 * av14 + av28) / (4.0 + 2.0 + 1.0)
    
    • Finally the assignment of the calculation to the defined uo line:
    self.lines.uo = uo
    

It seems longer than it actually is (the full code, including imports) at the bottom.

Since we want not only the values but also a nice looking plot, like the ones provided by Stockcharts, we’ll be adding 2 extra touches:

  • 2 parameters which determine where to place the horizontal lines that delimit the overbought and oversold areas (ala RSI or Stochastic):

    ('upperband', 70.0),
    ('lowerband', 30.0),
    
  • And plot initialization code to use the parameters. Ticks at 10, 50 and 90 like in the Stockcharts plots will be added:

    def _plotinit(self):
        baseticks = [10.0, 50.0, 90.0]
        hlines = [self.p.upperband, self.p.lowerband]
    
        self.plotinfo.plotyhlines = hlines
        self.plotinfo.plotyticks = baseticks + hlines
    

To test and to further use existing facilities provided by backtrader, the btrun executable installed along with backtrader will be used.

  • The indicator is stored in a file named ultimateoscillator.py

  • The data used is one of the data samples available in the sources of backtrader

  • The indicator will be added twice with the default parameters and with shorter term parameters

Execution:

btrun \
  --nostdstats \
  --data 2005-2006-day-001.txt \
  --indicator ultimateoscillator:UltimateOscillator \
  --indicator ultimateoscillator:UltimateOscillator:p1=4,p2=8,p3=16 \
  --plot

Note

Using –nostdstats to remove some observers from the chart. No need to track cash and value in this case

The output is simply a chart showing the evolution of the UltimateOscillator.

!image

The UltimateOscillator code:

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)


import backtrader as bt
from backtrader.indicators import SumN, TrueLow, TrueRange


class UltimateOscillator(bt.Indicator):
    '''
    Formula:
      # Buying Pressure = Close - TrueLow
      BP = Close - Minimum(Low or Prior Close)

      # TrueRange = TrueHigh - TrueLow
      TR = Maximum(High or Prior Close)  -  Minimum(Low or Prior Close)

      Average7 = (7-period BP Sum) / (7-period TR Sum)
      Average14 = (14-period BP Sum) / (14-period TR Sum)
      Average28 = (28-period BP Sum) / (28-period TR Sum)

      UO = 100 x [(4 x Average7)+(2 x Average14)+Average28]/(4+2+1)

    See:

      - https://en.wikipedia.org/wiki/Ultimate_oscillator
      - http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:ultimate_oscillator
    '''
    lines = ('uo',)

    params = (('p1', 7),
              ('p2', 14),
              ('p3', 28),
              ('upperband', 70.0),
              ('lowerband', 30.0),
    )

    def _plotinit(self):
        baseticks = [10.0, 50.0, 90.0]
        hlines = [self.p.upperband, self.p.lowerband]

        self.plotinfo.plotyhlines = hlines
        self.plotinfo.plotyticks = baseticks + hlines

    def __init__(self):
        bp = self.data.close - TrueLow(self.data)
        tr = TrueRange(self.data)

        av7 = SumN(bp, period=self.p.p1) / SumN(tr, period=self.p.p1)
        av14 = SumN(bp, period=self.p.p2) / SumN(tr, period=self.p.p2)
        av28 = SumN(bp, period=self.p.p3) / SumN(tr, period=self.p.p3)

        uo = 100.0 * (4.0 * av7 + 2.0 * av14 + av28) / (4.0 + 2.0 + 1.0)
        self.lines.uo = uo