#!/usr/bin/env python
"""Price Oscillator Module - Price oscillators.
This module provides Price Oscillator indicators that measure the
difference between two moving averages.
Classes:
_PriceOscBase: Base class for price oscillators.
PriceOscillator: Price difference (aliases: PriceOsc, APO, AbsPriceOsc).
PercentagePriceOscillator: Percentage price oscillator (aliases: PPO, PercPriceOsc).
PercentagePriceOscillatorShort: PPO with short denominator (aliases: PPOShort).
Example:
class MyStrategy(bt.Strategy):
def __init__(self):
self.ppo = bt.indicators.PPO(self.data, period1=12, period2=26)
def next(self):
if self.ppo.ppo[0] > self.ppo.signal[0]:
self.buy()
elif self.ppo.ppo[0] < self.ppo.signal[0]:
self.sell()
"""
import math
from . import Indicator, MovAv
class _PriceOscBase(Indicator):
params = (
("period1", 12),
("period2", 26),
("_movav", MovAv.Exponential),
)
plotinfo = dict(plothlines=[0.0])
def __init__(self):
"""Initialize the price oscillator base class.
Creates two moving averages with configured periods.
"""
super().__init__()
self.ma1 = self.p._movav(self.data, period=self.p.period1)
self.ma2 = self.p._movav(self.data, period=self.p.period2)
def next(self):
"""Calculate oscillator value: ma1 - ma2."""
self.lines[0][0] = self.ma1[0] - self.ma2[0]
def once(self, start, end):
"""Calculate oscillator in runonce mode."""
ma1_array = self.ma1.lines[0].array
ma2_array = self.ma2.lines[0].array
larray = self.lines[0].array
while len(larray) < end:
larray.append(0.0)
for i in range(start, min(end, len(ma1_array), len(ma2_array))):
ma1_val = ma1_array[i] if i < len(ma1_array) else 0.0
ma2_val = ma2_array[i] if i < len(ma2_array) else 0.0
if isinstance(ma1_val, float) and math.isnan(ma1_val):
larray[i] = float("nan")
elif isinstance(ma2_val, float) and math.isnan(ma2_val):
larray[i] = float("nan")
else:
larray[i] = ma1_val - ma2_val
# Moving average difference
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class PriceOscillator(_PriceOscBase):
"""
Shows the difference between a short and long exponential moving
averages expressed in points.
Formula:
- po = ema(short) - ema(long)
See:
- http://www.metastock.com/Customer/Resources/TAAZ/?c=3&p=94
"""
alias = (
"PriceOsc",
"AbsolutePriceOscillator",
"APO",
"AbsPriceOsc",
)
lines = ("po",)
# Similar to MACD indicator, expressed in percentage
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class PercentagePriceOscillator(_PriceOscBase):
"""
Shows the difference between a short and long exponential moving
averages expressed in percentage. The MACD does the same but expressed in
absolute points.
Expressing the difference in percentage allows to compare the indicator at
different points in time when the underlying value has significatnly
different values.
Formula:
- po = 100 * (ema(short) - ema(long)) / ema(long)
See:
- http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:price_oscillators_ppo
"""
_long = True
alias = (
"PPO",
"PercPriceOsc",
)
lines = ("ppo", "signal", "histo")
params = (("period_signal", 9),)
plotlines = dict(histo=dict(_method="bar", alpha=0.50, width=1.0))
def __init__(self):
"""Initialize the PPO indicator.
Sets up signal line EMA parameters.
"""
super().__init__()
self.signal_alpha = 2.0 / (1.0 + self.p.period_signal)
self.signal_alpha1 = 1.0 - self.signal_alpha
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def next(self):
"""Calculate PPO, signal, and histogram for current bar.
PPO = 100 * (ma1 - ma2) / ma2
Signal = EMA(PPO)
Histogram = PPO - Signal
"""
# Calculate base PO
po_val = self.ma1[0] - self.ma2[0]
self.lines.po[0] = po_val
# Calculate PPO
den = self.ma2[0] if self._long else self.ma1[0]
if den != 0:
ppo_val = 100.0 * po_val / den
else:
ppo_val = 0.0
self.lines.ppo[0] = ppo_val
# Calculate signal (EMA of PPO)
self.lines.signal[0] = (
self.lines.signal[-1] * self.signal_alpha1 + ppo_val * self.signal_alpha
)
# Calculate histogram
self.lines.histo[0] = self.lines.ppo[0] - self.lines.signal[0]
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def nextstart(self):
"""Seed PPO calculation on first valid bar.
Initializes signal line with first PPO value.
"""
# Calculate base PO
po_val = self.ma1[0] - self.ma2[0]
self.lines.po[0] = po_val
# Calculate PPO
den = self.ma2[0] if self._long else self.ma1[0]
if den != 0:
ppo_val = 100.0 * po_val / den
else:
ppo_val = 0.0
self.lines.ppo[0] = ppo_val
# Seed signal with PPO
self.lines.signal[0] = ppo_val
# Calculate histogram
self.lines.histo[0] = 0.0
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def once(self, start, end):
"""Calculate PPO in runonce mode."""
ma1_array = self.ma1.lines[0].array
ma2_array = self.ma2.lines[0].array
po_array = self.lines.po.array
ppo_array = self.lines.ppo.array
signal_array = self.lines.signal.array
histo_array = self.lines.histo.array
signal_alpha = self.signal_alpha
signal_alpha1 = self.signal_alpha1
use_long = self._long
for arr in [po_array, ppo_array, signal_array, histo_array]:
while len(arr) < end:
arr.append(0.0)
prev_signal = 0.0
for i in range(start, min(end, len(ma1_array), len(ma2_array))):
ma1_val = ma1_array[i] if i < len(ma1_array) else 0.0
ma2_val = ma2_array[i] if i < len(ma2_array) else 0.0
if isinstance(ma1_val, float) and math.isnan(ma1_val):
po_array[i] = float("nan")
ppo_array[i] = float("nan")
signal_array[i] = float("nan")
histo_array[i] = float("nan")
continue
if isinstance(ma2_val, float) and math.isnan(ma2_val):
po_array[i] = float("nan")
ppo_array[i] = float("nan")
signal_array[i] = float("nan")
histo_array[i] = float("nan")
continue
po_val = ma1_val - ma2_val
po_array[i] = po_val
den = ma2_val if use_long else ma1_val
if den != 0:
ppo_val = 100.0 * po_val / den
else:
ppo_val = 0.0
ppo_array[i] = ppo_val
# Update signal
if i > 0 and i - 1 < len(signal_array):
prev_val = signal_array[i - 1]
if not (isinstance(prev_val, float) and math.isnan(prev_val)):
prev_signal = prev_val
prev_signal = prev_signal * signal_alpha1 + ppo_val * signal_alpha
signal_array[i] = prev_signal
histo_array[i] = ppo_val - prev_signal
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class PercentagePriceOscillatorShort(PercentagePriceOscillator):
"""
Shows the difference between a short and long exponential moving
averages expressed in percentage. The MACD does the same but expressed in
absolute points.
Expressing the difference in percentage allows to compare the indicator at
different points in time when the underlying value has significatnly
different values.
Most on-line literature shows the percentage calculation having the long
exponential moving average as the denominator. Some sources like MetaStock
use the short one.
Formula:
- po = 100 * (ema(short) - ema(long)) / ema(short)
See:
- http://www.metastock.com/Customer/Resources/TAAZ/?c=3&p=94
"""
_long = False
alias = (
"PPOShort",
"PercPriceOscShort",
)