PSAR Calculation Class

psar.py

from collections import deque

class PSAR:
  '''
  Calculates the Parabolic Stop-and-Reverse (PSAR) indicator for trading.
  Find the full explanation here:
  https://raposa.trade/blog/the-complete-guide-to-calculating-the-parabolic-sar-in-python/
  '''

  def __init__(self, init_af=0.02, max_af=0.2, af_step=0.02):
    self.max_af = max_af
    self.init_af = init_af
    self.af = init_af
    self.af_step = af_step
    self.extreme_point = None
    self.high_price_trend = []
    self.low_price_trend = []
    self.high_price_window = deque(maxlen=2)
    self.low_price_window = deque(maxlen=2)

    # Lists to track results
    self.psar_list = []
    self.af_list = []
    self.ep_list = []
    self.high_list = []
    self.low_list = []
    self.trend_list = []
    self._num_days = 0

  def calcPSAR(self, high, low):
    if self._num_days >= 3:
      psar = self._calcPSAR()
    else:
      psar = self._initPSARVals(high, low)

    psar = self._updateCurrentVals(psar, high, low)
    self._num_days += 1

    return psar

  def _initPSARVals(self, high, low):
    if len(self.low_price_window) <= 1:
      self.trend = None
      self.extreme_point = high
      return None

    if self.high_price_window[0] < self.high_price_window[1]:
      self.trend = 1
      psar = min(self.low_price_window)
      self.extreme_point = max(self.high_price_window)
    else: 
      self.trend = 0
      psar = max(self.high_price_window)
      self.extreme_point = min(self.low_price_window)

    return psar

  def _calcPSAR(self):
    prev_psar = self.psar_list[-1]
    if self.trend == 1: # Up
      psar = prev_psar + self.af * (self.extreme_point - prev_psar)
      psar = min(psar, min(self.low_price_window))
    else:
      psar = prev_psar - self.af * (prev_psar - self.extreme_point)
      psar = max(psar, max(self.high_price_window))

    return psar

  def _updateCurrentVals(self, psar, high, low):
    if self.trend == 1:
      self.high_price_trend.append(high)
    elif self.trend == 0:
      self.low_price_trend.append(low)

    psar = self._trendReversal(psar, high, low)

    self.psar_list.append(psar)
    self.af_list.append(self.af)
    self.ep_list.append(self.extreme_point)
    self.high_list.append(high)
    self.low_list.append(low)
    self.high_price_window.append(high)
    self.low_price_window.append(low)
    self.trend_list.append(self.trend)

    return psar

  def _trendReversal(self, psar, high, low):
    # Checks for reversals
    reversal = False
    if self.trend == 1 and psar > low:
      self.trend = 0
      psar = max(self.high_price_trend)
      self.extreme_point = low
      reversal = True
    elif self.trend == 0 and psar < high:
      self.trend = 1
      psar = min(self.low_price_trend)
      self.extreme_point = high
      reversal = True

    if reversal:
      self.af = self.init_af
      self.high_price_trend.clear()
      self.low_price_trend.clear()
    else:
        if high > self.extreme_point and self.trend == 1:
          self.af = min(self.af + self.af_step, self.max_af)
          self.extreme_point = high
        elif low < self.extreme_point and self.trend == 0:
          self.af = min(self.af + self.af_step, self.max_af)
          self.extreme_point = low

    return psar