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add new indicators
1 parent 5d88da3 commit 11b18a2

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Lines changed: 273 additions & 2 deletions

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‎pyrobot/indicators.py‎

Lines changed: 252 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -643,6 +643,256 @@ def mass_index(self, period: int = 9) -> pd.DataFrame:
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)
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return self._frame
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def force_index(self, period: int) -> pd.DataFrame:
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"""Calculates the Force Index.
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Arguments:
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----
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period {int} -- The number of periods to use when calculating
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the force index.
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Returns:
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----
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{pd.DataFrame} -- A Pandas data frame with the force index included.
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Usage:
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----
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>>> historical_prices_df = trading_robot.grab_historical_prices(
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start=start_date,
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end=end_date,
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bar_size=1,
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bar_type='minute'
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)
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>>> price_data_frame = pd.DataFrame(data=historical_prices)
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>>> indicator_client = Indicators(price_data_frame=price_data_frame)
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>>> indicator_client.force_index(period=9)
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"""
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locals_data = locals()
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del locals_data['self']
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column_name = 'force_index'
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self._current_indicators[column_name] = {}
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self._current_indicators[column_name]['args'] = locals_data
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self._current_indicators[column_name]['func'] = self.force_index
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# Calculate the Force Index.
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self._frame[column_name] = self._frame['close'].diff(period) * self._frame['volume'].diff(period)
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return self._frame
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def ease_of_movement(self, period: int) -> pd.DataFrame:
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"""Calculates the Ease of Movement.
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Arguments:
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----
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period {int} -- The number of periods to use when calculating
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the Ease of Movement.
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Returns:
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----
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{pd.DataFrame} -- A Pandas data frame with the Ease of Movement included.
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Usage:
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----
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>>> historical_prices_df = trading_robot.grab_historical_prices(
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start=start_date,
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end=end_date,
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bar_size=1,
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bar_type='minute'
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)
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>>> price_data_frame = pd.DataFrame(data=historical_prices)
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>>> indicator_client = Indicators(price_data_frame=price_data_frame)
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>>> indicator_client.ease_of_movement(period=9)
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"""
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locals_data = locals()
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del locals_data['self']
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column_name = 'ease_of_movement'
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self._current_indicators[column_name] = {}
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self._current_indicators[column_name]['args'] = locals_data
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self._current_indicators[column_name]['func'] = self.ease_of_movement
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# Calculate the ease of movement.
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high_plus_low = (self._frame['high'].diff(1) + self._frame['low'].diff(1))
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diff_divi_vol = (self._frame['high'] - self._frame['low']) / (2 * self._frame['volume'])
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self._frame['ease_of_movement_raw'] = high_plus_low * diff_divi_vol
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# Calculate the Rolling Average of the Ease of Movement.
724+
self._frame['ease_of_movement'] = self._frame['ease_of_movement_raw'].transform(
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lambda x: x.rolling(window=period).mean()
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)
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# Clean up before sending back.
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self._frame.drop(
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labels=['ease_of_movement_raw'],
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axis=1,
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inplace=True
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)
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return self._frame
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def commodity_channel_index(self, period: int) -> pd.DataFrame:
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"""Calculates the Commodity Channel Index.
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Arguments:
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----
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period {int} -- The number of periods to use when calculating
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the Commodity Channel Index.
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Returns:
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----
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{pd.DataFrame} -- A Pandas data frame with the Commodity Channel Index included.
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Usage:
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----
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>>> historical_prices_df = trading_robot.grab_historical_prices(
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start=start_date,
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end=end_date,
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bar_size=1,
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bar_type='minute'
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)
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>>> price_data_frame = pd.DataFrame(data=historical_prices)
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>>> indicator_client = Indicators(price_data_frame=price_data_frame)
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>>> indicator_client.commodity_channel_index(period=9)
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"""
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locals_data = locals()
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del locals_data['self']
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column_name = 'commodity_channel_index'
766+
self._current_indicators[column_name] = {}
767+
self._current_indicators[column_name]['args'] = locals_data
768+
self._current_indicators[column_name]['func'] = self.commodity_channel_index
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# Calculate the Typical Price.
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self._frame['typical_price'] = (self._frame['high'] + self._frame['low'] + self._frame['close']) / 3
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# Calculate the Rolling Average of the Typical Price.
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self._frame['typical_price_mean'] = self._frame['pp'].transform(
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lambda x: x.rolling(window=period).mean()
776+
)
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# Calculate the Rolling Standard Deviation of the Typical Price.
779+
self._frame['typical_price_std'] = self._frame['pp'].transform(
780+
lambda x: x.rolling(window=period).std()
781+
)
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# Calculate the Commodity Channel Index.
784+
self._frame[column_name] = self._frame['typical_price_mean'] / self._frame['typical_price_std']
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# Clean up before sending back.
787+
self._frame.drop(
788+
labels=['typical_price', 'typical_price_mean', 'typical_price_std'],
789+
axis=1,
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inplace=True
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)
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return self._frame
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def standard_deviation(self, period: int) -> pd.DataFrame:
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"""Calculates the Standard Deviation.
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Arguments:
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----
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period {int} -- The number of periods to use when calculating
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the standard deviation.
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Returns:
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----
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{pd.DataFrame} -- A Pandas data frame with the Standard Deviation included.
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Usage:
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----
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>>> historical_prices_df = trading_robot.grab_historical_prices(
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start=start_date,
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end=end_date,
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bar_size=1,
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bar_type='minute'
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)
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>>> price_data_frame = pd.DataFrame(data=historical_prices)
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>>> indicator_client = Indicators(price_data_frame=price_data_frame)
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>>> indicator_client.standard_deviation(period=9)
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"""
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locals_data = locals()
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del locals_data['self']
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column_name = 'standard_deviation'
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self._current_indicators[column_name] = {}
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self._current_indicators[column_name]['args'] = locals_data
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self._current_indicators[column_name]['func'] = self.standard_deviation
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# Calculate the Standard Deviation.
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self._frame[column_name] = self._frame['close'].transform(
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lambda x: x.ewm(span=period).std()
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)
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return self._frame
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def chaikin_oscillator(self, period: int) -> pd.DataFrame:
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"""Calculates the Chaikin Oscillator.
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Arguments:
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----
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period {int} -- The number of periods to use when calculating
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the Chaikin Oscillator.
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Returns:
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----
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{pd.DataFrame} -- A Pandas data frame with the Chaikin Oscillator included.
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Usage:
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----
849+
>>> historical_prices_df = trading_robot.grab_historical_prices(
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start=start_date,
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end=end_date,
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bar_size=1,
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bar_type='minute'
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)
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>>> price_data_frame = pd.DataFrame(data=historical_prices)
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>>> indicator_client = Indicators(price_data_frame=price_data_frame)
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>>> indicator_client.chaikin_oscillator(period=9)
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"""
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locals_data = locals()
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del locals_data['self']
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column_name = 'chaikin_oscillator'
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self._current_indicators[column_name] = {}
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self._current_indicators[column_name]['args'] = locals_data
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self._current_indicators[column_name]['func'] = self.chaikin_oscillator
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# Calculate the Money Flow Multiplier.
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money_flow_multiplier_top = 2 * (self._frame['close'] - self._frame['high'] - self._frame['low'])
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money_flow_multiplier_bot = (self._frame['high'] - self._frame['low'])
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# Calculate Money Flow Volume
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self._frame['money_flow_volume'] = (money_flow_multiplier_top / money_flow_multiplier_bot) * self._frame['volume']
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# Calculate the 3-Day moving average of the Money Flow Volume.
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self._frame['money_flow_volume_3'] = self._frame['money_flow_volume'].transform(
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lambda x: x.ewm(span=3, min_periods=2).mean()
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)
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# Calculate the 10-Day moving average of the Money Flow Volume.
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self._frame['money_flow_volume_10'] = self._frame['money_flow_volume'].transform(
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lambda x: x.ewm(span=10, min_periods=9).mean()
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)
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# Calculate the Chaikin Oscillator.
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self._frame[column_name] = self._frame['money_flow_volume_3'] - self._frame['money_flow_volume_10']
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# Clean up before sending back.
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self._frame.drop(
890+
labels=['money_flow_volume_3', 'money_flow_volume_10', 'money_flow_volume'],
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axis=1,
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inplace=True
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)
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895+
return self._frame
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def kst_oscillator(self, r1: int, r2: int, r3: int, r4: int, n1: int, n2: int, n3: int, n4: int) -> pd.DataFrame:
648898
"""Calculates the Mass Index indicator.
@@ -714,7 +964,7 @@ def kst_oscillator(self, r1: int, r2: int, r3: int, r4: int, n1: int, n2: int, n
714964
self._frame[column_name + "_signal"] = self._frame['column_name'].transform(
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lambda x: x.rolling().mean()
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)
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# Clean up before sending back.
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self._frame.drop(
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labels=['roc_1', 'roc_2', 'roc_3', 'roc_4', 'roc_1_n', 'roc_2_n', 'roc_3_n', 'roc_4_n'],
@@ -724,6 +974,7 @@ def kst_oscillator(self, r1: int, r2: int, r3: int, r4: int, n1: int, n2: int, n
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725975
return self._frame
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# #KST Oscillator
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# def KST(df, r1, r2, r3, r4, n1, n2, n3, n4):
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# M = df['Close'].diff(r1 - 1)

‎pyrobot/robot.py‎

Lines changed: 9 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -3,6 +3,7 @@
33
import pprint
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import pathlib
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import pandas as pd
6+
import pkg_resources
67

78
from datetime import time
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from datetime import datetime
@@ -18,8 +19,15 @@
1819
from pyrobot.portfolio import Portfolio
1920
from pyrobot.stock_frame import StockFrame
2021

22+
current_td_version = pkg_resources.get_distribution('td-ameritrade-python-api').version
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2124
from td.client import TDClient
22-
from td.utils import milliseconds_since_epoch
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if current_td_version == '0.3.0':
27+
from td.utils import TDUtilities
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milliseconds_since_epoch = TDUtilities().milliseconds_since_epoch
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else:
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from td.utils import milliseconds_since_epoch
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2533
class PyRobot():

‎trading_robot_indicators.py‎

Lines changed: 12 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -87,6 +87,18 @@
8787
# Add the Mass Index.
8888
indicator_client.mass_index(period=9)
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# Add the K-Oscillator
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indicator_client.kst_oscillator(
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r1=1,
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r2=2,
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r3=3,
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r4=4,
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n1=1,
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n2=2,
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n3=3,
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n4=4
100+
)
101+
90102
while True:
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92104
# Grab the latest bar.

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