90 lines
3.3 KiB
Python
90 lines
3.3 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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class IndicatorExtensionsSMAWithCustomIndicatorsRegressionAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_start_date(2020, 2, 20)
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self.set_end_date(2020, 4, 20)
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self.qqq = self.add_equity("QQQ", Resolution.DAILY).symbol
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self.range_indicator = RangeIndicator("range1")
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self.range_sma = IndicatorExtensions.sma(self.range_indicator, 5)
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self.range_indicator_2 = RangeIndicator2("range2")
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self.range_sma_2 = IndicatorExtensions.sma(self.range_indicator_2, 5)
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def on_data(self, data):
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self.range_indicator.update(data.bars.get(self.qqq))
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self.range_indicator_2.update(data.bars.get(self.qqq))
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self.debug(f"{self.range_indicator.name} {self.range_indicator.value}")
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self.debug(f"{self.range_sma.name} {self.range_sma.current.value}")
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self.debug(f"{self.range_indicator_2.name} {self.range_indicator_2.value}")
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self.debug(f"{self.range_sma_2.name} {self.range_sma_2.current.value}")
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def on_end_of_algorithm(self):
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if not self.range_sma.is_ready:
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raise AssertionError(f"{self.range_sma.name} should have been ready at the end of the algorithm, but it wasn't. The indicator received {self.range_sma.samples} samples.")
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if not self.range_sma_2.is_ready:
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raise AssertionError(f"{self.range_sma_2.name} should have been ready at the end of the algorithm, but it wasn't. The indicator received {self.range_sma_2.samples} samples.")
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class RangeIndicator(PythonIndicator):
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def __init__(self, name):
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self.name = name
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self.time = datetime.min
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self.value = 0
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self.is_ready = False
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@property
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def is_ready(self):
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return self._is_ready
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@is_ready.setter
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def is_ready(self, value):
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self._is_ready = value
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def update(self, bar: TradeBar):
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if bar is None:
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return False
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self.value = bar.high - bar.low
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self.time = bar.time
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self.is_ready = True
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self.on_updated(IndicatorDataPoint(bar.end_time, self.value))
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return True
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class RangeIndicator2(PythonIndicator):
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def __init__(self, name):
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self.name = name
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self.time = datetime.min
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self.value = 0
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self._is_ready = False
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@property
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def is_ready(self):
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return self._is_ready
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def update(self, bar: TradeBar):
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if bar is None:
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return False
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self.value = bar.high - bar.low
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self.time = bar.time
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self._is_ready = True
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self.on_updated(IndicatorDataPoint(bar.end_time, self.value))
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return True
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