wehub-resource-sync
59 lines
2.9 KiB
Python
59 lines
2.9 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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### <summary>
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### Demonstration algorithm of indicators history window usage
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### </summary>
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class IndicatorHistoryAlgorithm(QCAlgorithm):
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'''Demonstration algorithm of indicators history window usage.'''
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def initialize(self):
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'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
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self.set_start_date(2013, 1, 1)
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self.set_end_date(2014, 12, 31)
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self.set_cash(25000)
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self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
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self.bollinger_bands = self.bb(self._symbol, 20, 2.0, resolution=Resolution.DAILY)
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# Let's keep BB values for a 20 day period
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self.bollinger_bands.window.size = 20
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# Also keep the same period of data for the middle band
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self.bollinger_bands.middle_band.window.size = 20
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def on_data(self, slice: Slice):
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# Let's wait for our indicator to fully initialize and have a full window of history data
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if not self.bollinger_bands.window.is_ready: return
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# We can access the current and oldest (in our period) values of the indicator
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self.log(f"Current BB value: {self.bollinger_bands[0].end_time} - {self.bollinger_bands[0].value}")
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self.log(f"Oldest BB value: {self.bollinger_bands[self.bollinger_bands.window.count - 1].end_time} - "
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f"{self.bollinger_bands[self.bollinger_bands.window.count - 1].value}")
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# Let's log the BB values for the last 20 days, for demonstration purposes on how it can be enumerated
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for data_point in self.bollinger_bands:
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self.log(f"BB @{data_point.end_time}: {data_point.value}")
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# We can also do the same for internal indicators:
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middle_band = self.bollinger_bands.middle_band
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self.log(f"Current BB Middle Band value: {middle_band[0].end_time} - {middle_band[0].value}")
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self.log(f"Oldest BB Middle Band value: {middle_band[middle_band.window.count - 1].end_time} - "
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f"{middle_band[middle_band.window.count - 1].value}")
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for data_point in middle_band:
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self.log(f"BB Middle Band @{data_point.end_time}: {data_point.value}")
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# We are done now!
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self.quit()
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