wehub-resource-sync
69 lines
3.1 KiB
Python
69 lines
3.1 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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### Using rolling windows for efficient storage of historical data; which automatically clears after a period of time.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="history and warm up" />
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### <meta name="tag" content="history" />
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### <meta name="tag" content="warm up" />
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### <meta name="tag" content="indicators" />
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### <meta name="tag" content="rolling windows" />
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class RollingWindowAlgorithm(QCAlgorithm):
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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(2013,10,1) #Set Start Date
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self.set_end_date(2013,11,1) #Set End Date
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self.set_cash(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.add_equity("SPY", Resolution.DAILY)
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# Creates a Rolling Window indicator to keep the 2 TradeBar
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self._window = RollingWindow(2) # For other security types, use QuoteBar
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# Creates an indicator and adds to a rolling window when it is updated
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self._sma = self.sma("SPY", 5)
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self._sma.updated += self._sma_updated
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self._sma_win = RollingWindow(5)
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def _sma_updated(self, sender, updated):
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'''Adds updated values to rolling window'''
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self._sma_win.add(updated)
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def on_data(self, data):
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'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
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# Add SPY TradeBar in rollling window
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self._window.add(data["SPY"])
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# Wait for windows to be ready.
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if not (self._window.is_ready and self._sma_win.is_ready): return
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curr_bar = self._window[0] # Current bar had index zero.
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past_bar = self._window[1] # Past bar has index one.
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self.log(f"Price: {past_bar.time} -> {past_bar.close} ... {curr_bar.time} -> {curr_bar.close}")
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curr_sma = self._sma_win[0] # Current SMA had index zero.
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past_sma = self._sma_win[self._sma_win.count-1] # Oldest SMA has index of window count minus 1.
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self.log(f"SMA: {past_sma.time} -> {past_sma.value} ... {curr_sma.time} -> {curr_sma.value}")
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if not self.portfolio.invested and curr_sma.value > past_sma.value:
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self.set_holdings("SPY", 1)
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