wehub-resource-sync
55 lines
2.6 KiB
Python
55 lines
2.6 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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### Uses daily data and a simple moving average cross to place trades and an ema for stop placement
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="indicators" />
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### <meta name="tag" content="trading and orders" />
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class DailyAlgorithm(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(2013,1,1) #Set Start Date
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self.set_end_date(2014,1,1) #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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self.add_equity("IBM", Resolution.HOUR, leverage=1)
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self._macd = self.macd("SPY", 12, 26, 9, MovingAverageType.WILDERS, Resolution.DAILY, Field.CLOSE)
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self._ema = self.ema("IBM", 15 * 6, Resolution.HOUR, Field.SEVEN_BAR)
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self._last_action = self.start_date
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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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Arguments:
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data: Slice object keyed by symbol containing the stock data
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'''
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if not self._macd.is_ready: return
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bar = data.bars.get("IBM")
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if not bar: return
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if self._last_action.date() == self.time.date(): return
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self._last_action = self.time
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quantity = self.portfolio["SPY"].quantity
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if quantity <= 0 and self._macd.current.value > self._macd.signal.current.value and bar.price > self._ema.current.value:
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self.set_holdings("IBM", 0.25)
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if quantity >= 0 and self._macd.current.value < self._macd.signal.current.value and bar.price < self._ema.current.value:
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self.set_holdings("IBM", -0.25)
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