chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
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+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from AlgorithmImports import *
+
+### <summary>
+### Uses daily data and a simple moving average cross to place trades and an ema for stop placement
+### </summary>
+### <meta name="tag" content="using data" />
+### <meta name="tag" content="indicators" />
+### <meta name="tag" content="trading and orders" />
+class DailyAlgorithm(QCAlgorithm):
+
+    def initialize(self):
+        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
+
+        self.set_start_date(2013,1,1)    #Set Start Date
+        self.set_end_date(2014,1,1)      #Set End Date
+        self.set_cash(100000)           #Set Strategy Cash
+        # Find more symbols here: http://quantconnect.com/data
+        self.add_equity("SPY", Resolution.DAILY)
+        self.add_equity("IBM", Resolution.HOUR, leverage=1)
+        self._macd = self.macd("SPY", 12, 26, 9, MovingAverageType.WILDERS, Resolution.DAILY, Field.CLOSE)
+        self._ema = self.ema("IBM", 15 * 6, Resolution.HOUR, Field.SEVEN_BAR)
+        self._last_action = self.start_date
+
+    def on_data(self, data):
+        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+
+        Arguments:
+            data: Slice object keyed by symbol containing the stock data
+        '''
+        if not self._macd.is_ready: return
+        bar = data.bars.get("IBM")
+        if not bar: return
+        if self._last_action.date() == self.time.date(): return
+
+        self._last_action = self.time
+        quantity = self.portfolio["SPY"].quantity
+
+        if quantity <= 0 and self._macd.current.value > self._macd.signal.current.value and bar.price > self._ema.current.value:
+            self.set_holdings("IBM", 0.25)
+        if quantity >= 0 and self._macd.current.value < self._macd.signal.current.value and bar.price < self._ema.current.value:
+            self.set_holdings("IBM", -0.25)