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>
+### Simple indicator demonstration algorithm of MACD
+### </summary>
+### <meta name="tag" content="indicators" />
+### <meta name="tag" content="indicator classes" />
+### <meta name="tag" content="plotting indicators" />
+class MACDTrendAlgorithm(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(2004, 1, 1)    #Set Start Date
+        self.set_end_date(2015, 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)
+
+        # define our daily macd(12,26) with a 9 day signal
+        self.__macd = self.macd("SPY", 12, 26, 9, MovingAverageType.EXPONENTIAL, Resolution.DAILY)
+        self.__previous = datetime.min
+        self.plot_indicator("MACD", True, self.__macd, self.__macd.signal)
+        self.plot_indicator("SPY", self.__macd.fast, self.__macd.slow)
+
+
+    def on_data(self, data):
+        '''on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
+        # wait for our macd to fully initialize
+        if not self.__macd.is_ready: return
+
+        # only once per day
+        if self.__previous.date() == self.time.date(): return
+
+        # define a small tolerance on our checks to avoid bouncing
+        tolerance = 0.0025
+
+        holdings = self.portfolio["SPY"].quantity
+
+        signal_delta_percent = (self.__macd.current.value - self.__macd.signal.current.value)/self.__macd.fast.current.value
+
+        # if our macd is greater than our signal, then let's go long
+        if holdings <= 0 and signal_delta_percent > tolerance:  # 0.01%
+            # longterm says buy as well
+            self.set_holdings("SPY", 1.0)
+
+        # of our macd is less than our signal, then let's go short
+        elif holdings >= 0 and signal_delta_percent < -tolerance:
+            self.liquidate("SPY")
+
+
+        self.__previous = self.time