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 *
+
+class IndicatorRibbonBenchmark(QCAlgorithm):
+
+    # Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+    def initialize(self):
+        self.set_start_date(2010, 1, 1)  #Set Start Date
+        self.set_end_date(2018, 1, 1)    #Set End Date
+        self._spy = self.add_equity("SPY", Resolution.MINUTE).symbol
+        count = 50
+        offset = 5
+        period = 15
+        self._ribbon = []
+        # define our sma as the base of the ribbon
+        self._sma = SimpleMovingAverage(period)
+        
+        for x in range(count):
+            # define our offset to the zero sma, these various offsets will create our 'displaced' ribbon
+            delay = Delay(offset*(x+1))
+            # define an indicator that takes the output of the sma and pipes it into our delay indicator
+            delayed_sma = IndicatorExtensions.of(delay, self._sma)
+            # register our new 'delayed_sma' for automatic updates on a daily resolution
+            self.register_indicator(self._spy, delayed_sma, Resolution.DAILY)
+            self._ribbon.append(delayed_sma)
+
+    def on_data(self, data):
+        # wait for our entire ribbon to be ready
+        if not all(x.is_ready for x in self._ribbon): return
+        for x in self._ribbon:
+            value = x.current.value