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 MacdAlphaModel(AlphaModel):
+    '''Defines a custom alpha model that uses MACD crossovers. The MACD signal line
+    is used to generate up/down insights if it's stronger than the bounce threshold.
+    If the MACD signal is within the bounce threshold then a flat price insight is returned.'''
+
+    def __init__(self,
+                 fastPeriod = 12,
+                 slowPeriod = 26,
+                 signalPeriod = 9,
+                 movingAverageType = MovingAverageType.Exponential,
+                 resolution = Resolution.Daily):
+        ''' Initializes a new instance of the MacdAlphaModel class
+        Args:
+            fastPeriod: The MACD fast period
+            slowPeriod: The MACD slow period</param>
+            signalPeriod: The smoothing period for the MACD signal
+            movingAverageType: The type of moving average to use in the MACD'''
+        self.fastPeriod = fastPeriod
+        self.slowPeriod = slowPeriod
+        self.signalPeriod = signalPeriod
+        self.movingAverageType = movingAverageType
+        self.resolution = resolution
+        self.insightPeriod = Time.Multiply(Extensions.ToTimeSpan(resolution), fastPeriod)
+        self.bounceThresholdPercent = 0.01
+        self.insightCollection = InsightCollection()
+        self.symbolData = {}
+
+        self.Name = '{}({},{},{},{},{})'.format(self.__class__.__name__, fastPeriod, slowPeriod, signalPeriod, movingAverageType, resolution)
+
+
+    def Update(self, algorithm, data):
+        ''' Determines an insight for each security based on it's current MACD signal
+        Args:
+            algorithm: The algorithm instance
+            data: The new data available
+        Returns:
+            The new insights generated'''
+        insights = []
+
+        for key, sd in self.symbolData.items():
+            if sd.Security.Price == 0:
+                continue
+
+            direction = InsightDirection.Flat
+            normalized_signal = sd.MACD.Signal.Current.Value / sd.Security.Price
+
+            if normalized_signal > self.bounceThresholdPercent:
+                direction = InsightDirection.Up
+            elif normalized_signal < -self.bounceThresholdPercent:
+                direction = InsightDirection.Down
+
+            # ignore signal for same direction as previous signal
+            if direction == sd.PreviousDirection:
+                continue
+
+            sd.PreviousDirection = direction
+
+            if direction == InsightDirection.Flat:
+                self.CancelInsights(algorithm, sd.Security.Symbol)
+                continue
+
+            insight = Insight.Price(sd.Security.Symbol, self.insightPeriod, direction)
+            insights.append(insight)
+            self.insightCollection.Add(insight)
+
+        return insights
+
+
+    def OnSecuritiesChanged(self, algorithm, changes):
+        '''Event fired each time the we add/remove securities from the data feed.
+        This initializes the MACD for each added security and cleans up the indicator for each removed security.
+        Args:
+            algorithm: The algorithm instance that experienced the change in securities
+            changes: The security additions and removals from the algorithm'''
+        for added in changes.AddedSecurities:
+            self.symbolData[added.Symbol] = SymbolData(algorithm, added, self.fastPeriod, self.slowPeriod, self.signalPeriod, self.movingAverageType, self.resolution)
+
+        for removed in changes.RemovedSecurities:
+            symbol = removed.Symbol
+
+            data = self.symbolData.pop(symbol, None)
+            if data is not None:
+                # clean up our consolidator
+                algorithm.SubscriptionManager.RemoveConsolidator(symbol, data.Consolidator)
+
+            # remove from insight collection manager
+            self.CancelInsights(algorithm, symbol)
+
+    def CancelInsights(self, algorithm, symbol):
+        if not self.insightCollection.ContainsKey(symbol):
+            return
+        insights = self.insightCollection[symbol]
+        algorithm.Insights.Cancel(insights)
+        self.insightCollection.Clear([ symbol ]);
+
+
+class SymbolData:
+    def __init__(self, algorithm, security, fastPeriod, slowPeriod, signalPeriod, movingAverageType, resolution):
+        self.Security = security
+        self.MACD = MovingAverageConvergenceDivergence(fastPeriod, slowPeriod, signalPeriod, movingAverageType)
+
+        self.Consolidator = algorithm.ResolveConsolidator(security.Symbol, resolution)
+        algorithm.RegisterIndicator(security.Symbol, self.MACD, self.Consolidator)
+        algorithm.WarmUpIndicator(security.Symbol, self.MACD, resolution)
+
+        self.PreviousDirection = None