chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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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 *
+
+from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
+from Execution.ImmediateExecutionModel import ImmediateExecutionModel
+from Selection.ManualUniverseSelectionModel import ManualUniverseSelectionModel
+
+### <summary>
+### Basic template framework algorithm uses framework components to define the algorithm.
+### Shows EqualWeightingPortfolioConstructionModel.long_only() application
+### </summary>
+### <meta name="tag" content="alpha streams" />
+### <meta name="tag" content="using quantconnect" />
+### <meta name="tag" content="algorithm framework" />
+class LongOnlyAlphaStreamAlgorithm(QCAlgorithm):
+
+    def initialize(self):
+        # 1. Required:
+        self.set_start_date(2013, 10, 7)
+        self.set_end_date(2013, 10, 11)
+
+        # 2. Required: Alpha Streams Models:
+        self.set_brokerage_model(BrokerageName.ALPHA_STREAMS)
+
+        # 3. Required: Significant AUM Capacity
+        self.set_cash(1000000)
+
+        # Only SPY will be traded
+        self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel(Resolution.DAILY, PortfolioBias.LONG))
+        self.set_execution(ImmediateExecutionModel())
+
+        # Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
+        # Commented so regression algorithm is more sensitive
+        #self.settings.minimum_order_margin_portfolio_percentage = 0.005
+
+        # Set algorithm framework models
+        self.set_universe_selection(ManualUniverseSelectionModel(
+            [Symbol.create(x, SecurityType.EQUITY, Market.USA) for x in ["SPY", "IBM"]]))
+
+    def on_data(self, slice):
+        if self.portfolio.invested: return
+
+        self.emit_insights(
+            [
+                Insight.price("SPY", timedelta(1), InsightDirection.UP),
+                Insight.price("IBM", timedelta(1), InsightDirection.DOWN)
+            ])
+
+    def on_order_event(self, order_event):
+        if order_event.status == OrderStatus.FILLED:
+            if self.securities[order_event.symbol].holdings.is_short:
+                raise ValueError("Invalid position, should not be short")
+            self.debug(order_event)