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>
+### Algorithm used for regression tests purposes
+### </summary>
+### <meta name="tag" content="regression test" />
+class RegressionAlgorithm(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(2013,10,7)   #Set Start Date
+        self.set_end_date(2013,10,8)    #Set End Date
+        self.set_cash(10000000)         #Set Strategy Cash
+        # Find more symbols here: http://quantconnect.com/data
+        self.add_equity("SPY", Resolution.TICK)
+        self.add_equity("BAC", Resolution.MINUTE)
+        self.add_equity("AIG", Resolution.HOUR)
+        self.add_equity("IBM", Resolution.DAILY)
+
+        self.__last_trade_ticks = self.start_date
+        self.__last_trade_trade_bars = self.__last_trade_ticks
+        self.__trade_every = timedelta(minutes=1)
+
+
+    def on_data(self, data):
+        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
+        if self.time - self.__last_trade_trade_bars < self.__trade_every:
+            return
+        self.__last_trade_trade_bars = self.time
+
+        for kvp in data.bars:
+            bar = kvp.Value
+            if bar.is_fill_forward:
+                continue
+
+            symbol = kvp.key
+            holdings = self.portfolio[symbol]
+
+            if not holdings.invested:
+                self.market_order(symbol, 10)
+            else:
+                self.market_order(symbol, -holdings.quantity)