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>
+### Regression algorithm for fractional forex pair
+### </summary>
+### <meta name="tag" content="using data" />
+### <meta name="tag" content="trading and orders" />
+### <meta name="tag" content="regression test" />
+class FractionalQuantityRegressionAlgorithm(QCAlgorithm):
+
+    def initialize(self):
+
+        self.set_start_date(2015, 11, 12)
+        self.set_end_date(2016, 4, 1)
+        self.set_cash(100000)
+        self.set_brokerage_model(BrokerageName.GDAX, AccountType.CASH)
+
+        self.set_time_zone(TimeZones.UTC)
+
+        security = self.add_security(SecurityType.CRYPTO, "BTCUSD", Resolution.DAILY, Market.GDAX, False, 1, True)
+
+        ### The default buying power model for the Crypto security type is now CashBuyingPowerModel.
+        ### Since this test algorithm uses leverage we need to set a buying power model with margin.
+        security.set_buying_power_model(SecurityMarginModel(3.3))
+
+        con = TradeBarConsolidator(1)
+        self.subscription_manager.add_consolidator("BTCUSD", con)
+        con.data_consolidated += self.data_consolidated
+        self.set_benchmark(security.symbol)
+
+    def data_consolidated(self, sender, bar):
+        quantity = math.floor((self.portfolio.cash + self.portfolio.total_fees) / abs(bar.value + 1))
+        btc_qnty = float(self.portfolio["BTCUSD"].quantity)
+
+        if not self.portfolio.invested:
+            self.order("BTCUSD", quantity)
+        elif btc_qnty == quantity:
+            self.order("BTCUSD", 0.1)
+        elif btc_qnty == quantity + 0.1:
+            self.order("BTCUSD", 0.01)
+        elif btc_qnty == quantity + 0.11:
+            self.order("BTCUSD", -0.02)
+        elif btc_qnty == quantity + 0.09:
+            # should fail (below minimum order quantity)
+            self.order("BTCUSD", 0.00001)
+            self.set_holdings("BTCUSD", -2.0)
+            self.set_holdings("BTCUSD", 2.0)
+            self.quit()