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>
+### Basic algorithm demonstrating how to place stop limit orders.
+### </summary>
+### <meta name="tag" content="trading and orders" />
+### <meta name="tag" content="placing orders" />
+### <meta name="tag" content="stop limit order"/>
+class StopLimitOrderRegressionAlgorithm(QCAlgorithm):
+    '''Basic algorithm demonstrating how to place stop limit orders.'''
+
+    tolerance = 0.001
+    fast_period = 30
+    slow_period = 60
+    asynchronous_orders = False
+
+    def initialize(self):
+        self.set_start_date(2013, 1, 1)
+        self.set_end_date(2017, 1, 1)
+        self.set_cash(100000)
+
+        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
+
+        self._fast = self.ema(self._symbol, self.fast_period, Resolution.DAILY)
+        self._slow = self.ema(self._symbol, self.slow_period, Resolution.DAILY)
+
+        self._buy_order_ticket: OrderTicket = None
+        self._sell_order_ticket: OrderTicket = None
+        self._previous_slice: Slice = None
+
+    def on_data(self, slice: Slice):
+        if not self.is_ready():
+            return
+
+        security = self.securities[self._symbol]
+        if self._buy_order_ticket is None and self.trend_is_up():
+            self._buy_order_ticket = self.stop_limit_order(self._symbol, 100, stop_price=security.high * 1.10, limit_price=security.high * 1.11, asynchronous=self.asynchronous_orders)
+        elif self._buy_order_ticket.status == OrderStatus.FILLED and self._sell_order_ticket is None and self.trend_is_down():
+            self._sell_order_ticket = self.stop_limit_order(self._symbol, -100, stop_price=security.low * 0.99, limit_price=security.low * 0.98, asynchronous=self.asynchronous_orders)
+
+    def on_order_event(self, order_event: OrderEvent):
+        if order_event.status == OrderStatus.FILLED:
+            order = self.transactions.get_order_by_id(order_event.order_id)
+            if not order.stop_triggered:
+                raise AssertionError("StopLimitOrder StopTriggered should haven been set if the order filled.")
+
+            if order_event.direction == OrderDirection.BUY:
+                limit_price = self._buy_order_ticket.get(OrderField.LIMIT_PRICE)
+                if order_event.fill_price > limit_price:
+                    raise AssertionError(f"Buy stop limit order should have filled with price less than or equal to the limit price {limit_price}. "
+                                    f"Fill price: {order_event.fill_price}")
+            else:
+                limit_price = self._sell_order_ticket.get(OrderField.LIMIT_PRICE)
+                if order_event.fill_price < limit_price:
+                    raise AssertionError(f"Sell stop limit order should have filled with price greater than or equal to the limit price {limit_price}. "
+                                    f"Fill price: {order_event.fill_price}")
+
+    def on_end_of_algorithm(self):
+        for ticket in self.transactions.get_order_tickets():
+            if ticket.submit_request.asynchronous != self.asynchronous_orders:
+                raise AssertionError("Expected all orders to have the same asynchronous flag as the algorithm.")
+
+    def is_ready(self):
+        return self._fast.is_ready and self._slow.is_ready
+
+    def trend_is_up(self):
+        return self.is_ready() and self._fast.current.value > self._slow.current.value * (1 + self.tolerance)
+
+    def trend_is_down(self):
+        return self.is_ready() and self._fast.current.value < self._slow.current.value * (1 + self.tolerance)