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 *
+
+### <summary>
+### Algorithm demonstrating custom charting support in QuantConnect.
+### The entire charting system of quantconnect is adaptable. You can adjust it to draw whatever you'd like.
+### Charts can be stacked, or overlayed on each other. Series can be candles, lines or scatter plots.
+### Even the default behaviours of QuantConnect can be overridden.
+### </summary>
+### <meta name="tag" content="charting" />
+### <meta name="tag" content="adding charts" />
+### <meta name="tag" content="series types" />
+### <meta name="tag" content="plotting indicators" />
+class CustomChartingAlgorithm(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date(2016,1,1)
+        self.set_end_date(2017,1,1)
+        self.set_cash(100000)
+
+        spy = self.add_equity("SPY", Resolution.DAILY).symbol
+
+        # In your initialize method:
+        # Chart - Master Container for the Chart:
+        stock_plot = Chart("Trade Plot")
+        # On the Trade Plotter Chart we want 3 series: trades and price:
+        stock_plot.add_series(Series("Buy", SeriesType.SCATTER, 0))
+        stock_plot.add_series(Series("Sell", SeriesType.SCATTER, 0))
+        stock_plot.add_series(Series("Price", SeriesType.LINE, 0))
+        self.add_chart(stock_plot)
+
+        # On the Average Cross Chart we want 2 series, slow MA and fast MA
+        avg_cross = Chart("Average Cross")
+        avg_cross.add_series(Series("FastMA", SeriesType.LINE, 0))
+        avg_cross.add_series(Series("SlowMA", SeriesType.LINE, 0))
+        self.add_chart(avg_cross)
+
+        # There's support for candlestick charts built-in:
+        weekly_spy_plot = Chart("Weekly SPY")
+        spy_candlesticks = CandlestickSeries("SPY")
+        weekly_spy_plot.add_series(spy_candlesticks)
+        self.add_chart(weekly_spy_plot)
+
+        self.consolidate(spy, Calendar.WEEKLY, lambda bar: self.plot("Weekly SPY", "SPY", bar))
+
+        self.fast_ma = 0
+        self.slow_ma = 0
+        self.last_price = 0
+        self.resample = datetime.min
+        self.resample_period = (self.end_date - self.start_date) / 2000
+
+    def on_data(self, slice):
+        if slice["SPY"] is None: return
+
+        self.last_price = slice["SPY"].close
+        if self.fast_ma == 0: self.fast_ma = self.last_price
+        if self.slow_ma == 0: self.slow_ma = self.last_price
+        self.fast_ma = (0.01 * self.last_price) + (0.99 * self.fast_ma)
+        self.slow_ma = (0.001 * self.last_price) + (0.999 * self.slow_ma)
+
+
+        if self.time > self.resample:
+            self.resample = self.time  + self.resample_period
+            self.plot("Average Cross", "FastMA", self.fast_ma)
+            self.plot("Average Cross", "SlowMA", self.slow_ma)
+
+        # On the 5th days when not invested buy:
+        if not self.portfolio.invested and self.time.day % 13 == 0:
+        	self.order("SPY", (int)(self.portfolio.margin_remaining / self.last_price))
+        	self.plot("Trade Plot", "Buy", self.last_price)
+        elif self.time.day % 21 == 0 and self.portfolio.invested:
+            self.plot("Trade Plot", "Sell", self.last_price)
+            self.liquidate()
+
+    def on_end_of_day(self, symbol):
+       #Log the end of day prices:
+       self.plot("Trade Plot", "Price", self.last_price)