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 System.Collections.Generic import Dictionary
+
+### <summary>
+### Demonstration of how to access the statistics results from within an algorithm through the `Statistics` property.
+### </summary>
+class StatisticsResultsAlgorithm(QCAlgorithm):
+
+    most_traded_security_statistic = "Most Traded Security"
+    most_traded_security_trade_count_statistic = "Most Traded Security Trade Count"
+
+    def initialize(self):
+        self.set_start_date(2013, 10, 7)
+        self.set_end_date(2013, 10, 11)
+        self.set_cash(100000)
+
+        self.spy = self.add_equity("SPY", Resolution.MINUTE).symbol
+        self.ibm = self.add_equity("IBM", Resolution.MINUTE).symbol
+
+        self.fast_spy_ema = self.ema(self.spy, 30, Resolution.MINUTE)
+        self.slow_spy_ema = self.ema(self.spy, 60, Resolution.MINUTE)
+
+        self.fast_ibm_ema = self.ema(self.spy, 10, Resolution.MINUTE)
+        self.slow_ibm_ema = self.ema(self.spy, 30, Resolution.MINUTE)
+
+        self.trade_counts = {self.spy: 0, self.ibm: 0}
+
+    def on_data(self, data: Slice):
+        if not self.slow_spy_ema.is_ready: return
+
+        if self.fast_spy_ema > self.slow_spy_ema:
+            self.set_holdings(self.spy, 0.5)
+        elif self.securities[self.spy].invested:
+            self.liquidate(self.spy)
+
+        if self.fast_ibm_ema > self.slow_ibm_ema:
+            self.set_holdings(self.ibm, 0.2)
+        elif self.securities[self.ibm].invested:
+            self.liquidate(self.ibm)
+
+    def on_order_event(self, order_event):
+        if order_event.status == OrderStatus.FILLED:
+            # We can access the statistics summary at runtime
+            statistics = self.statistics.summary
+            statistics_str = "".join([f"{kvp.key}: {kvp.value}" for kvp in statistics])
+            self.debug(f"Statistics after fill:{statistics_str}")
+
+            # Access a single statistic
+            self.log(f"Total trades so far: {statistics[PerformanceMetrics.TOTAL_ORDERS]}")
+            self.log(f"Sharpe Ratio: {statistics[PerformanceMetrics.SHARPE_RATIO]}")
+
+            # --------
+
+            # We can also set custom summary statistics:
+
+            if all(count == 0 for count in self.trade_counts.values()):
+                if StatisticsResultsAlgorithm.most_traded_security_statistic in statistics:
+                    raise AssertionError(f"Statistic {StatisticsResultsAlgorithm.most_traded_security_statistic} should not be set yet")
+                if StatisticsResultsAlgorithm.most_traded_security_trade_count_statistic in statistics:
+                    raise AssertionError(f"Statistic {StatisticsResultsAlgorithm.most_traded_security_trade_count_statistic} should not be set yet")
+            else:
+                # The current most traded security should be set in the summary
+                most_trade_security, most_trade_security_trade_count = self.get_most_trade_security()
+                self.check_most_traded_security_statistic(statistics, most_trade_security, most_trade_security_trade_count)
+
+            # Update the trade count
+            self.trade_counts[order_event.symbol] += 1
+
+            # Set the most traded security
+            most_trade_security, most_trade_security_trade_count = self.get_most_trade_security()
+            self.set_summary_statistic(StatisticsResultsAlgorithm.most_traded_security_statistic, str(most_trade_security))
+            self.set_summary_statistic(StatisticsResultsAlgorithm.most_traded_security_trade_count_statistic, most_trade_security_trade_count)
+
+            # Re-calculate statistics:
+            statistics = self.statistics.summary
+
+            # Let's keep track of our custom summary statistics after the update
+            self.check_most_traded_security_statistic(statistics, most_trade_security, most_trade_security_trade_count)
+
+    def on_end_of_algorithm(self):
+        statistics = self.statistics.summary
+        if StatisticsResultsAlgorithm.most_traded_security_statistic not in statistics:
+            raise AssertionError(f"Statistic {StatisticsResultsAlgorithm.most_traded_security_statistic} should be in the summary statistics")
+        if StatisticsResultsAlgorithm.most_traded_security_trade_count_statistic not in statistics:
+            raise AssertionError(f"Statistic {StatisticsResultsAlgorithm.most_traded_security_trade_count_statistic} should be in the summary statistics")
+
+        most_trade_security, most_trade_security_trade_count = self.get_most_trade_security()
+        self.check_most_traded_security_statistic(statistics, most_trade_security, most_trade_security_trade_count)
+
+    def check_most_traded_security_statistic(self, statistics: Dictionary[str, str], most_traded_security: Symbol, trade_count: int):
+        most_traded_security_statistic = statistics[StatisticsResultsAlgorithm.most_traded_security_statistic]
+        most_traded_security_trade_count_statistic = statistics[StatisticsResultsAlgorithm.most_traded_security_trade_count_statistic]
+        self.log(f"Most traded security: {most_traded_security_statistic}")
+        self.log(f"Most traded security trade count: {most_traded_security_trade_count_statistic}")
+
+        if most_traded_security_statistic != most_traded_security:
+            raise AssertionError(f"Most traded security should be {most_traded_security} but it is {most_traded_security_statistic}")
+
+        if most_traded_security_trade_count_statistic != str(trade_count):
+            raise AssertionError(f"Most traded security trade count should be {trade_count} but it is {most_traded_security_trade_count_statistic}")
+
+    def get_most_trade_security(self) -> tuple[Symbol, int]:
+        most_trade_security = max(self.trade_counts, key=lambda symbol: self.trade_counts[symbol])
+        most_trade_security_trade_count = self.trade_counts[most_trade_security]
+        return most_trade_security, most_trade_security_trade_count
+