Add a example to collecting all the decisions

2026-07-06 12:30:57 +08:00 · 2021-08-15 15:22:48 +00:00
parent 735153a50d
commit 309dfa36cc
5 changed files with 245 additions and 16 deletions
--- a/tests/backtest/test_high_freq_trading.py
+++ b/tests/backtest/test_high_freq_trading.py
@@ -0,0 +1,133 @@
+from typing import List, Tuple, Union
+from qlib.backtest.position import Position
+from qlib.backtest import collect_data, format_decisions
+from qlib.backtest.order import BaseTradeDecision, TradeRangeByTime
+import qlib
+from qlib.tests import TestAutoData
+import unittest
+from qlib.config import REG_CN, HIGH_FREQ_CONFIG
+import pandas as pd
+
+
+@unittest.skip("This test takes a lot of time due to the large size of high-frequency data")
+class TestHFBacktest(TestAutoData):
+    @classmethod
+    def setUpClass(cls) -> None:
+        super().setUpClass(enable_1min=True, enable_1d_type="full")
+
+    def _gen_orders(self, inst, date, pos) -> pd.DataFrame:
+        headers = [
+            "datetime",
+            "instrument",
+            "amount",
+            "direction",
+        ]
+        orders = [
+            [date, inst, pos, "sell"],
+        ]
+        return pd.DataFrame(orders, columns=headers)
+
+    def test_trading(self):
+
+        # date = "2020-02-03"
+        # inst = "SH600068"
+        # pos = 2.0167
+        pos = 100000
+        inst, date = "SH600519", "2021-01-18"
+        market = [inst]
+
+        start_time = f"{date}"
+        end_time = f"{date} 15:00"  # include the high-freq data on the end day
+        freq_l0 = "day"
+        freq_l1 = "30min"
+        freq_l2 = "1min"
+
+        orders = self._gen_orders(inst=inst, date=date, pos=pos * 0.90)
+
+        strategy_config = {
+            "class": "FileOrderStrategy",
+            "module_path": "qlib.contrib.strategy.rule_strategy",
+            "kwargs": {
+                "trade_range": TradeRangeByTime("10:45", "14:44"),
+                "file": orders,
+            },
+        }
+        backtest_config = {
+            "start_time": start_time,
+            "end_time": end_time,
+            "account": {
+                "cash": 0,
+                inst: pos,
+            },
+            "benchmark": None,  # benchmark is not required here for trading
+            "exchange_kwargs": {
+                "freq": freq_l2,  # use the most fine-grained data as the exchange
+                "limit_threshold": 0.095,
+                "deal_price": "close",
+                "open_cost": 0.0005,
+                "close_cost": 0.0015,
+                "min_cost": 5,
+                "codes": market,
+                "trade_unit": 100,
+            },
+            # "pos_type": "InfPosition"  # Position with infinitive position
+        }
+        executor_config = {
+            "class": "NestedExecutor",  # Level 1 Order execution
+            "module_path": "qlib.backtest.executor",
+            "kwargs": {
+                "time_per_step": freq_l0,
+                "inner_executor": {
+                    "class": "NestedExecutor",  # Leve 2 Order Execution
+                    "module_path": "qlib.backtest.executor",
+                    "kwargs": {
+                        "time_per_step": freq_l1,
+                        "inner_executor": {
+                            "class": "SimulatorExecutor",
+                            "module_path": "qlib.backtest.executor",
+                            "kwargs": {
+                                "time_per_step": freq_l2,
+                                "generate_report": False,
+                                "verbose": True,
+                                "indicator_config": {
+                                    "show_indicator": False,
+                                },
+                                "track_data": True,
+                            },
+                        },
+                        "inner_strategy": {
+                            "class": "TWAPStrategy",
+                            "module_path": "qlib.contrib.strategy.rule_strategy",
+                        },
+                        "generate_report": False,
+                        "indicator_config": {
+                            "show_indicator": True,
+                        },
+                        "track_data": True,
+                    },
+                },
+                "inner_strategy": {
+                    "class": "TWAPStrategy",
+                    "module_path": "qlib.contrib.strategy.rule_strategy",
+                },
+                "generate_report": False,
+                "indicator_config": {
+                    "show_indicator": True,
+                },
+                "track_data": True,
+            },
+        }
+
+        ret_val = {}
+        decisions = list(
+            collect_data(executor=executor_config, strategy=strategy_config, **backtest_config, return_value=ret_val)
+        )
+        report, indicator = ret_val["report"], ret_val["indicator"]
+        # NOTE: please refer to the docs of format_decisions
+        # NOTE: `"track_data": True,`  is very NECESSARY for collecting the decision!!!!!
+        f_dec = format_decisions(decisions)
+        print(indicator["1day"])
+
+
+if __name__ == "__main__":
+    unittest.main()