modify backtest_daily's docstring

Author: zhupr

docs/component/strategy.rst

@@ -111,9 +111,18 @@ Usage & Example
 
 
         strategy_obj = TopkDropoutStrategy(**STRATEGY_CONFIG)
-        analysis_df = backtest_daily(
-            start_time="2017-01-01", end_time="2020-08-01", strategy=strategy_obj, executor=executor_obj
+        report_normal, positions_normal = backtest_daily(
+            start_time="2017-01-01", end_time="2020-08-01", strategy=strategy_obj
         )
+        analysis = dict()
+        analysis["excess_return_without_cost"] = risk_analysis(
+            report_normal["return"] - report_normal["bench"], freq=analysis_freq
+        )
+        analysis["excess_return_with_cost"] = risk_analysis(
+            report_normal["return"] - report_normal["bench"] - report_normal["cost"], freq=analysis_freq
+        )
+
+        analysis_df = pd.concat(analysis)  # type: pd.DataFrame
         pprint(analysis_df)
 
 

qlib/config.py

@@ -244,8 +244,8 @@ def set_conf_from_C(self, config_c):
 _default_region_config = {
     REG_CN: {
         "trade_unit": 100,
-        "limit_threshold": 0.099,
-        "deal_price": "vwap",
+        "limit_threshold": 0.095,
+        "deal_price": "close",
     },
     REG_US: {
         "trade_unit": 1,

qlib/contrib/evaluate.py

@@ -3,7 +3,6 @@
 
 from __future__ import division
 from __future__ import print_function
-from logging import warn
 
 import numpy as np
 import pandas as pd
@@ -130,7 +129,7 @@ def backtest_daily(
     benchmark: str = "SH000300",
     exchange_kwargs: dict = None,
     pos_type: str = "Position",
-) -> pd.DataFrame:
+):
     """initialize the strategy and executor, then executor the backtest of daily frequency
 
     Parameters
@@ -187,13 +186,28 @@ def backtest_daily(
             Using Account with a Position
     exchange_kwargs : dict
         the kwargs for initializing Exchange
+        E.g.
+
+        .. code-block:: python
+
+            exchange_kwargs = {
+                "freq": freq,
+                "limit_threshold": None, # limit_threshold is None, using C.limit_threshold
+                "deal_price": None, # deal_price is None, using C.deal_price
+                "open_cost": 0.0005,
+                "close_cost": 0.0015,
+                "min_cost": 5,
+            }
+
     pos_type : str
         the type of Position.
 
     Returns
     -------
-    analysis_df: pd.DataFrame
-        backtest results
+    report_normal: pd.DataFrame
+        backtest report
+    positions_normal: pd.DataFrame
+        backtest positions
 
     """
     freq = "day"
@@ -205,8 +219,8 @@ def backtest_daily(
         executor = _executor.SimulatorExecutor(**executor_config)
     _exchange_kwargs = {
         "freq": freq,
-        "limit_threshold": 0.095,
-        "deal_price": "close",
+        "limit_threshold": None,
+        "deal_price": None,
         "open_cost": 0.0005,
         "close_cost": 0.0015,
         "min_cost": 5,
@@ -227,16 +241,8 @@ def backtest_daily(
     analysis_freq = "{0}{1}".format(*Freq.parse(freq))
 
     report_normal, positions_normal = portfolio_metric_dict.get(analysis_freq)
-    analysis = dict()
-    analysis["excess_return_without_cost"] = risk_analysis(
-        report_normal["return"] - report_normal["bench"], freq=analysis_freq
-    )
-    analysis["excess_return_with_cost"] = risk_analysis(
-        report_normal["return"] - report_normal["bench"] - report_normal["cost"], freq=analysis_freq
-    )
 
-    analysis_df = pd.concat(analysis)  # type: pd.DataFrame
-    return analysis_df
+    return report_normal, positions_normal
 
 
 def long_short_backtest(
@@ -374,12 +380,7 @@ def t_run():
         "n_drop": 5,
         "signal": pred,
     }
-    portfolio_metric_dict, indicator_dict = backtest_daily(
-        start_time="2017-01-01", end_time="2020-08-01", strategy=strategy_config
-    )
-    freq = "day"
-    analysis_freq = "{0}{1}".format(*Freq.parse(freq))
-    report_df, positions = portfolio_metric_dict.get(analysis_freq)
+    report_df, positions = backtest_daily(start_time="2017-01-01", end_time="2020-08-01", strategy=strategy_config)
     print(report_df.head())
     print(positions.keys())
     print(positions[list(positions.keys())[0]])