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[BUGFIX] allow sell in limit-up case and allow buy in limit-down case in topk strategy (#1407)

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* 1) check limit_up/down should consider direction; 2) fix some typo, typehint etc

* fix error

* Update test_all_pipeline.py

Believe it's just some arbitrary number.
The excess return is expected to change when trading logic changes.

* add flag forbid_all_trade_at_limit to keep previous behivour for backward compatibility
This commit is contained in:
YQ Tsui
2023-01-10 09:46:18 +08:00
committed by GitHub
parent 7f08e6c7b3
commit d8764660dc
2 changed files with 36 additions and 16 deletions
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50
qlib/contrib/strategy/signal_strategy.py
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@@ -7,6 +7,7 @@ import numpy as np
import pandas as pd import pandas as pd
from typing import Dict, List, Text, Tuple, Union from typing import Dict, List, Text, Tuple, Union
from abc import ABC
from qlib.data import D from qlib.data import D
from qlib.data.dataset import Dataset from qlib.data.dataset import Dataset
@@ -17,11 +18,11 @@ from qlib.backtest.signal import Signal, create_signal_from
from qlib.backtest.decision import Order, OrderDir, TradeDecisionWO from qlib.backtest.decision import Order, OrderDir, TradeDecisionWO
from qlib.log import get_module_logger from qlib.log import get_module_logger
from qlib.utils import get_pre_trading_date, load_dataset from qlib.utils import get_pre_trading_date, load_dataset
from qlib.contrib.strategy.order_generator import OrderGenWOInteract from qlib.contrib.strategy.order_generator import OrderGenerator, OrderGenWOInteract
from qlib.contrib.strategy.optimizer import EnhancedIndexingOptimizer from qlib.contrib.strategy.optimizer import EnhancedIndexingOptimizer
class BaseSignalStrategy(BaseStrategy): class BaseSignalStrategy(BaseStrategy, ABC):
def __init__( def __init__(
self, self,
*, *,
@@ -47,7 +48,7 @@ class BaseSignalStrategy(BaseStrategy):
- If `trade_exchange` is None, self.trade_exchange will be set with common_infra - If `trade_exchange` is None, self.trade_exchange will be set with common_infra
- It allowes different trade_exchanges is used in different executions. - It allowes different trade_exchanges is used in different executions.
- For example: - For example:
- In daily execution, both daily exchange and minutely are usable, but the daily exchange is recommended because it run faster. - In daily execution, both daily exchange and minutely are usable, but the daily exchange is recommended because it runs faster.
- In minutely execution, the daily exchange is not usable, only the minutely exchange is recommended. - In minutely execution, the daily exchange is not usable, only the minutely exchange is recommended.
""" """
@@ -64,7 +65,7 @@ class BaseSignalStrategy(BaseStrategy):
def get_risk_degree(self, trade_step=None): def get_risk_degree(self, trade_step=None):
"""get_risk_degree """get_risk_degree
Return the proportion of your total value you will used in investment. Return the proportion of your total value you will use in investment.
Dynamically risk_degree will result in Market timing. Dynamically risk_degree will result in Market timing.
""" """
# It will use 95% amount of your total value by default # It will use 95% amount of your total value by default
@@ -76,6 +77,7 @@ class TopkDropoutStrategy(BaseSignalStrategy):
# 1. Supporting leverage the get_range_limit result from the decision # 1. Supporting leverage the get_range_limit result from the decision
# 2. Supporting alter_outer_trade_decision # 2. Supporting alter_outer_trade_decision
# 3. Supporting checking the availability of trade decision # 3. Supporting checking the availability of trade decision
# 4. Regenerate results with forbid_all_trade_at_limit set to false and flip the default to false, as it is consistent with reality.
def __init__( def __init__(
self, self,
*, *,
@@ -85,6 +87,7 @@ class TopkDropoutStrategy(BaseSignalStrategy):
method_buy="top", method_buy="top",
hold_thresh=1, hold_thresh=1,
only_tradable=False, only_tradable=False,
forbid_all_trade_at_limit=True,
**kwargs, **kwargs,
): ):
""" """
@@ -111,6 +114,17 @@ class TopkDropoutStrategy(BaseSignalStrategy):
else: else:
strategy will make buy sell decision without checking the tradable state of the stock. strategy will make buy sell decision without checking the tradable state of the stock.
forbid_all_trade_at_limit : bool
if forbid all trades when limit_up or limit_down reached.
if forbid_all_trade_at_limit:
strategy will not do any trade when price reaches limit up/down, even not sell at limit up nor buy at
limit down, though allowed in reality.
else:
strategy will sell at limit up and buy ad limit down.
""" """
super().__init__(**kwargs) super().__init__(**kwargs)
self.topk = topk self.topk = topk
@@ -119,6 +133,7 @@ class TopkDropoutStrategy(BaseSignalStrategy):
self.method_buy = method_buy self.method_buy = method_buy
self.hold_thresh = hold_thresh self.hold_thresh = hold_thresh
self.only_tradable = only_tradable self.only_tradable = only_tradable
self.forbid_all_trade_at_limit = forbid_all_trade_at_limit
def generate_trade_decision(self, execute_result=None): def generate_trade_decision(self, execute_result=None):
# get the number of trading step finished, trade_step can be [0, 1, 2, ..., trade_len - 1] # get the number of trading step finished, trade_step can be [0, 1, 2, ..., trade_len - 1]
@@ -161,7 +176,7 @@ class TopkDropoutStrategy(BaseSignalStrategy):
] ]
else: else:
# Otherwise, the stock will make decision with out the stock tradable info # Otherwise, the stock will make decision without the stock tradable info
def get_first_n(li, n): def get_first_n(li, n):
return list(li)[:n] return list(li)[:n]
@@ -171,7 +186,7 @@ class TopkDropoutStrategy(BaseSignalStrategy):
def filter_stock(li): def filter_stock(li):
return li return li
current_temp = copy.deepcopy(self.trade_position) current_temp: Position = copy.deepcopy(self.trade_position)
# generate order list for this adjust date # generate order list for this adjust date
sell_order_list = [] sell_order_list = []
buy_order_list = [] buy_order_list = []
@@ -216,7 +231,10 @@ class TopkDropoutStrategy(BaseSignalStrategy):
buy = today[: len(sell) + self.topk - len(last)] buy = today[: len(sell) + self.topk - len(last)]
for code in current_stock_list: for code in current_stock_list:
if not self.trade_exchange.is_stock_tradable( if not self.trade_exchange.is_stock_tradable(
stock_id=code, start_time=trade_start_time, end_time=trade_end_time stock_id=code,
start_time=trade_start_time,
end_time=trade_end_time,
direction=None if self.forbid_all_trade_at_limit else OrderDir.SELL,
): ):
continue continue
if code in sell: if code in sell:
@@ -244,7 +262,7 @@ class TopkDropoutStrategy(BaseSignalStrategy):
cash += trade_val - trade_cost cash += trade_val - trade_cost
# buy new stock # buy new stock
# note the current has been changed # note the current has been changed
current_stock_list = current_temp.get_stock_list() # current_stock_list = current_temp.get_stock_list()
value = cash * self.risk_degree / len(buy) if len(buy) > 0 else 0 value = cash * self.risk_degree / len(buy) if len(buy) > 0 else 0
# open_cost should be considered in the real trading environment, while the backtest in evaluate.py does not # open_cost should be considered in the real trading environment, while the backtest in evaluate.py does not
@@ -253,7 +271,10 @@ class TopkDropoutStrategy(BaseSignalStrategy):
for code in buy: for code in buy:
# check is stock suspended # check is stock suspended
if not self.trade_exchange.is_stock_tradable( if not self.trade_exchange.is_stock_tradable(
stock_id=code, start_time=trade_start_time, end_time=trade_end_time stock_id=code,
start_time=trade_start_time,
end_time=trade_end_time,
direction=None if self.forbid_all_trade_at_limit else OrderDir.BUY,
): ):
continue continue
# buy order # buy order
@@ -296,15 +317,15 @@ class WeightStrategyBase(BaseSignalStrategy):
- It allowes different trade_exchanges is used in different executions. - It allowes different trade_exchanges is used in different executions.
- For example: - For example:
- In daily execution, both daily exchange and minutely are usable, but the daily exchange is recommended because it run faster. - In daily execution, both daily exchange and minutely are usable, but the daily exchange is recommended because it runs faster.
- In minutely execution, the daily exchange is not usable, only the minutely exchange is recommended. - In minutely execution, the daily exchange is not usable, only the minutely exchange is recommended.
""" """
super().__init__(**kwargs) super().__init__(**kwargs)
if isinstance(order_generator_cls_or_obj, type): if isinstance(order_generator_cls_or_obj, type):
self.order_generator = order_generator_cls_or_obj() self.order_generator: OrderGenerator = order_generator_cls_or_obj()
else: else:
self.order_generator = order_generator_cls_or_obj self.order_generator: OrderGenerator = order_generator_cls_or_obj
def generate_target_weight_position(self, score, current, trade_start_time, trade_end_time): def generate_target_weight_position(self, score, current, trade_start_time, trade_end_time):
""" """
@@ -316,9 +337,8 @@ class WeightStrategyBase(BaseSignalStrategy):
pred score for this trade date, index is stock_id, contain 'score' column. pred score for this trade date, index is stock_id, contain 'score' column.
current : Position() current : Position()
current position. current position.
trade_exchange : Exchange() trade_start_time: pd.Timestamp
trade_date : pd.Timestamp trade_end_time: pd.Timestamp
trade date.
""" """
raise NotImplementedError() raise NotImplementedError()

2
tests/test_all_pipeline.py
View File

@@ -165,7 +165,7 @@ class TestAllFlow(TestAutoData):
analyze_df = backtest_analysis(TestAllFlow.PRED_SCORE, TestAllFlow.RID, self.URI_PATH) analyze_df = backtest_analysis(TestAllFlow.PRED_SCORE, TestAllFlow.RID, self.URI_PATH)
self.assertGreaterEqual( self.assertGreaterEqual(
analyze_df.loc(axis=0)["excess_return_with_cost", "annualized_return"].values[0], analyze_df.loc(axis=0)["excess_return_with_cost", "annualized_return"].values[0],
0.10, 0.05,
"backtest failed", "backtest failed",
) )
self.assertTrue(not analyze_df.isna().any().any(), "backtest failed") self.assertTrue(not analyze_df.isna().any().any(), "backtest failed")