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update file strategy test

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Young
2021-10-03 05:31:43 +00:00
committed by you-n-g
parent 873129aa9b
commit 28fe4d4bb4
3 changed files with 39 additions and 23 deletions
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40
tests/backtest/test_file_strategy.py
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@@ -6,19 +6,20 @@ from qlib.backtest import backtest, decision
from qlib.tests import TestAutoData
import pandas as pd
from pathlib import Path
from qlib.data import D
import numpy as np
DIRNAME = Path(__file__).absolute().resolve().parent
class FileStrTest(TestAutoData):
# Assumption to ensure the correctness of the test
# - No price adjustment in these several trading days.
TEST_INST = "SH600519"
EXAMPLE_FILE = DIRNAME / "order_example.csv"
DEAL_NUM_FOR_1000 = 123.47105436976445
def _gen_orders(self) -> pd.DataFrame:
def _gen_orders(self, dealt_num_for_1000) -> pd.DataFrame:
headers = [
"datetime",
"instrument",
@@ -37,18 +38,29 @@ class FileStrTest(TestAutoData):
# test min_cost for selling
["20200109", self.TEST_INST, "1", "sell"],
# test selling all stocks
["20200110", self.TEST_INST, str(self.DEAL_NUM_FOR_1000), "sell"],
["20200110", self.TEST_INST, str(dealt_num_for_1000), "sell"],
]
return pd.DataFrame(orders, columns=headers).set_index(["datetime", "instrument"])
def test_file_str(self):
# 0) basic settings
account_money = 150000
orders = self._gen_orders()
# 1) get information
df = D.features([self.TEST_INST], ["$close", "$factor"], start_time="20200103", end_time="20200103")
price = df["$close"].item()
factor = df["$factor"].item()
price_unit = price / factor * 100
dealt_num_for_1000 = (account_money // price_unit) * (100 / factor)
# 2) generate orders
orders = self._gen_orders(dealt_num_for_1000)
print(orders)
orders.to_csv(self.EXAMPLE_FILE)
orders = pd.read_csv(self.EXAMPLE_FILE, index_col=["datetime", "instrument"])
# 3) run the strategy
strategy_config = {
"class": "FileOrderStrategy",
"module_path": "qlib.contrib.strategy.rule_strategy",
@@ -63,7 +75,7 @@ class FileStrTest(TestAutoData):
backtest_config = {
"start_time": start_time,
"end_time": end_time,
"account": 30000,
"account": account_money,
"benchmark": None, # benchmark is not required here for trading
"exchange_kwargs": {
"freq": freq,
@@ -73,7 +85,7 @@ class FileStrTest(TestAutoData):
"close_cost": 0.0015,
"min_cost": 500,
"codes": codes,
"trade_unit": 2,
"trade_unit": 100,
},
# "pos_type": "InfPosition" # Position with infinitive position
}
@@ -94,12 +106,12 @@ class FileStrTest(TestAutoData):
# ffr valid
ffr_dict = indicator_dict["1day"]["ffr"].to_dict()
ffr_dict = {str(date).split()[0]: ffr_dict[date] for date in ffr_dict}
assert ffr_dict["2020-01-03"] == self.DEAL_NUM_FOR_1000 / 1000
assert ffr_dict["2020-01-06"] == 0
assert ffr_dict["2020-01-07"] == self.DEAL_NUM_FOR_1000 / 1000
assert ffr_dict["2020-01-08"] == self.DEAL_NUM_FOR_1000 / 1000
assert ffr_dict["2020-01-09"] == 0
assert ffr_dict["2020-01-10"] == 1
assert np.isclose(ffr_dict["2020-01-03"], dealt_num_for_1000 / 1000)
assert np.isclose(ffr_dict["2020-01-06"], 0)
assert np.isclose(ffr_dict["2020-01-07"], dealt_num_for_1000 / 1000)
assert np.isclose(ffr_dict["2020-01-08"], dealt_num_for_1000 / 1000)
assert np.isclose(ffr_dict["2020-01-09"], 0)
assert np.isclose(ffr_dict["2020-01-10"], 1)
self.EXAMPLE_FILE.unlink()