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qlib/qlib/contrib/online/operator.py
2020-12-15 20:37:43 +08:00

318 lines
13 KiB
Python

# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import fire
import pandas as pd
import pathlib
import qlib
import logging
from ...data import D
from ...log import get_module_logger
from ...utils import get_pre_trading_date, is_tradable_date
from ..evaluate import risk_analysis
from ..backtest.backtest import update_account
from .manager import UserManager
from .utils import prepare
from .utils import create_user_folder
from .executor import load_order_list, save_order_list
from .executor import SimulatorExecutor
from .executor import save_score_series, load_score_series
class Operator:
def __init__(self, client: str):
"""
Parameters
----------
client: str
The qlib client config file(.yaml)
"""
self.logger = get_module_logger("online operator", level=logging.INFO)
self.client = client
@staticmethod
def init(client, path, date=None):
"""Initial UserManager(), get predict date and trade date
Parameters
----------
client: str
The qlib client config file(.yaml)
path : str
Path to save user account.
date : str (YYYY-MM-DD)
Trade date, when the generated order list will be traded.
Return
----------
um: UserManager()
pred_date: pd.Timestamp
trade_date: pd.Timestamp
"""
qlib.init_from_yaml_conf(client)
um = UserManager(user_data_path=pathlib.Path(path))
um.load_users()
if not date:
trade_date, pred_date = None, None
else:
trade_date = pd.Timestamp(date)
if not is_tradable_date(trade_date):
raise ValueError("trade date is not tradable date".format(trade_date.date()))
pred_date = get_pre_trading_date(trade_date, future=True)
return um, pred_date, trade_date
def add_user(self, id, config, path, date):
"""Add a new user into the a folder to run 'online' module.
Parameters
----------
id : str
User id, should be unique.
config : str
The file path (yaml) of user config
path : str
Path to save user account.
date : str (YYYY-MM-DD)
The date that user account was added.
"""
create_user_folder(path)
qlib.init_from_yaml_conf(self.client)
um = UserManager(user_data_path=path)
add_date = D.calendar(end_time=date)[-1]
if not is_tradable_date(add_date):
raise ValueError("add date is not tradable date".format(add_date.date()))
um.add_user(user_id=id, config_file=config, add_date=add_date)
def remove_user(self, id, path):
"""Remove user from folder used in 'online' module.
Parameters
----------
id : str
User id, should be unique.
path : str
Path to save user account.
"""
um = UserManager(user_data_path=path)
um.remove_user(user_id=id)
def generate(self, date, path):
"""Generate order list that will be traded at 'date'.
Parameters
----------
date : str (YYYY-MM-DD)
Trade date, when the generated order list will be traded.
path : str
Path to save user account.
"""
um, pred_date, trade_date = self.init(self.client, path, date)
for user_id, user in um.users.items():
dates, trade_exchange = prepare(um, pred_date, user_id)
# get and save the score at predict date
input_data = user.model.get_data_with_date(pred_date)
score_series = user.model.predict(input_data)
save_score_series(score_series, (pathlib.Path(path) / user_id), trade_date)
# update strategy (and model)
user.strategy.update(score_series, pred_date, trade_date)
# generate and save order list
order_list = user.strategy.generate_order_list(
score_series=score_series,
current=user.account.current,
trade_exchange=trade_exchange,
trade_date=trade_date,
)
save_order_list(
order_list=order_list,
user_path=(pathlib.Path(path) / user_id),
trade_date=trade_date,
)
self.logger.info("Generate order list at {} for {}".format(trade_date, user_id))
um.save_user_data(user_id)
def execute(self, date, exchange_config, path):
"""Execute the orderlist at 'date'.
Parameters
----------
date : str (YYYY-MM-DD)
Trade date, that the generated order list will be traded.
exchange_config: str
The file path (yaml) of exchange config
path : str
Path to save user account.
"""
um, pred_date, trade_date = self.init(self.client, path, date)
for user_id, user in um.users.items():
dates, trade_exchange = prepare(um, trade_date, user_id, exchange_config)
executor = SimulatorExecutor(trade_exchange=trade_exchange)
if not str(dates[0].date()) == str(pred_date.date()):
raise ValueError(
"The account data is not newest! last trading date {}, today {}".format(
dates[0].date(), trade_date.date()
)
)
# load and execute the order list
# will not modify the trade_account after executing
order_list = load_order_list(user_path=(pathlib.Path(path) / user_id), trade_date=trade_date)
trade_info = executor.execute(order_list=order_list, trade_account=user.account, trade_date=trade_date)
executor.save_executed_file_from_trade_info(
trade_info=trade_info,
user_path=(pathlib.Path(path) / user_id),
trade_date=trade_date,
)
self.logger.info("execute order list at {} for {}".format(trade_date.date(), user_id))
def update(self, date, path, type="SIM"):
"""Update account at 'date'.
Parameters
----------
date : str (YYYY-MM-DD)
Trade date, that the generated order list will be traded.
path : str
Path to save user account.
type : str
which executor was been used to execute the order list
'SIM': SimulatorExecutor()
"""
if type not in ["SIM", "YC"]:
raise ValueError("type is invalid, {}".format(type))
um, pred_date, trade_date = self.init(self.client, path, date)
for user_id, user in um.users.items():
dates, trade_exchange = prepare(um, trade_date, user_id)
if type == "SIM":
executor = SimulatorExecutor(trade_exchange=trade_exchange)
else:
raise ValueError("not found executor")
# dates[0] is the last_trading_date
if str(dates[0].date()) > str(pred_date.date()):
raise ValueError(
"The account data is not newest! last trading date {}, today {}".format(
dates[0].date(), trade_date.date()
)
)
# load trade info and update account
trade_info = executor.load_trade_info_from_executed_file(
user_path=(pathlib.Path(path) / user_id), trade_date=trade_date
)
score_series = load_score_series((pathlib.Path(path) / user_id), trade_date)
update_account(user.account, trade_info, trade_exchange, trade_date)
report = user.account.report.generate_report_dataframe()
self.logger.info(report)
um.save_user_data(user_id)
self.logger.info("Update account state {} for {}".format(trade_date, user_id))
def simulate(self, id, config, exchange_config, start, end, path, bench="SH000905"):
"""Run the ( generate_order_list -> execute_order_list -> update_account) process everyday
from start date to end date.
Parameters
----------
id : str
user id, need to be unique
config : str
The file path (yaml) of user config
exchange_config: str
The file path (yaml) of exchange config
start : str "YYYY-MM-DD"
The start date to run the online simulate
end : str "YYYY-MM-DD"
The end date to run the online simulate
path : str
Path to save user account.
bench : str
The benchmark that our result compared with.
'SH000905' for csi500, 'SH000300' for csi300
"""
# Clear the current user if exists, then add a new user.
create_user_folder(path)
um = self.init(self.client, path, None)[0]
start_date, end_date = pd.Timestamp(start), pd.Timestamp(end)
try:
um.remove_user(user_id=id)
except BaseException:
pass
um.add_user(user_id=id, config_file=config, add_date=pd.Timestamp(start_date))
# Do the online simulate
um.load_users()
user = um.users[id]
dates, trade_exchange = prepare(um, end_date, id, exchange_config)
executor = SimulatorExecutor(trade_exchange=trade_exchange)
for pred_date, trade_date in zip(dates[:-2], dates[1:-1]):
user_path = pathlib.Path(path) / id
# 1. load and save score_series
input_data = user.model.get_data_with_date(pred_date)
score_series = user.model.predict(input_data)
save_score_series(score_series, (pathlib.Path(path) / id), trade_date)
# 2. update strategy (and model)
user.strategy.update(score_series, pred_date, trade_date)
# 3. generate and save order list
order_list = user.strategy.generate_order_list(
score_series=score_series,
current=user.account.current,
trade_exchange=trade_exchange,
trade_date=trade_date,
)
save_order_list(order_list=order_list, user_path=user_path, trade_date=trade_date)
# 4. auto execute order list
order_list = load_order_list(user_path=user_path, trade_date=trade_date)
trade_info = executor.execute(trade_account=user.account, order_list=order_list, trade_date=trade_date)
executor.save_executed_file_from_trade_info(
trade_info=trade_info, user_path=user_path, trade_date=trade_date
)
# 5. update account state
trade_info = executor.load_trade_info_from_executed_file(user_path=user_path, trade_date=trade_date)
update_account(user.account, trade_info, trade_exchange, trade_date)
report = user.account.report.generate_report_dataframe()
self.logger.info(report)
um.save_user_data(id)
self.show(id, path, bench)
def show(self, id, path, bench="SH000905"):
"""show the newly report (mean, std, information_ratio, annualized_return)
Parameters
----------
id : str
user id, need to be unique
path : str
Path to save user account.
bench : str
The benchmark that our result compared with.
'SH000905' for csi500, 'SH000300' for csi300
"""
um = self.init(self.client, path, None)[0]
if id not in um.users:
raise ValueError("Cannot find user ".format(id))
bench = D.features([bench], ["$change"]).loc[bench, "$change"]
report = um.users[id].account.report.generate_report_dataframe()
report["bench"] = bench
analysis_result = {}
r = (report["return"] - report["bench"]).dropna()
analysis_result["excess_return_without_cost"] = risk_analysis(r)
r = (report["return"] - report["bench"] - report["cost"]).dropna()
analysis_result["excess_return_with_cost"] = risk_analysis(r)
print("Result:")
print("excess_return_without_cost:")
print(analysis_result["excess_return_without_cost"])
print("excess_return_with_cost:")
print(analysis_result["excess_return_with_cost"])
def run():
fire.Fire(Operator)
if __name__ == "__main__":
run()