def __QA_backtest_prepare(self):
"""
这是模型内部的 初始化,主要是初始化一些账户和市场资产
写成了私有函数
@yutiansut
2017/7/20
"""
if len(str(self.strategy_start_date))==10:
self.strategy_start_time=str(self.strategy_start_date)+' 15:00:00'
elif len(str(self.strategy_start_date))==19:
self.strategy_start_time=str(self.strategy_start_date)
self.strategy_start_date=str(self.strategy_start_date)[0:10]
else:
QA_util_log_info('Wrong start date format')
if len(str(self.strategy_end_date))==10:
self.strategy_end_time=str(self.strategy_end_date)+' 15:00:00'
elif len(str(self.strategy_end_date))==19:
self.strategy_end_time=str(self.strategy_end_date)
self.strategy_end_date=str(self.strategy_end_date)[0:10]
else:
QA_util_log_info('Wrong end date format')
# 重新初始账户资产
self.market = QA_Market(self.commission_fee_coeff)
self.setting.QA_setting_init()
self.account.init()
self.start_real_date = QA_util_get_real_date(
self.strategy_start_date, self.trade_list, 1)
self.start_real_time=str(self.start_real_date)+' '+self.strategy_start_time.split(' ')[1]
self.start_real_id = self.trade_list.index(self.start_real_date)
self.end_real_date = QA_util_get_real_date(
self.strategy_end_date, self.trade_list, -1)
self.end_real_id = self.trade_list.index(self.end_real_date)
self.end_real_time=str(self.end_real_date)+' '+self.strategy_end_time.split(' ')[1]
# 重新初始化账户的cookie
self.account.account_cookie = str(random.random())
# 初始化股票池的市场数据
if self.benchmark_type in ['I','index']:
self.benchmark_data = QA_fetch_index_day_adv(
self.benchmark_code, self.start_real_date, self.end_real_date)
elif self.benchmark_type in ['S','stock']:
self.benchmark_data = QA_fetch_stock_day_adv(
self.benchmark_code, self.start_real_date, self.end_real_date)
if self.backtest_type in ['day', 'd', '0x00']:
self.market_data = QA_fetch_stocklist_day_adv(
self.strategy_stock_list, self.trade_list[self.start_real_id - int(
self.strategy_gap+1)], self.trade_list[self.end_real_id]).to_qfq()
elif self.backtest_type in ['1min', '5min', '15min', '30min', '60min']:
self.market_data = QA_fetch_stocklist_min_adv(
self.strategy_stock_list, QA_util_time_gap(self.start_real_time,self.strategy_gap+1,'<',self.backtest_type),
QA_util_time_gap(self.end_real_time,1,'>',self.backtest_type), self.backtest_type).to_qfq()
elif self.backtest_type in ['index_day']:
self.market_data = QA_fetch_index_day_adv(self.strategy_stock_list, self.trade_list[self.start_real_id - int(
self.strategy_gap+1)], self.end_real_date)
elif self.backtest_type in ['index_1min', 'index_5min', 'index_15min', 'index_30min', 'index_60min']:
self.market_data = QA_fetch_index_min_adv(
self.strategy_stock_list, QA_util_time_gap(self.start_real_time,self.strategy_gap+1,'<',self.backtest_type.split('_')[1]), QA_util_time_gap(self.end_real_time,1,'>',self.backtest_type.split('_')[1]), self.backtest_type.split('_')[1])
def __QA_backtest_init_class(self):
"""
这是模型内部的 初始化,主要是初始化一些账户和市场资产
写成了私有函数
@yutiansut
2017/7/20
"""
# 重新初始账户资产
self.setting.QA_setting_init()
self.account.init()
self.start_real_date = QA_util_get_real_date(self.strategy_start_date,
self.trade_list, 1)
self.start_real_id = self.trade_list.index(self.start_real_date)
self.end_real_date = QA_util_get_real_date(self.strategy_end_date,
self.trade_list, -1)
self.end_real_id = self.trade_list.index(self.end_real_date)
# 重新初始化账户的cookie
self.account.account_cookie = str(random.random())
# 初始化股票池的市场数据
self.market_data = QA_fetch_stocklist_day(
self.strategy_stock_list, self.setting.client.quantaxis.stock_day,
[
self.trade_list[self.start_real_id - int(self.strategy_gap)],
self.trade_list[self.end_real_id]
])
def now_time():
return str(
QA_util_get_real_date(
str(datetime.date.today() -
datetime.timedelta(days=1)), trade_date_sse,
-1)) + ' 15:00:00' if datetime.datetime.now().hour < 15 else str(
QA_util_get_real_date(str(datetime.date.today()),
trade_date_sse, -1)) + ' 15:00:00'
def now_time():
real_date = str(QA_util_get_real_date(str(datetime.date.today() -
datetime.timedelta(days=1)),
trade_date_sse, -1))
str_now = real_date + ' 17:00:00' if datetime.datetime.now().hour < 15 \
else str(QA_util_get_real_date(str(datetime.date.today()),
trade_date_sse, -1)) + ' 15:00:00'
return date_conver_to_new_format(str_now)
def __QA_backtest_prepare(self):
"""
这是模型内部的 初始化,主要是初始化一些账户和市场资产
写成了私有函数
@yutiansut
2017/7/20
"""
# 重新初始账户资产
self.market = QA_Market(self.commission_fee_coeff)
self.setting.QA_setting_init()
self.account.init()
self.start_real_date = QA_util_get_real_date(self.strategy_start_date,
self.trade_list, 1)
self.start_real_id = self.trade_list.index(self.start_real_date)
self.end_real_date = QA_util_get_real_date(self.strategy_end_date,
self.trade_list, -1)
self.end_real_id = self.trade_list.index(self.end_real_date)
# 重新初始化账户的cookie
self.account.account_cookie = str(random.random())
# 初始化股票池的市场数据
self.benchmark_data = QA_fetch_index_day_adv(self.benchmark_code,
self.start_real_date,
self.end_real_date)
if self.backtest_type in ['day', 'd', '0x00']:
self.market_data = QA_fetch_stocklist_day_adv(
self.strategy_stock_list,
self.trade_list[self.start_real_id - int(self.strategy_gap)],
self.trade_list[self.end_real_id]).to_qfq()
elif self.backtest_type in ['1min', '5min', '15min', '30min', '60min']:
self.market_data = QA_fetch_stocklist_min_adv(
self.strategy_stock_list,
self.trade_list[self.start_real_id - int(self.strategy_gap)],
self.trade_list[self.end_real_id + 1],
self.backtest_type).to_qfq()
elif self.backtest_type in ['index_day']:
self.market_data = QA_fetch_index_day_adv(
self.strategy_stock_list,
self.trade_list[self.start_real_id - int(self.strategy_gap)],
self.trade_list[self.end_real_id])
elif self.backtest_type in [
'index_1min', 'index_5min', 'index_15min', 'index_30min',
'index_60min'
]:
self.market_data = QA_fetch_index_min_adv(
self.strategy_stock_list, self.start_real_date,
self.end_real_date,
self.backtest_type.split('_')[1])
def QA_backtest_init(self):
# 设置回测的开始结束时间
try:
self.QA_backtest_import_setting()
except:
sys.exit()
self.strategy_start_date = str(
self.__backtest_setting['backtest']['strategy_start_date'])
self.strategy_end_date = str(
self.__backtest_setting['backtest']['strategy_end_date'])
# 设置回测标的,是一个list对象,不过建议只用一个标的
# gap是回测时,每日获取数据的前推日期(交易日)
self.strategy_gap = int(
self.__backtest_setting['backtest']['strategy_gap'])
# 设置全局的数据库地址,回测用户名,密码,并初始化
self.setting.QA_util_sql_mongo_ip = str(
self.__backtest_setting['backtest']['database_ip'])
self.setting.QA_setting_user_name = str(
self.__backtest_setting['backtest']['username'])
self.setting.QA_setting_user_password = str(
self.__backtest_setting['backtest']['password'])
self.setting.QA_setting_init()
# 回测的名字
self.strategy_name = str(
self.__backtest_setting['backtest']['strategy_name'])
# 股票的交易日历,真实回测的交易周期,和交易周期在交易日历中的id
self.trade_list = QA_fetch_trade_date(
self.setting.client.quantaxis.trade_date)
self.benchmark_code = self.__backtest_setting['backtest'][
'benchmark_code']
"""
这里会涉及一个区间的问题,开始时间是要向后推,而结束时间是要向前推,1代表向后推,-1代表向前推
"""
self.start_real_date = QA_util_get_real_date(self.strategy_start_date,
self.trade_list, 1)
self.start_real_id = self.trade_list.index(self.start_real_date)
self.end_real_date = QA_util_get_real_date(self.strategy_end_date,
self.trade_list, -1)
self.end_real_id = self.trade_list.index(self.end_real_date)
self.__QA_backtest_set_stock_list()
self.account.init_assest = self.__backtest_setting['account'][
'account_assets']
def now_time():
"""
1. 当前日期如果是交易日且当前时间在 17:00 之前，默认行情取到上个交易日收盘
2. 当前日期如果是交易日且当前时间在 17:00 之后，默认行情取到当前交易日收盘
"""
return (str(
QA_util_get_real_date(
str(datetime.date.today() - datetime.timedelta(days=1)),
trade_date_sse,
-1,
)) + " 17:00:00"
if datetime.datetime.now().hour < TRADE_HOUR_END else str(
QA_util_get_real_date(str(datetime.date.today()),
trade_date_sse, -1)) + " 17:00:00")
def QA_fetch_get_index_day(code,
start_date,
end_date,
ip='119.147.212.81',
port=7709):
api = TdxHq_API()
start_date = QA_util_get_real_date(start_date, trade_date_sse, 1)
end_date = QA_util_get_real_date(end_date, trade_date_sse, -1)
with api.connect(ip, port):
data = []
for i in range(10):
data += api.get_index_bars(9, 1, code, (9 - i) * 800, 800)
data = api.to_df(data)
data['date'] = data['datetime'].apply(lambda x: x[0:10])
data['date'] = pd.to_datetime(data['date'])
data = data.set_index('date', drop=False)
data = data.drop(
['year', 'month', 'day', 'hour', 'minute', 'datetime'], axis=1)
return data[start_date:end_date]
def get_stock_industry(self, code, start, end):
codex = []
if isinstance(code, list):
pass
else:
code = [code]
start = QA_util_get_real_date(start)
end = QA_util_get_real_date(end)
for coder in code:
if '.' in coder:
codex.append(coder)
else:
codex.append(coder + '.XSHG' if coder[0] == '6' else coder +
'.XSHE')
res = self.execute(
"SELECT * FROM quantaxis.citis_industry WHERE ((`date` >= '{}')) AND (`date` <= '{}') AND (`order_book_id` IN ({}))"
.format(start, end, "'{}'".format(
"','".join(codex)))).drop_duplicates(['date', 'order_book_id'])
return res
def QA_backtest_init(self):
"""既然是被当做装饰器使用,就需要把变量设置放在装饰函数的前面,把函数放在装饰函数的后面"""
# 设置回测的开始结束时间
self.strategy_start_date = str('2017-01-05')
self.strategy_end_date = str('2017-07-01')
# 设置回测标的,是一个list对象,不过建议只用一个标的
# gap是回测时,每日获取数据的前推日期(交易日)
self.strategy_gap = int(60)
# 设置全局的数据库地址,回测用户名,密码,并初始化
self.setting.QA_util_sql_mongo_ip = str('127.0.0.1')
self.setting.QA_setting_user_name = str('admin')
self.setting.QA_setting_user_password = str('admin')
self.setting.QA_setting_init()
# 回测的名字
self.strategy_name = str('example')
# 股票的交易日历,真实回测的交易周期,和交易周期在交易日历中的id
self.trade_list = QA_fetch_trade_date(
self.setting.client.quantaxis.trade_date)
self.benchmark_code = 'hs300'
"""
这里会涉及一个区间的问题,开始时间是要向后推,而结束时间是要向前推,1代表向后推,-1代表向前推
"""
self.start_real_date = QA_util_get_real_date(self.strategy_start_date,
self.trade_list, 1)
self.start_real_id = self.trade_list.index(self.start_real_date)
self.end_real_date = QA_util_get_real_date(self.strategy_end_date,
self.trade_list, -1)
self.end_real_id = self.trade_list.index(self.end_real_date)
self.strategy_stock_list = ['000001', '000002', '000004']
self.account.init_assest = 1000000
self.backtest_bid_model = 'market_price'
def QA_fetch_get_stock_day(code, start_date,end_date,ip='119.147.212.81',port=7709):
if str(code)[0]=='6':
#0 - 深圳， 1 - 上海
market_code=1
else:
market_code=0
start_date=QA_util_get_real_date(start_date,trade_date_sse,1)
end_date=QA_util_get_real_date(end_date,trade_date_sse,-1)
with api.connect(ip, port):
# 判断end_date在哪个位置
index_0=str(datetime.date.today())
index_of_index_0=trade_date_sse.index(index_0)
index_of_index_end=trade_date_sse.index(end_date)
index_of_index_start=trade_date_sse.index(start_date)
index_of_end=index_of_index_0-index_of_index_end
index_length=index_of_index_end+1-index_of_index_start
#data = api.get_security_bars(9, market_code, code,index_of_end, index_length) # 返回普通list
data = api.to_df(api.get_security_bars(9, market_code, code,index_of_end, index_length)) # 返回DataFrame
return data
def QA_fetch_get_stock_day(code, start_date,end_date,ip='119.147.212.81',port=7709):
api = TdxHq_API()
if str(code)[0]=='6':
#0 - 深圳， 1 - 上海
market_code=1
else:
market_code=0
start_date=QA_util_get_real_date(start_date,trade_date_sse,1)
end_date=QA_util_get_real_date(end_date,trade_date_sse,-1)
with api.connect(ip, port):
data=[]
for i in range(10):
data+=api.get_security_bars(9,market_code,code,(9-i)*800,800)
data=api.to_df(data)
data['date']=data['datetime'].apply(lambda x:x[0:10])
data['date']=pd.to_datetime(data['date'])
data = data.set_index('date')
data = data.drop(['year','month','day','hour','minute','datetime'],axis=1)
return data[start_date:end_date]
def __QA_backtest_prepare(self):
"""
这是模型内部的 初始化,主要是初始化一些账户和市场资产
写成了私有函数
@yutiansut
2017/7/20
"""
# 重新初始账户资产
self.setting.QA_setting_init()
self.account.init()
self.start_real_date = QA_util_get_real_date(self.strategy_start_date,
self.trade_list, 1)
self.start_real_id = self.trade_list.index(self.start_real_date)
self.end_real_date = QA_util_get_real_date(self.strategy_end_date,
self.trade_list, -1)
self.end_real_id = self.trade_list.index(self.end_real_date)
# 重新初始化账户的cookie
self.account.account_cookie = str(random.random())
# 初始化股票池的市场数据
if self.backtest_type in ['day', 'd', '0x00']:
self.market_data = QA_fetch_stocklist_day(
self.strategy_stock_list, [
self.trade_list[self.start_real_id -
int(self.strategy_gap)],
self.trade_list[self.end_real_id]
])
elif self.backtest_type in ['min', 'm', '0x01']:
self.market_data = QA_fetch_stocklist_min(
self.strategy_stock_list, [
self.trade_list[self.start_real_id -
int(self.strategy_gap)],
self.trade_list[self.end_real_id]
])
def get_index_weight(self, code, start, end):
codex = []
if isinstance(code, list):
pass
else:
code = [code]
start = QA_util_get_real_date(start)
end = QA_util_get_real_date(end)
start = start[0:8] + '01'
end = end[0:8] + '01'
for coder in code:
if '.' in coder:
codex.append(coder)
else:
codex.append(coder + '.XSHE' if coder[0] == '6' else coder +
'.XSHG')
res = self.execute(
"SELECT * FROM quantaxis.index_weight WHERE ((`date` >= '{}')) AND (`date` <= '{}') AND (`index_code` IN ({}))"
.format(start, end, "'{}'".format(
"','".join(codex)))).drop_duplicates(['date', 'order_book_id'])
return res
#%%
data = QA.QAFetch.QATdx.QA_fetch_get_stock_transaction('000001','2015-06-05','2015-06-06')
data.index = pd.to_datetime(data.index)
type(data.index[0])('2019-01-01')
#%%
data = QA.QAFetch.QATdx.QA_fetch_get_future_list()
data['signal'] = data['code'].apply(lambda x:x[-2:])
data[data['signal'].isin(['L8','L9'])]
1300/8200
assert False
STOCK_DAY = (['code', 'open', 'high', 'low','close', 'volume', 'amount', 'date'],'date')
['code','open'] in
from QUANTAXIS.QAUtil import (DATABASE, QA_Setting, QA_util_date_stamp,
QA_util_date_valid, QA_util_dict_remove_key,
QA_util_log_info, QA_util_code_tostr, QA_util_date_str2int, QA_util_date_int2str,
QA_util_sql_mongo_sort_DESCENDING,
QA_util_time_stamp, QA_util_to_json_from_pandas,
trade_date_sse,QA_util_dateordatetime_valid,QA_util_to_anyformat_from_pandas,
QA_util_get_last_day,QA_util_get_next_day,QA_util_get_real_date)
QA_util_time_stamp('2016-01-01 09:00:00')
QA_util_time_stamp('2016-01-01')
QA_util_time_stamp('2016-01-01 00:00:00')
QA_util_get_real_date(QA_util_get_last_day('2019-07-01'), towards = -1)
QA_util_get_real_date(QA_util_get_next_day('2019-07-01'), towards = 1)
def QA_fetch_daily_basic(
code: Union[str, List, Tuple] = None,
start: Union[str, pd.Timestamp, datetime.datetime] = None,
end: Union[str, pd.Timestamp, datetime.datetime] = None,
cursor_date: Union[str, pd.Timestamp, datetime.datetime] = None,
fields: Union[str, Tuple, List] = None) -> pd.DataFrame:
"""获取全部股票每日重要的基本面指标，可用于选股分析、报表展示等
Args:
code (Union[str, List, Tuple], optional): 指定股票代码或列表, 默认为 None，获取全市场
start (Union[str, pd.Timestamp, datetime.datetime], optional): 起始日期，默认为 None
end (Union[str, pd.Timestamp, datetime.datetime], optional): 结束日期，默认为 None
cursor_date (Union[str, pd.Timestamp, datetime.datetime], optional): 指定日期，与 start 和 end 冲突，只能选择 cursor_date
或者 start, end
fields (Union[str, Tuple, List], optional): 指定 fields
Returns:
pd.DataFrame: 以日期，股票名为 Multiindex 的基本信息
"""
if isinstance(code, str):
code = (code, )
if not code:
if (not start) and (not cursor_date):
raise ValueError(
"[ERROR]\tstart and end and cursor_date cannot all be none!")
if not cursor_date:
if not end:
end_stamp = QA_util_date_stamp(datetime.date.today())
else:
end_stamp = QA_util_date_stamp(end)
start_stamp = QA_util_date_stamp(start)
qry = {
"trade_date_stamp": {
"$gte": start_stamp,
"$lte": end_stamp
}
}
else:
real_trade_date = QA_util_get_real_date(cursor_date)
trade_date_stamp = QA_util_date_stamp(real_trade_date)
qry = {"trade_date_stamp": trade_date_stamp}
else:
if (not start) and (not cursor_date):
raise ValueError(
"[ERROR]\tstart and end and cursor_date cannot all be none!")
if not cursor_date:
if not end:
end_stamp = QA_util_date_stamp(datetime.date.today())
else:
end_stamp = QA_util_date_stamp(end)
start_stamp = QA_util_date_stamp(start)
qry = {
"code": {
"$in": code
},
"trade_date_stamp": {
"$gte": start_stamp,
"$lte": end_stamp
}
}
else:
real_trade_date = QA_util_get_real_date(cursor_date)
trade_date_stamp = QA_util_date_stamp(real_trade_date)
qry = {"code": {"$in": code}, "trade_date_stamp": trade_date_stamp}
coll = DATABASE.daily_basic
cursor = coll.find(qry)
df = pd.DataFrame(cursor)
if df.empty:
return df
df = df.rename(columns={"trade_date": "date"}).drop(columns="_id")
df.date = pd.to_datetime(
df.date).dt.tz_localize(None).dt.tz_localize('Asia/Shanghai')
df = df.set_index(["date", "code"]).sort_index()
if not fields:
return df
return df[fields]
def now_time_tradedate():
return str(QA_util_get_real_date(str(da.today() - timedelta(days=1)), trade_date_sse, -1)) + \
' 17:00:00' if dt.now().hour < 15 else str(QA_util_get_real_date(
str(da.today()), trade_date_sse, -1)) + ' 15:00:00'
def __QA_backtest_prepare(self):
"""
这是模型内部的 初始化,主要是初始化一些账户和市场资产
写成了私有函数
@yutiansut
2017/7/20
"""
self.strategy_stock_list = np.unique(
self.strategy_stock_list).tolist() # 保证不会重复
if len(str(self.strategy_start_date)) == 10:
self.strategy_start_time = str(
self.strategy_start_date) + ' 15:00:00'
elif len(str(self.strategy_start_date)) == 19:
self.strategy_start_time = str(self.strategy_start_date)
self.strategy_start_date = str(self.strategy_start_date)[0:10]
else:
self.__QA_backtest_log_info(self, 'Wrong start date format')
if len(str(self.strategy_end_date)) == 10:
self.strategy_end_time = str(self.strategy_end_date) + ' 15:00:00'
elif len(str(self.strategy_end_date)) == 19:
self.strategy_end_time = str(self.strategy_end_date)
self.strategy_end_date = str(self.strategy_end_date)[0:10]
else:
self.__QA_backtest_log_info(self, 'Wrong end date format')
# 重新初始账户资产
self.market = QA_Market(self.commission_fee_coeff)
self.setting.QA_setting_init()
self.account.init()
self.account_d_value.append(self.account.init_assest)
self.start_real_date = QA_util_get_real_date(self.strategy_start_date,
self.trade_list, 1)
self.start_real_time = str(
self.start_real_date) + ' ' + self.strategy_start_time.split(
' ')[1]
self.start_real_id = self.trade_list.index(self.start_real_date)
self.end_real_date = QA_util_get_real_date(self.strategy_end_date,
self.trade_list, -1)
self.end_real_id = self.trade_list.index(self.end_real_date)
self.end_real_time = str(self.end_real_date) + \
' ' + self.strategy_end_time.split(' ')[1]
# 重新初始化账户的cookie
self.account.account_cookie = str(random.random())
# 初始化股票池的市场数据
if self.benchmark_type in ['I', 'index']:
self.benchmark_data = QA_fetch_index_day_adv(
self.benchmark_code, self.trade_list[self.start_real_id - 1],
self.end_real_date)
elif self.benchmark_type in ['S', 'stock']:
self.benchmark_data = QA_fetch_stock_day_adv(
self.benchmark_code, self.trade_list[self.start_real_id - 1],
self.end_real_date)
if self.backtest_type in ['day', 'd', '0x00']:
self.market_data = QA_fetch_stocklist_day_adv(
self.strategy_stock_list,
self.trade_list[self.start_real_id -
int(self.strategy_gap + 1)],
self.trade_list[self.end_real_id]).to_qfq()
elif self.backtest_type in ['1min', '5min', '15min', '30min', '60min']:
self.market_data = QA_fetch_stocklist_min_adv(
self.strategy_stock_list,
QA_util_time_gap(self.start_real_time, self.strategy_gap + 1,
'<', self.backtest_type),
QA_util_time_gap(self.end_real_time, 1, '>',
self.backtest_type),
self.backtest_type).to_qfq()
elif self.backtest_type in ['index_day']:
self.market_data = QA_fetch_index_day_adv(
self.strategy_stock_list,
self.trade_list[self.start_real_id -
int(self.strategy_gap + 1)],
self.end_real_date)
elif self.backtest_type in [
'index_1min', 'index_5min', 'index_15min', 'index_30min',
'index_60min'
]:
self.market_data = QA_fetch_index_min_adv(
self.strategy_stock_list,
QA_util_time_gap(self.start_real_time, self.strategy_gap + 1,
'<',
self.backtest_type.split('_')[1]),
QA_util_time_gap(self.end_real_time, 1, '>',
self.backtest_type.split('_')[1]),
self.backtest_type.split('_')[1])
self.market_data_dict = dict(
zip(list(self.market_data.code), self.market_data.splits()))
self.market_data_hashable = self.market_data.dicts
self.dirs = '.{}QUANTAXIS_RESULT{}{}{}{}{}'.format(
os.sep, os.sep, self.topic_name, os.sep, self.stratey_version,
os.sep)
os.makedirs(self.dirs, exist_ok=True)
