parent
d671f820d4
commit
0977e8c9fd
|
|
@ -0,0 +1,68 @@
|
|||
import numpy as np
|
||||
|
||||
|
||||
def check_buy_exclude(buy_exclude):
|
||||
buy_exclude_dict = dict()
|
||||
# 检查剔除条件
|
||||
for cond in ['amt_20', 'list_days', 'mkt', 'price']:
|
||||
if cond == 'amt_20':
|
||||
# 20日成交量均值
|
||||
if cond in buy_exclude:
|
||||
amt_exclude = buy_exclude[cond]
|
||||
else:
|
||||
buy_exclude[cond] = (0, np.inf)
|
||||
continue
|
||||
if isinstance(buy_exclude[cond], (set,list,tuple)):
|
||||
if len(amt_exclude) == 1:
|
||||
buy_exclude_dict[cond] = (amt_exclude[0], np.inf)
|
||||
else:
|
||||
buy_exclude_dict[cond] = (amt_exclude[0], amt_exclude[1])
|
||||
else:
|
||||
raise Exception('wrong input type for buy exclude: amt_20, `set`, `list` or `tuple` is required')
|
||||
|
||||
if cond == 'list_days':
|
||||
# 上市时间
|
||||
if cond in buy_exclude:
|
||||
list_exclude = buy_exclude[cond]
|
||||
else:
|
||||
buy_exclude[cond] = (0, np.inf)
|
||||
continue
|
||||
if isinstance(buy_exclude[cond], (set,list,tuple)):
|
||||
if len(list_exclude) == 1:
|
||||
buy_exclude_dict[cond] = (list_exclude[0], np.inf)
|
||||
else:
|
||||
buy_exclude_dict[cond] = (list_exclude[0], list_exclude[1])
|
||||
else:
|
||||
raise Exception('wrong input type for buy exclude: list_days, `set`, `list` or `tuple` is required')
|
||||
|
||||
if cond == 'mkt':
|
||||
# 市值
|
||||
if cond in buy_exclude:
|
||||
mkt_exclude = buy_exclude[cond]
|
||||
else:
|
||||
buy_exclude[cond] = (0, np.inf)
|
||||
continue
|
||||
if isinstance(buy_exclude[cond], (set,list,tuple)):
|
||||
if len(mkt_exclude) == 1:
|
||||
buy_exclude_dict[cond] = (mkt_exclude[0], np.inf)
|
||||
else:
|
||||
buy_exclude_dict[cond] = (mkt_exclude[0], mkt_exclude[1])
|
||||
else:
|
||||
raise Exception('wrong input type for buy exclude: mkt, `set`, `list` or `tuple` is required')
|
||||
|
||||
if cond == 'price':
|
||||
# 价格
|
||||
if cond in buy_exclude:
|
||||
price_exclude = buy_exclude[cond]
|
||||
else:
|
||||
buy_exclude[cond] = (0, np.inf)
|
||||
continue
|
||||
if isinstance(buy_exclude[cond], (set,list,tuple)):
|
||||
if len(price_exclude) == 1:
|
||||
buy_exclude_dict[cond] = (price_exclude[0], np.inf)
|
||||
else:
|
||||
buy_exclude_dict[cond] = (price_exclude[0], price_exclude[1])
|
||||
else:
|
||||
raise Exception('wrong input type for buy exclude: price, `set`, `list` or `tuple` is required')
|
||||
|
||||
return buy_exclude_dict
|
||||
|
|
@ -10,8 +10,8 @@ if __name__ == '__main__':
|
|||
data_dir = '/home/lenovo/quant/tools/detail_testing/basic_data'
|
||||
save_dir = '/home/lenovo/quant/data/backtest/basic_data'
|
||||
|
||||
for i,f in enumerate(['open_post','close_post','down_limit','up_limit','size','amount_20','opening_info','ipo_days','margin_list',
|
||||
'abnormal', 'recession']):
|
||||
for i,f in enumerate(['open_post','close_post','open_pre','close_pre','down_limit','up_limit','size','amount_20',
|
||||
'opening_info','ipo_days','margin_list','abnormal', 'recession']):
|
||||
if f in ['margin_list']:
|
||||
tmp = gft.get_stock_factor(f, start='2012-01-01').fillna(0)
|
||||
else:
|
||||
|
|
@ -34,7 +34,7 @@ if __name__ == '__main__':
|
|||
# 更新下一日的数据用于筛选
|
||||
next_date = gft.days_after(df.index.max(), 1)
|
||||
next_list = []
|
||||
for i,f in enumerate(['amount_20','opening_info','ipo_days','margin_list','abnormal','recession']):
|
||||
for i,f in enumerate(['close_pre','size','amount_20','opening_info','ipo_days','margin_list','abnormal','recession']):
|
||||
if f in ['margin_list']:
|
||||
next_list.append(pd.Series(gft.get_stock_factor(f, start='2012-01-01').fillna(0).iloc[-1], name=f))
|
||||
else:
|
||||
|
|
|
|||
104
trader.py
104
trader.py
|
|
@ -1,5 +1,4 @@
|
|||
import pandas as pd
|
||||
import numpy as np
|
||||
import sys
|
||||
import os
|
||||
import copy
|
||||
|
|
@ -8,12 +7,13 @@ from typing import Union, Iterable, Dict
|
|||
|
||||
from account import Account
|
||||
from dataloader import DataLoader
|
||||
from check_funcs import check_buy_exclude
|
||||
|
||||
sys.path.append("/home/lenovo/quant/tools/get_factor_tools/")
|
||||
from db_tushare import get_factor_tools
|
||||
gft = get_factor_tools()
|
||||
|
||||
|
||||
|
||||
class Trader(Account):
|
||||
"""
|
||||
交易类: 用于控制每日交易情况
|
||||
|
|
@ -35,7 +35,7 @@ class Trader(Account):
|
|||
slippage (tuple): 买入和卖出滑点
|
||||
commission (float): 佣金
|
||||
tax (dict): 印花税
|
||||
exclude_list (list): 额外的剔除列表，会优先满足该剔除列表中的条件，之后再进行正常的调仓
|
||||
force_exclude (list): 额外的剔除列表，会优先满足该剔除列表中的条件，之后再进行正常的调仓
|
||||
- abnormal: 异常公告剔除，包含中止上市、立案调查、警示函等异常情况的剔除
|
||||
- receesion: 财报同比或环比下降50%以上
|
||||
- qualified_opinion: 会计保留意见
|
||||
|
|
@ -50,18 +50,17 @@ class Trader(Account):
|
|||
data_root:dict={},
|
||||
tick: bool=False,
|
||||
weight: str='avg',
|
||||
amt_filter: set=(0,),
|
||||
ipo_days: int=20,
|
||||
slippage :tuple=(0.001,0.001),
|
||||
commission: float=0.0001,
|
||||
buy_exclude: Dict[str, Union[set,int,float]]={},
|
||||
force_exclude: list=[],
|
||||
account: dict={},
|
||||
tax: dict={
|
||||
'1990-01-01': (0.001,0.001),
|
||||
'2008-04-24': (0.001,0.001),
|
||||
'2008-09-19': (0, 0.001),
|
||||
'2023-08-28': (0, 0.0005)
|
||||
},
|
||||
exclude_list: list=[],
|
||||
account: dict={},
|
||||
**kwargs) -> None:
|
||||
# 初始化账户
|
||||
super().__init__(**account)
|
||||
|
|
@ -100,21 +99,6 @@ class Trader(Account):
|
|||
self.weight = weight
|
||||
else:
|
||||
raise ValueError('invalid type for `weight`')
|
||||
# amt_filter
|
||||
if isinstance(amt_filter, (set,list,tuple)):
|
||||
if len(amt_filter) == 1:
|
||||
self.amt_filter_min = amt_filter[0]
|
||||
self.amt_filter_max = np.inf
|
||||
else:
|
||||
self.amt_filter_min = amt_filter[0]
|
||||
self.amt_filter_max = amt_filter[1]
|
||||
else:
|
||||
raise Exception('wrong type for amt_filter, `set` `list` or `tuple` is required')
|
||||
# ipo_days
|
||||
if isinstance(ipo_days, int):
|
||||
self.ipo_days = ipo_days
|
||||
else:
|
||||
raise Exception('wrong type for ipo_days, `int` is required')
|
||||
# slippage
|
||||
if isinstance(slippage, tuple) and len(slippage) == 2:
|
||||
self.slippage = slippage
|
||||
|
|
@ -130,17 +114,19 @@ class Trader(Account):
|
|||
self.tax = tax
|
||||
else:
|
||||
raise ValueError('tax should be dict.')
|
||||
# exclude
|
||||
if isinstance(exclude_list, list):
|
||||
self.exclude_list = exclude_list
|
||||
# buy exclude
|
||||
self.buy_exclude = check_buy_exclude(buy_exclude)
|
||||
# force exclude
|
||||
if isinstance(force_exclude, list):
|
||||
self.force_exclude = force_exclude
|
||||
optional_list = ['abnormal', 'recession']
|
||||
for item in exclude_list:
|
||||
for item in force_exclude:
|
||||
if item in optional_list:
|
||||
pass
|
||||
else:
|
||||
raise ValueError(f"Unexpected keyword argument '{item}'")
|
||||
else:
|
||||
raise ValueError('exclude_list should be list.')
|
||||
raise ValueError('force_exclude should be list.')
|
||||
# data_root
|
||||
# 至少包含basic data路径，open信号默认使用basic_data
|
||||
if len(data_root) <= 0:
|
||||
|
|
@ -276,36 +262,58 @@ class Trader(Account):
|
|||
|
||||
# 获取用于筛选的数据
|
||||
stock_status = self.today_data['basic'].get(factor.index.values, 'opening_info').sort_index()
|
||||
stock_amt20 = self.today_data['basic'].get(factor.index.values, 'amount_20').sort_index()
|
||||
stock_amt_filter = stock_amt20.copy()
|
||||
stock_amt_filter.loc[:] = 0
|
||||
stock_amt_filter.loc[(stock_amt20 > self.amt_filter_min) & (stock_amt20 < self.amt_filter_max)] = 1
|
||||
stock_amt_filter = stock_amt_filter.sort_index()
|
||||
stock_ipo_days = self.today_data['basic'].get(factor.index.values, 'ipo_days').sort_index()
|
||||
stock_ipo_filter = stock_ipo_days.copy()
|
||||
stock_ipo_filter.loc[:] = 0
|
||||
stock_ipo_filter.loc[stock_ipo_days > self.ipo_days] = 1
|
||||
exclude_data = dict()
|
||||
for cond in self.buy_exclude:
|
||||
if cond == 'amt_20':
|
||||
stock_amt20 = self.today_data['basic'].get(factor.index.values, 'amount_20').sort_index()
|
||||
stock_amt_exclude = stock_amt20.copy()
|
||||
stock_amt_exclude.loc[:] = 0
|
||||
stock_amt_exclude.loc[(stock_amt20 > self.buy_exclude[cond][0]) & (stock_amt20 < self.buy_exclude[cond][1])] = 1
|
||||
stock_amt_exclude = stock_amt_exclude.sort_index()
|
||||
exclude_data[cond] = stock_amt_exclude
|
||||
if cond == 'list_days':
|
||||
stock_ipo_days = self.today_data['basic'].get(factor.index.values, 'ipo_days').sort_index()
|
||||
stock_ipo_exclude = stock_ipo_days.copy()
|
||||
stock_ipo_exclude.loc[:] = 0
|
||||
stock_ipo_exclude.loc[(stock_ipo_days > self.buy_exclude[cond][0]) & (stock_ipo_days < self.buy_exclude[cond][1])] = 1
|
||||
stock_ipo_exclude = stock_ipo_exclude.sort_index()
|
||||
exclude_data[cond] = stock_ipo_exclude
|
||||
if cond == 'mkt':
|
||||
stock_size = self.today_data['basic'].get(factor.index.values, 'size').sort_index()
|
||||
stock_size_exclude = stock_size.copy()
|
||||
stock_size_exclude.loc[:] = 0
|
||||
stock_size_exclude.loc[(stock_size > self.buy_exclude[cond][0]) & (stock_size < self.buy_exclude[cond][1])] = 1
|
||||
stock_size_exclude = stock_size_exclude.sort_index()
|
||||
exclude_data[cond] = stock_size_exclude
|
||||
if cond == 'price':
|
||||
stock_price = self.today_data['basic'].get(factor.index.values, 'close_pre').sort_index()
|
||||
stock_price_exclude = stock_price.copy()
|
||||
stock_price_exclude.loc[:] = 0
|
||||
stock_price_exclude.loc[(stock_price > self.buy_exclude[cond][0]) & (stock_price < self.buy_exclude[cond][1])] = 1
|
||||
stock_price_exclude = stock_price_exclude.sort_index()
|
||||
exclude_data[cond] = stock_price_exclude
|
||||
|
||||
# 剔除列表
|
||||
# 包含强制列表和普通列表：
|
||||
# 包含强制剔除列表和买入剔除列表：
|
||||
# 强制列表会将已经持仓的也强制剔除并且不算在换手率限制中
|
||||
# 普通列表如果已经持有不会过滤只对新买入的过滤
|
||||
# 买入剔除列表如果已经持有不会过滤只对新买入的过滤
|
||||
|
||||
# 强制过滤列表
|
||||
exclude_stock = []
|
||||
for exclude in self.exclude_list:
|
||||
if exclude == 'abnormal':
|
||||
for cond in self.force_exclude:
|
||||
if cond == 'abnormal':
|
||||
stock_abnormal = self.today_data['basic'].get(factor.index.values, 'abnormal').sort_index()
|
||||
exclude_stock += stock_abnormal.loc[stock_abnormal > 0].index.to_list()
|
||||
if exclude == 'recession':
|
||||
if cond == 'recession':
|
||||
stock_recession = self.today_data['basic'].get(factor.index.values, 'recession').sort_index()
|
||||
exclude_stock += stock_recession.loc[stock_recession > 0].index.to_list()
|
||||
exclude_stock = list(set(exclude_stock))
|
||||
force_exclude = copy.deepcopy(exclude_stock)
|
||||
# 普通过滤列表
|
||||
normal_exclude = []
|
||||
normal_exclude += stock_ipo_filter.loc[stock_ipo_filter != 1].index.to_list()
|
||||
normal_exclude += stock_amt_filter.loc[stock_amt_filter != 1].index.to_list()
|
||||
normal_exclude = list(set(normal_exclude))
|
||||
# 买入过滤列表
|
||||
buy_exclude = []
|
||||
for cond in self.buy_exclude:
|
||||
buy_exclude += exclude_data[cond].loc[exclude_data[cond] != 1].index.to_list()
|
||||
buy_exclude = list(set(buy_exclude))
|
||||
|
||||
# 交易列表
|
||||
# 仓位判断给与计算误差冗余
|
||||
|
|
@ -360,7 +368,7 @@ class Trader(Account):
|
|||
buy_list = []
|
||||
|
||||
# 剔除过滤条件后可买入列表
|
||||
after_filter_list = list(set(factor.index) - set(normal_exclude) - set(force_exclude))
|
||||
after_filter_list = list(set(factor.index) - set(buy_exclude) - set(force_exclude))
|
||||
target_list = factor.loc[after_filter_list].dropna().sort_values(ascending=self.ascending).index.to_list()
|
||||
|
||||
# 更新卖出后的持仓列表
|
||||
|
|
@ -469,7 +477,7 @@ class Trader(Account):
|
|||
buy_list = []
|
||||
|
||||
# 剔除过滤条件后可买入列表
|
||||
after_filter_list = list(set(factor.index) - set(normal_exclude) - set(force_exclude))
|
||||
after_filter_list = list(set(factor.index) - set(buy_exclude) - set(force_exclude))
|
||||
target_list = factor.loc[after_filter_list].dropna().sort_values(ascending=self.ascending).index.to_list()
|
||||
|
||||
# 更新卖出后的持仓列表
|
||||
|
|
|
|||
Loading…
Reference in New Issue