新增异常公告剔除列表
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@ -39,8 +39,8 @@ class Account():
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if isinstance(leverage, (int,float)):
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if leverage > 1.5:
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raise ValueError('leverage should less than 1.5')
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if leverage > 1:
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warnings.warn('leverage(杠杆率)大于1时，优先满足杠杆，会出现高于指定换手率的情况！', category=CustomWarning)
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# if leverage > 1:
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# warnings.warn('leverage(杠杆率)大于1时，优先满足杠杆，会出现高于指定换手率的情况！', category=CustomWarning)
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else:
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raise ValueError('leverage should be int or float')
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self.leverage = leverage
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@ -72,6 +72,7 @@ class Spread_Backtest():
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else:
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year_rtn.loc[year, '收益'] = (rtn_stat.loc[end_date] / rtn_stat.loc[start_date]) - 1
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year_rtn.loc['Annualized'] = np.power(rtn_stat.values[-1], 1 / (len(rtn_stat) / 244)) - 1
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year_rtn.loc['Avg.Turnover'] = self.trader.account_history.groupby('date')['turnover'].sum().mean()
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year_rtn = year_rtn.applymap(lambda x: '{:.2%}'.format(x))
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year_rtn = year_rtn.reset_index()
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year_rtn.columns = ['Year', 'Rtn']
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63
trader.py
63
trader.py
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@ -1,6 +1,7 @@
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import pandas as pd
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import numpy as np
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import sys, os
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import copy
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sys.path.append("/home/lenovo/quant/tools/get_factor_tools/")
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from db_tushare import get_factor_tools
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gft = get_factor_tools()
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@ -55,6 +56,7 @@ class Trader(Account):
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'2008-09-19': (0, 0.001),
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'2023-08-28': (0, 0.0005)
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},
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exclude_list: list=[],
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**kwargs) -> None:
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# 初始化账户
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super().__init__(**kwargs.get('account', {}))
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@ -138,6 +140,11 @@ class Trader(Account):
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self.tax = tax
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else:
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raise ValueError('tax should be dict.')
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# exclude
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if isinstance(exclude_list, list):
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self.exclude_list = exclude_list
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else:
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raise ValueError('exclude_list should be list.')
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# data_root
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# 至少包含basic data路径，open信号默认使用basic_data
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if len(data_root) <= 0:
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@ -229,7 +236,16 @@ class Trader(Account):
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stock_ipo_filter.loc[:] = 0
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stock_ipo_filter.loc[stock_ipo_days > self.ipo_days] = 1
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# 剔除列表
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exclude_stock = []
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for exclude in self.exclude_list:
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if exclude == 'abnormal':
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stock_abnormal = self.today_data['basic'].get(factor.index.values, 'abnormal').sort_index()
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exclude_stock += stock_abnormal.loc[stock_abnormal > 0].index.to_list()
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exclude_stock = list(set(exclude_stock))
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force_exclude = copy.deepcopy(exclude_stock)
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exclude_stock += stock_ipo_filter.loc[stock_ipo_filter != 1].index.to_list()
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exclude_stock += stock_amt_filter.loc[stock_amt_filter != 1].index.to_list()
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exclude_stock = list(set(exclude_stock))
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# 交易列表
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if self.leverage <= 1.0:
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# 获取当前时间目标列表和冻结(无法交易)列表:
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@ -239,13 +255,12 @@ class Trader(Account):
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# 如果停牌或者跌停继续持有
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if stock_status.loc[stock] in [0,2]:
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target_list.append(stock)
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for stock in factor.dropna().sort_values(ascending=self.ascending).index.values:
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# 剔除过滤条件后
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after_filter_list = list(set(factor.index) - set(exclude_stock))
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for stock in factor.loc[after_filter_list].dropna().sort_values(ascending=self.ascending).index.values:
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# 目标持仓数量达到持仓数量则中止
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if len(target_list) == self.num:
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break
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# 成交量、上市时间过滤
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if (stock_amt_filter.loc[stock] != 1) or (stock_ipo_filter.loc[stock] != 1):
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continue
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# ST过滤
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if self.with_st:
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if stock_status.loc[stock] in [0,2,5,7]:
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@ -257,7 +272,6 @@ class Trader(Account):
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# 非ST
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if stock_status.loc[stock] in [3,6]:
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target_list.append(stock)
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# 如果停牌或者跌停继续持有
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if stock_status.loc[stock] in [0,2,7]:
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if stock in last_position.index:
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@ -268,12 +282,19 @@ class Trader(Account):
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buy_list = []
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sell_list = []
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# ----- 卖出 -----
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# 异常强制卖出
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for stock in last_position.index:
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if stock in force_exclude:
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sell_list.append(stock)
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force_sell_num = len(sell_list)
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# 按照反向排名逐个卖出
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if self.ascending:
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factor = factor.fillna(factor.max()+1)
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else:
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factor = factor.fillna(factor.min()-1)
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for stock in factor.loc[last_position.index].sort_values(ascending=self.ascending).index.values[::-1]:
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if len(sell_list) >= max_sell_num + force_sell_num:
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break
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if stock in target_list:
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continue
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else:
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@ -281,9 +302,7 @@ class Trader(Account):
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continue
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else:
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sell_list.append(stock)
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if len(sell_list) >= max_sell_num:
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break
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sell_list = list(set(sell_list))
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# ----- 买入 -----
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# 卖出后持仓列表
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after_sell_list = set(last_position.index) - set(sell_list)
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@ -329,8 +348,9 @@ class Trader(Account):
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# 如果停牌或者跌停继续持有
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if stock_status.loc[stock] in [0,2]:
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normal_list, margin_list = assign_stock(normal_list, margin_list, margin_needed, stock, is_margin.loc[stock])
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for stock in factor.dropna().sort_values(ascending=self.ascending).index.values:
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# 剔除过滤条件后
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after_filter_list = list(set(factor.index) - set(exclude_stock))
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for stock in factor.loc[after_filter_list].dropna().sort_values(ascending=self.ascending).index.values:
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if stock_amt_filter.loc[stock] != 1:
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continue
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if self.with_st:
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@ -360,7 +380,14 @@ class Trader(Account):
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last_margin_list = self.position.loc[self.position['margin_trade'] == 1, 'stock_code'].to_list()
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else:
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last_margin_list = []
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# 异常强制卖出
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for stock in last_margin_list:
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if stock in force_exclude:
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sell_list.append(stock)
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force_sell_num = len(sell_list)
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for stock in factor.loc[last_margin_list].sort_values(ascending=self.ascending).index.values[::-1]:
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if len(sell_list) >= int(max_sell_num * margin_ratio) + force_sell_num + 1:
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break
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if stock in normal_list:
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continue
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else:
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@ -368,15 +395,21 @@ class Trader(Account):
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continue
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else:
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sell_list.append(stock)
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if len(sell_list) >= int(max_sell_num * margin_ratio) + 1:
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break
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sell_list = list(set(sell_list))
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next_margin_list = list(set(last_margin_list) - set(sell_list))
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# 更新非融资融券池
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if len(last_position) > 0:
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last_normal_list = self.position.loc[self.position['margin_trade'] == 0, 'stock_code'].to_list()
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else:
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last_normal_list = []
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# 异常强制卖出
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for stock in last_normal_list:
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if stock in force_exclude:
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sell_list.append(stock)
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force_sell_num += 1
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for stock in factor.loc[last_normal_list].sort_values(ascending=self.ascending).index.values[::-1]:
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if len(sell_list) >= max_sell_num + force_sell_num:
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break
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if stock in normal_list:
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continue
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else:
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@ -384,8 +417,7 @@ class Trader(Account):
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continue
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else:
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sell_list.append(stock)
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if len(sell_list) >= max_sell_num:
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break
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sell_list = list(set(sell_list))
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next_normal_list = list(set(last_normal_list) - set(sell_list))
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# ----- 买入 -----
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# 卖出后持仓列表
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@ -412,6 +444,7 @@ class Trader(Account):
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next_normal_list.append(stock)
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if len(next_normal_list) >= self.num - margin_needed:
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break
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next_position = pd.DataFrame({'stock_code': next_margin_list + next_normal_list})
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next_position['date'] = date
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# 融资融券数量
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