def __init__(self) -> None:
"""Constructor"""
super().__init__()
self.factor_data_manager: FactorDataManager = FactorDataManager()
self.industry_data_manager: IndustryDataManager = IndustryDataManager()
self.continuous_contract_data_manager: ContinuousContractDataManager = ContinuousContractDataManager(
)
self.factor_test_result_path: Path = Path(
__file__).parent.parent.joinpath("output_result")
self.factor_info: Dict[str, str] = {}
self.factor: BaseFactor = None
self.factor_params: Dict[str, Any] = {}
def __init__(self, **params) -> None:
"""Constructor"""
super().__init__(**params)
self.group: str = Path(inspect.getfile(self.__class__)).parent.name
self.name: str = self.__class__.__name__
self.daily_data_manager: DailyDataManager = DailyDataManager()
self.basics_data_manager: BasicsDataManager = BasicsDataManager()
self.continuous_contract_data_manager: ContinuousContractDataManager = ContinuousContractDataManager(
)
self.daily_volume: DataFrame = None
self.listed_date_df: DataFrame = None
self.all_instruments: DataFrame = None
self.commodity_pool_value: DataFrame = None
def __init__(self, file_path: str) -> None:
"""Constructor"""
self.file_path: Path = Path(file_path)
self.factor_name: str = None
self.factor_data: DataFrame = None
self.factor_data_with_pool: DataFrame = None
self.commodity_pool: DataFrame = None
self.long_short_quantile_func: Callable = None
self.quantile1: Series = None
self.quantile2: Series = None
self.continuous_contract_data_manager: ContinuousContractDataManager = ContinuousContractDataManager()
# 如果不存在因子绩效保存路径，则需要先创建
self.init_file_path()
def __init__(self, **params) -> None:
"""Constructor"""
super().__init__(**params)
self.group: str = Path(inspect.getfile(self.__class__)).parent.name
self.name: str = self.__class__.__name__
self.all_instruments: DataFrame = None
self.symbol_industry_map: DataFrame = None
self.daily_data_manager: DailyDataManager = DailyDataManager()
self.basics_data_manager: BasicsDataManager = BasicsDataManager()
self.continuous_contract_data_manager: ContinuousContractDataManager = ContinuousContractDataManager(
)
self.maturity_date_dict: Dict[str, DataFrame] = {}
self.factor_value: DataFrame = None
self.init_basics_data()
## 导入库
import pandas as pd
from data_manager.DailyDataManager import DailyDataManager
from data_manager.ContinuousContractDataManager import ContinuousContractDataManager
## 导入数据
volume_df = DailyDataManager().daily_data.groupby(
['datetime', 'underlying_symbol'])['volume'].sum().unstack(level=-1)
price_df = ContinuousContractDataManager().get_field(field='continuous_price')
## 检查index和columns是否完全相等
print("index is equal: ", volume_df.index.equals(price_df.index))
print("columns is equal: ", volume_df.columns.equals(price_df.columns))
## 检查volume_df有数据的位置price_df是否一定有数据
check1_df = pd.DataFrame(data=False,
index=volume_df.index,
columns=volume_df.columns)
check1_df[(volume_df.notnull()) & (price_df.isnull())] = True
print(check1_df.astype(int).sum().sum())
check1_series = check1_df.sum()
check1_series[check1_series == 1]
check1_df.loc[check1_df == True, 'LR']
from datetime import datetime
price_df.loc[datetime(2020, 7, 15), 'LR']
# price_df.loc[datetime(2020, 7,15), 'LR'] = price_df.loc[datetime(2020,7,14), 'LR']
## 检查price_df有数据的位置volume_df一定有数据
import pandas as pd
import matplotlib.pyplot as plt
from data_manager.BasicsDataManager import BasicsDataManager
from data_manager.ContinuousContractDataManager import ContinuousContractDataManager
symbol_list = BasicsDataManager().get_symbol_list()
self = ContinuousContractDataManager()
data_list = []
contract = 'main'
for price in ['close', 'settlement']:
for rebalance_num in [1, 3, 5]:
df = self.get_continuous_contract_data(contract=contract, price=price, rebalance_num=rebalance_num)
df = df[['datetime', 'underlying_symbol', 'continuous_price']]
df['contract'] = contract
df['price'] = price
df['rebalance_num'] = rebalance_num
data_list.append(df)
data = pd.concat(data_list, axis=0)
for symbol in symbol_list:
df = data[data.underlying_symbol == symbol]
plt.figure()
df.groupby(['price', 'rebalance_num'])['continuous_price'].plot(legend=True)
plt.savefig(f"C:/Users/qtg_i/Desktop/LFNotes/笔记/期货连续合约/主力连续合约/主力连续合约对比/{symbol}.png")
plt.show()
import os
import pandas as pd
folder_path = "D:/LFProjects/NewPythonProject/data/continuous_contract_series"
def __init__(self) -> None:
""""""
self.index_data_path: Path = Path(__file__).parent.parent.joinpath("data").joinpath("index")
self.industry_data_manager: IndustryDataManager = IndustryDataManager()
self.continuous_contract_data_manager: ContinuousContractDataManager = ContinuousContractDataManager()
from data_manager.ContinuousContractDataManager import ContinuousContractDataManager
from correlation_analysis.analysis import get_industry_correlation_result, get_period_industry_correlation_result
##
# 导入代码名称列表
all_instruments: DataFrame = BasicsDataManager().get_all_instruments()[[
'underlying_symbol', 'symbol', 'industry_name'
]]
all_instruments['name'] = all_instruments['symbol'].str.extract(r"([^0-9]+)")
all_instruments = all_instruments[['underlying_symbol',
'name']].drop_duplicates()
symbol_name_map: Dict[str, str] = all_instruments.set_index(
'underlying_symbol')['name'].to_dict()
##
# 导入连续合约数据
price_df: DataFrame = ContinuousContractDataManager().get_field(
field='continuous_price')
return_df = ContinuousContractDataManager().get_field(field='return')
##
# 导入行业数据
industry_data_manager = IndustryDataManager()
industry_data_manager.get_all_industry_symbol_maps()
# 从行业数据中导出谷物的组
arg_groups = {}
arg_groups[
'Huatai_industry_map'] = industry_data_manager.get_industry_symbol_map(
group='original_industry', name='Huatai_industry_map')['谷物']
arg_groups['RQ_industry_map'] = industry_data_manager.get_industry_symbol_map(
group='original_industry', name='RQ_industry_map')['谷物']
##