def data_get(self):
self.Price, \
self.LimitStatus, \
self.Status, \
self.listDateNum, \
self.Industry, \
self.Size \
= basic_data(para)
self.ROA_,\
self.CFO_, \
self.Accrual_, \
self.ROA_VAR, \
self.Sales_G_TTM_VAR, \
self.RD_MV_, \
self.Sales_MV_, \
self.Expenditure_MV_\
= data_initial_G(para)
self.Expenditure_MV_ = stock_dif(self.Expenditure_MV_,
self.LimitStatus)
self.RD_MV_ = stock_dif(self.RD_MV_, self.LimitStatus)
self.Sales_MV_ = stock_dif(self.Sales_MV_, self.LimitStatus)
self.Expenditure_MV_ = self.Expenditure_MV_.iloc[
para.backtestwindow:, :]
self.RD_MV_ = self.RD_MV_.iloc[para.backtestwindow:, :]
self.Sales_MV_ = self.Sales_MV_.iloc[para.backtestwindow:, :]
return
def __init__(self):
self.tradingDateList = getTradingDateFromJY(para.startDate,
para.endDate,
ifTrade=True,
Period='M')
# get basid data from function basic_data
self.Price, \
self.LimitStatus, \
self.Status, \
self.listDateNum, \
self.Industry, \
self.Size = basic_data(para)
pass
def __init__(self, para):
# get trading date list as monthly frequancy
self.tradingDateList = getTradingDateFromJY(para.startDate,
para.endDate,
ifTrade=True,
Period='M')
self.Price, self.LimitStatus, self.Status, self.listDateNum, self.Industry, self.Size = basic_data(
para)
Factor = pd.read_csv(para.data_path + para.factor + '.csv',
index_col=0)
self.Factor = stock_dif(Factor, self.LimitStatus)
self.df = pd.read_csv(para.data_path + 'mean_industry_index.csv',
index_col=0)
pass
def __init__(self, para):
# get trading date list as monthly frequancy
self.tradingDateList = getTradingDateFromJY(para.startDate,
para.endDate,
ifTrade=True,
Period='M')
DATA = loadData(para.factor)
Factor = DATA.BasicDailyFactorAlpha.loc[para.startDate:para.endDate, :]
self.Price, self.LimitStatus, self.Status, self.listDateNum, self.Industry, self.Size = basic_data(
para)
self.Factor = stock_dif(Factor, self.LimitStatus)
# self.Factor = pd.read_csv(para.result_path+'等权重_Factor.csv',index_col=0)
pass
def __init__(self):
self.tradingDateList = getTradingDateFromJY(para.startDate, para.endDate, ifTrade=True, Period='M')
Factor = loadData(para = para.factor).BasicDailyFactorAlpha.loc[para.startDate:para.endDate, :]
self.Factor2 = pd.read_csv(para.result_path+'_'+para.factor2+'.csv',index_col=0)
self.Price, self.LimitStatus, self.Status, self.listDateNum, self.Industry, self.Size = basic_data(para)
self.Factor = stock_dif(Factor, self.LimitStatus)
self.Factor.index = self.LimitStatus.index.copy()
# self.Factor2 = stock_dif(Factor2, self.LimitStatus)
# self.Factor2.index = self.LimitStatus.index.copy()
# _, self.Factor2 = Gmain().every_month()
# self.Factor2.columns = self.LimitStatus.columns.copy()
pass
'STD_1Y_Excess',
'STD_3M',
'STD_3M_Excess',
'STD_6M',
'STD_6M_Excess'
]
pass
para = Para()
tradingDateList = getTradingDateFromJY(para.startDate,
para.endDate,
ifTrade=True,
Period='M')
Price, LimitStatus, Status, listDateNum, Industry, Size = basic_data(para)
Factor = pd.DataFrame()
WIC = []
IC = []
IC_list = []
for i, currentDate in enumerate(tqdm(tradingDateList[:-1])):
lastDate = tradingDateList[tradingDateList.index(currentDate) - 1]
if para.ret_calMethod == '对数':
ret = np.log(Price.loc[currentDate, :] / Price.loc[lastDate, :])
elif para.ret_calMethod == '简单':
ret = Price.loc[currentDate, :] / Price.loc[lastDate, :] - 1
dataFrame = pd.concat([
ret, LimitStatus.loc[currentDate, :], Status.loc[currentDate, :],
listDateNum.loc[currentDate, :], Industry.loc[currentDate, :],
def data_get(self):
self.ROA_, self.CFO_, self.GROAQ_, self.Accrual_, \
self.delta_BLEV_, self.delta_CurrentRatio_, self.EG_OFFER, self.delta_GrossProfitMargin_, \
self.delta_AssetsTurn_\
= data_initial_F(para)
self.Price, self.LimitStatus, self.Status, self.listDateNum, self.Industry, self.Size = basic_data(
para)
return
def __init__(self, para):
# get trading date list as monthly frequancy
self.tradingDateList = getTradingDateFromJY(para.startDate,
para.endDate,
ifTrade=True,
Period='M')
self.Price, self.LimitStatus, self.Status, self.listDateNum, self.Industry, self.Size = basic_data(
para)
# self.Factor = pd.read_excel(para.data_path + para.factor + '.xlsx',index_col = 0).T
Factor = pd.read_csv(para.data_path + para.factor + '.csv',
index_col=0)
self.Factor = stock_dif(Factor, self.LimitStatus)
# self.Factor = Factor.loc[para.startDate:para.endDate, :]
# self.Factor.index = self.LimitStatus.index.copy()
# Factor.index.astype('str')
# Factor.index = pd.to_datetime(Factor.index, format='%Y%m%d')
# self.Price = stock_dif(self.Price,self.Factor)
# self.LimitStatus = stock_dif(self.LimitStatus, self.Factor)
# self.Status = stock_dif(self.Status, self.Factor)
# self.listDateNum = stock_dif(self.listDateNum, self.Factor)
# self.Industry = stock_dif(self.Industry, self.Factor)
# self.Size = stock_dif(self.Size, self.Factor)
# self.Factor.index = self.LimitStatus.index
pass
