def run_formula(dv):
import pandas as pd
import numpy as np
from jaqs_fxdayu.data.dataservice import LocalDataService
dataview_folder = r'D:\my_data\量化云实习\data'
ds = LocalDataService(fp=dataview_folder)
rm=ds.index_daily(['000300.SH'], 20130101, 20180101,'trade_date,close')[0].set_index('trade_date')['close']
Rm80=rm.pct_change(80)
r80=dv.get_ts('close').pct_change(80)
Index_var80=(Rm80.rolling(80).std())**2
cov_r80=r80.rolling(80).cov(Rm80)
beta80=cov_r80.apply(lambda x:x/Index_var80,axis=0)
r_adj80=beta80.apply(lambda x:x*Rm80*100,axis=0)
dv.append_df(r_adj80,'r_adj80')
return r_adj80
def get_dv(start=20170101, end=20180101):
import jaqs_fxdayu
jaqs_fxdayu.patch_all()
from jaqs.data import DataView
from jaqs_fxdayu.data.dataservice import LocalDataService
import warnings
warnings.filterwarnings("ignore")
# --------------------------------------------------------
# define
factor_list = [
'np_parent_comp_ttm', 'tot_cur_liab', 'cogstosales', 'oper_rev_ttm',
'tangibleasset', 'interestdebt'
]
check_factor = ','.join(factor_list)
dataview_folder = r'd:/data'
ds = LocalDataService(fp=dataview_folder)
ZZ800_id = ds.query_index_member("000906.SH", start, end)
stock_symbol = list(set(ZZ800_id))
ben_ret = list(ds.index_daily(['000300.SH'], start, end, 'close'))[0]
dv_props = {
'start_date': start,
'end_date': end,
'symbol': ','.join(stock_symbol),
'fields': check_factor,
'freq': 1,
"prepare_fields": True
}
dv = DataView()
dv.init_from_config(dv_props, data_api=ds)
dv.prepare_data()
return dv
vema12 = pd.DataFrame(index=volume.index)
for col in volume.columns:
inter = pd.DataFrame(pd.Series(ta.EMA(np.array(list(volume[col])), 12)),
columns=[col])
for i in range(1215):
vema12.loc[vema12.index[i], col] = inter.iloc[i, 0]
temp = []
test = list(vema12.columns)
for i in stock_symbol:
if i not in test:
temp = temp + [i]
for i in temp:
vema12[i] = np.nan
dv.append_df(vema12, "vema12")
#informationratio60
hs300 = ds.index_daily(['000300.SH'], 20130101, 20180101,
"close")[0].pct_change()
close = dv.get_ts("close")
hs300 = hs300.set_index(close.index)
hs300 = hs300['close']
close = close.dropna(axis=1)
close = close.pct_change()
close = close.sub(hs300, axis=0) #计算出了每日的超额收益,下面计算60日IC
ret = close.rolling(window=60).mean()
std = close.rolling(window=60).std()
ir60 = close.copy()
for col in ir60.columns:
ir60[col] = ret[col].div(std[col], axis=0) #计算出60日信息比率
dv.append_df(ir60, "ir60")
#adminiexpenserate
adminiexpenserate = dv.add_formula(
'adminiexpenserate',