def _calc_factor_loading(cls, code, calc_date):
"""
计算指定日期、指定个股EGRLF因子载荷
Parameters:
--------
:param code: str
个股代码, 如SH600000, 600000
:param calc_date: datetime-like, str
计算日期, 格式: YYYY-MM-DD
:return: pd.Series
--------
个股的EGRLF因子载荷
0. code
1. egrlf
如果计算失败, 返回None
"""
code = Utils.code_to_symbol(code)
calc_date = Utils.to_date(calc_date)
# 读取个股的预期盈利增长率数据
earningsgrowth_data = Utils.get_consensus_data(
calc_date, code, ConsensusType.PredictedEarningsGrowth)
if earningsgrowth_data is None:
# 如果个股的预期盈利增长率数据不存在, 那么用过去3年净利润增长率代替
hist_growth_data = Utils.get_hist_growth_data(code, calc_date, 3)
if hist_growth_data is None:
return None
if np.isnan(hist_growth_data['netprofit']):
return None
egrlf = hist_growth_data['netprofit']
else:
egrlf = earningsgrowth_data['growth_2y']
return pd.Series([code, egrlf], index=['code', 'egrlf'])
def _calc_factor_loading(cls, code, calc_date):
"""
计算指定日期、指定个股EPFWD因子载荷
Parameters:
--------
:param code: str
个股代码, 如SH600000, 600000
:param calc_date: datetime-like, str
计算日期, 格式: YYYY-MM-DD
:return: pd.Series
--------
个股的EPFWD因子载荷
0. code
1. epfwd
如果计算失败, 返回None
"""
code = Utils.code_to_symbol(code)
# 读取个股的预期盈利数据
predictedearnings_data = Utils.get_consensus_data(
calc_date, code, ConsensusType.PredictedEarings)
if predictedearnings_data is None:
# 如果个股的预期盈利数据不存在, 那么代替ttm净利润
ttm_fin_data = Utils.get_ttm_fin_basic_data(code, calc_date)
if ttm_fin_data is None:
return None
predictedearnings_data = pd.Series(
[code, ttm_fin_data['NetProfit']],
index=['code', 'predicted_earnings'])
fpredictedearnings = predictedearnings_data['predicted_earnings']
if np.isnan(fpredictedearnings):
return None
# 读取个股市值
size_path = os.path.join(factor_ct.FACTOR_DB.db_path,
risk_ct.LNCAP_CT.db_file)
size_factor_loading = Utils.read_factor_loading(
size_path, Utils.datetimelike_to_str(calc_date, dash=False), code)
if size_factor_loading.empty:
return None
# epfwd = 盈利预期/市值
epfwd = fpredictedearnings * 10000.0 / np.exp(
size_factor_loading['factorvalue'])
return pd.Series([code, epfwd], index=['code', 'epfwd'])
