def get_stock_excess_pct():
""" 得到股票超额收益率 """
stock_pct = Stock().read_factor_h5("Pct_chg").T
free_pct = Macro().get_daily_risk_free_rate()
free_pct = free_pct['RiskFreeRate']
stock_excess_pct = stock_pct.sub(free_pct, axis='index')
stock_excess_pct = stock_excess_pct.dropna(how='all')
return stock_excess_pct
def cal_factor_exposure(self, beg_date, end_date):
""" 计算因子暴露 """
income = Stock().read_factor_h5("OperatingIncome").T
cost = Stock().read_factor_h5("OperatingCost").T
[income, cost] = Stock().make_same_index_columns([income, cost])
gross_profit = income.sub(cost)
gross_profit_4 = gross_profit.shift(4)
profit_yoy = gross_profit / gross_profit_4 - 1.0
profit_yoy = profit_yoy.T
report_data = Stock().read_factor_h5("ReportDateDaily")
profit_yoy = Stock().change_quarter_to_daily_with_disclosure_date(profit_yoy, report_data, beg_date, end_date)
res = profit_yoy.T.dropna(how='all').T
self.save_alpha_factor_exposure(res, self.raw_factor_name)
def cal_factor_exposure(self, beg_date, end_date):
""" 计算因子暴露 """
income = Stock().read_factor_h5("OperatingIncome")
cost = Stock().read_factor_h5("OperatingCost")
report_data = Stock().read_factor_h5("ReportDateDaily")
income_ttm = Stock().change_single_quarter_to_ttm_quarter(income).T
cost_ttm = Stock().change_single_quarter_to_ttm_quarter(cost).T
gross_profit_ttm = income_ttm.sub(cost_ttm)
gross_profit_ratio = gross_profit_ttm.div(income_ttm)
gpr = gross_profit_ratio.T
gpr = Stock().change_quarter_to_daily_with_disclosure_date(
gpr, report_data, beg_date, end_date)
res = gpr.T.dropna(how='all').T
self.save_alpha_factor_exposure(res, self.raw_factor_name)
def cal_factor_barra_leverage_book_leverage(self):
"""
账面杠杆 =（普通股账面价值+优先股账面价值+长期负债）/ 普通股账面价值
"""
holder_equity = Stock().read_factor_h5("TotalShareHoldeRequityDaily")
preferred_equity = Stock().read_factor_h5("PreferredEquityDaily")
common_equity = holder_equity.sub(preferred_equity)
long_loan = Stock().read_factor_h5("LongTermLoanDaily")
add = holder_equity.add(long_loan, fill_value=0.0)
book_leverage = add.div(common_equity)
book_leverage = book_leverage.T.dropna(how='all').T
self.save_risk_factor_exposure(book_leverage,
self.raw_factor_name_book_leverage)
book_leverage = FactorPreProcess().remove_extreme_value_mad(
book_leverage)
book_leverage = FactorPreProcess().standardization(book_leverage)
self.save_risk_factor_exposure(book_leverage,
self.factor_name_book_leverage)
def cal_factor_exposure(self, beg_date, end_date):
""" 计算因子暴露 """
# read data
income = Stock().read_factor_h5("OperatingIncome")
cost = Stock().read_factor_h5("OperatingCost")
total_share = Stock().read_factor_h5("TotalShare")
price_unadjust = Stock().read_factor_h5("Price_Unadjust")
report_data = Stock().read_factor_h5("ReportDateDaily")
profit = income.sub(cost)
# data precessing
profit = Stock().change_quarter_to_daily_with_disclosure_date(profit, report_data, beg_date, end_date)
[total_share, price_unadjust] = FactorPreProcess().make_same_index_columns([total_share, price_unadjust])
total_mv = total_share.mul(price_unadjust) / 100000000
[profit, total_mv] = Stock().make_same_index_columns([profit, total_mv])
gross_ep = 4 * profit.div(total_mv)
# save data
gross_ep = gross_ep.T.dropna(how='all').T
self.save_alpha_factor_exposure(gross_ep, self.raw_factor_name)
from quant.stock.stock import Stock
from quant.stock.date import Date
import pandas as pd
pct = Stock().read_factor_h5("Pct_chg")
price = Stock().read_factor_h5("Price_Adjust")
pct_2 = price.T.pct_change(fill_method=None).T * 100
diff = pct.sub(pct_2)
date = diff.abs().max().argmax()
diff_date = diff[date]
stock = diff_date.abs().argmax()
beg_date = Date().get_trade_date_offset(date, -10)
end_date = Date().get_trade_date_offset(date, 4)
print(stock, date)
print(diff.loc[stock, beg_date:end_date])
print(pct.loc[stock, beg_date:end_date])
print(pct_2.loc[stock, beg_date:end_date])
print(price.loc[stock, beg_date:end_date])
print(price.loc[stock, beg_date:end_date].pct_change())
