def FundReturnQuarter(report_date):
"""
计算在给定时间点前后一个月 一个基金收益 利用基金复权净值计算
"""
T = 20
beg_date = Date().get_trade_date_offset(report_date, -T)
end_date = Date().get_trade_date_offset(report_date, T)
date_series = Date().get_trade_date_series(beg_date, end_date)
fund_code_list = Fund().get_fund_pool_code(date=report_date,
name="基金持仓基准基金池")
fund_code_list3 = Fund().get_fund_pool_code(date=report_date, name="量化基金")
fund_code_list2 = Fund().get_fund_pool_code(date="20180630", name="东方红基金")
fund_code_list.extend(fund_code_list2)
fund_code_list.extend(fund_code_list3)
fund_code_list = list(set(fund_code_list))
fund_code_list.sort()
fund_pct = Fund().get_fund_factor("Repair_Nav_Pct", date_series,
fund_code_list)
print(" Calculting fund Return At date %s " % report_date)
fund_pct[fund_pct == 0] = np.nan
fund_pct_period = pd.DataFrame(fund_pct.sum(skipna=True).values,
index=fund_pct.columns,
columns=[report_date])
fund_pct_period[fund_pct_period == 0] = np.nan
return fund_pct_period
def GetAllFundAlphaOnFactorFile(stock_alpha, fund_holding_date, factor_name,
report_date):
"""
计算所有基金 在某个日期 在 Factor 上的alpha
"""
# params
###################################################################################
# report_date = '20171231'
# path = 'E:\\3_Data\\4_fund_data\\7_fund_select_stock\\StockAlpha\\'
# factor_name = "TotalMarketValue"
#
# stock_alpha = GetStockAlphaAtFactorFile(path, factor_name)
# fund_holding_all = Fund().get_fund_holding_all()
# fund_holding_date = fund_holding_all[fund_holding_all['Date'] == report_date]
# read data
###################################################################################
fund_code_list = Fund().get_fund_pool_code(date=report_date,
name="基金持仓基准基金池")
fund_code_list3 = Fund().get_fund_pool_code(date=report_date, name="量化基金")
fund_code_list2 = Fund().get_fund_pool_code(date="20180630", name="东方红基金")
fund_code_list.extend(fund_code_list2)
fund_code_list.extend(fund_code_list3)
result = pd.DataFrame([], index=fund_code_list, columns=[report_date])
# cal fund alpha on style
####################################################################################
for i in range(0, len(fund_code_list)):
fund_code = fund_code_list[i]
fund_holding = fund_holding_date[fund_holding_date['FundCode'] ==
fund_code]
fund_holding.index = fund_holding['StockCode']
fund_holding = fund_holding.ix[~fund_holding.index.duplicated(), :]
fund_holding = fund_holding.dropna(subset=['Weight'])
alpha = GetFundAlphaAtFactorFile(stock_alpha, fund_holding,
report_date)
result.ix[fund_code, report_date] = alpha
if fund_code == "229002.OF":
print(fund_holding)
print(" Alpha Fund %s At Date %s On Factor %s is %s" %
(fund_code, report_date, factor_name, str(alpha)))
####################################################################################
return result
def AllFundBarraDecomposeReturnQuarter(fund_holding_all, path, report_date):
"""
计算一个季报时间点 前后一个月 所有基金 拆分的 特异收益 风格收益 行业收益 和 市场收益
"""
# 参数
######################################################################################################
# report_date = '20171231'
# path = 'E:\\3_Data\\4_fund_data\\7_fund_select_stock\\'
# fund_holding_all = Fund().get_fund_holding_all()
# 持仓信息
######################################################################################################
fund_holding_date = fund_holding_all[fund_holding_all['Date'] ==
report_date]
# 基金池信息
######################################################################################################
fund_code_list = Fund().get_fund_pool_code(date=report_date,
name="基金持仓基准基金池")
fund_code_list3 = Fund().get_fund_pool_code(date=report_date, name="量化基金")
fund_code_list2 = Fund().get_fund_pool_code(date="20180630", name="东方红基金")
fund_code_list.extend(fund_code_list2)
fund_code_list.extend(fund_code_list3)
fund_code_list = list(set(fund_code_list))
fund_code_list.sort()
# cal fund alpha on style
######################################################################################################
for i in range(0, len(fund_code_list)):
fund_code = fund_code_list[i]
if i == 0:
result = FundBarraDecomposeReturnQuarter(fund_holding_date,
report_date, path,
fund_code)
else:
res = FundBarraDecomposeReturnQuarter(fund_holding_date,
report_date, path, fund_code)
result = pd.concat([result, res], axis=0)
######################################################################################################
file = "FundBarraDecomposeReturnQuarter" + report_date + '.csv'
file = os.path.join(path, "FundBarraDecomposeReturnQuarter", file)
result.to_csv(file)
def GetAllFundAllDateFactorAlphaFile(in_path, out_path, factor_name_list,
date_series):
# params
####################################################################################
# in_path = 'E:\\3_Data\\4_fund_data\\7_fund_select_stock\\StockAlpha\\'
# out_path = 'E:\\3_Data\\4_fund_data\\7_fund_select_stock\\FundSelectStockAlpha\\'
#
# factor_name_list = ["TotalMarketValue", "BP", "IncomeYOYDaily", "ROETTMDaily", "Industry"]
#
# beg_date = "20170530"
# end_date = "20180630"
# date_series = Date().get_normal_date_series(beg_date, end_date, "S")
if not os.path.exists(out_path):
os.makedirs(out_path)
# read data
###################################################################################
fund_code_list = Fund().get_fund_pool_code(date=report_date,
name="基金持仓基准基金池")
fund_code_list3 = Fund().get_fund_pool_code(date=report_date, name="量化基金")
fund_code_list2 = Fund().get_fund_pool_code(date="20180630", name="东方红基金")
fund_code_list.extend(fund_code_list2)
fund_code_list.extend(fund_code_list3)
result = pd.DataFrame([], index=fund_code_list, columns=[report_date])
# cal fund alpha on style
####################################################################################
for i in range(0, len(fund_code_list)):
fund_code = fund_code_list[i]
# read data
####################################################################################
fund_holding_all = Fund().get_fund_holding_all()
# cal alpha
####################################################################################
for i_factor in range(len(factor_name_list)):
factor_name = factor_name_list[i_factor]
stock_alpha = GetStockAlphaAtFactorFile(in_path, factor_name)
for i_date in range(len(date_series)):
report_date = date_series[i_date]
fund_holding_date = fund_holding_all[fund_holding_all['Date'] ==
report_date]
alpha_date = GetAllFundAlphaOnFactorFile(stock_alpha,
fund_holding_date,
factor_name, report_date)
if i_date == 0:
new_data = alpha_date
else:
new_data = pd.concat([new_data, alpha_date], axis=1)
new_data = new_data.T.dropna(how="all")
filename = os.path.join(out_path,
'FundSelectStockAlpha_' + factor_name + '.csv')
if os.path.exists(filename):
old_data = pd.read_csv(filename, index_col=[0], encoding='gbk')
old_data.index = old_data.index.map(str)
result = pandas_add_row(old_data, new_data)
else:
result = new_data
result.to_csv(filename)
