def write_public_fxwy(end_date, save_path):
# 参数
###########################################################################################
fund_name = '泰达宏利复兴伟业'
fund_code = '001170.OF'
fund_type = "公募"
benchmark_code = '885001.WI'
benchmark_name = '偏股混合基金总指数'
benchmark_code_2 = "000300.SH"
benchmark_name_2 = "沪深300"
benchmark_ratio = 0.95
setup_date = '20150421' # 吴华开始管理 也是成立日
today = datetime.strptime(end_date, "%Y%m%d")
before_1y = datetime(year=today.year-1, month=today.month, day=today.day).strftime("%Y%m%d")
before_2y = datetime(year=today.year-2, month=today.month, day=today.day).strftime("%Y%m%d")
before_3y = datetime(year=today.year-3, month=today.month, day=today.day).strftime("%Y%m%d")
before_5y = datetime(year=today.year-5, month=today.month, day=today.day).strftime("%Y%m%d")
date_array = np.array([["2019年", '20190101', end_date, '20180930'],
["2018年", "20180101", '20181231', "20170930"],
["2017年", "20170101", '20171231', "20160930"],
["2016年", '20160101', '20161231', "20150930"],
["成立以来（吴华管理）", setup_date, end_date, setup_date],
["过去1年", before_1y, end_date, before_1y],
["过去2年", before_2y, end_date, before_2y],
["过去3年", before_3y, end_date, before_3y],
])
benchmark_array = np.array([["沪深300", "000300.SH"],
["中证500", "000905.SH"],
["股票型基金总指数", '885012.WI'],
["WIND全A", '881001.WI']])
from quant.fund.fund import Fund
fund_pct = Fund().get_fund_factor("Repair_Nav_Pct")
bench_pct = Fund().get_fund_factor("Fund_Bench_Pct") * 100
# 准备文件
###########################################################################################
file_name = os.path.join(save_path, "OutFile", fund_name + '.xlsx')
sheet_name = fund_name
excel = WriteExcel(file_name)
worksheet = excel.add_worksheet(sheet_name)
# 写入基金表现 和基金排名
###########################################################################################
performance_table = MfcTable().cal_summary_table_sample(fund_name, fund_code, fund_type, date_array, benchmark_array)
rank1 = FundRank().rank_fund_array2(fund_pct, bench_pct, fund_code, date_array, "偏股混合型基金", excess=False)
rank2 = FundRank().rank_fund_array2(fund_pct, bench_pct, fund_code, date_array, "灵活配置型基金_60", excess=False)
rank3 = FundRank().rank_fund_array2(fund_pct, bench_pct, fund_code, date_array, "股票+灵活配置60型基金", excess=False)
performance_table = pd.concat([performance_table, rank1, rank2, rank3], axis=0)
col_number = 1
num_format_pd = pd.DataFrame([], columns=performance_table.columns, index=['format'])
num_format_pd.ix['format', :] = '0.00%'
excel.write_pandas(performance_table, worksheet, begin_row_number=0, begin_col_number=col_number,
num_format_pd=num_format_pd, color="red", fillna=True)
col_number = col_number + performance_table.shape[1] + 2
# 读取基金和基准时间序列
###########################################################################################
fund_data = MfcData().get_mfc_nav(fund_code, fund_name, fund_type)
benchmark_data = Index().get_index_factor(benchmark_code, attr=["CLOSE"])
fs = FinancialSeries(pd.DataFrame(fund_data), pd.DataFrame(benchmark_data))
cum_return = fs.get_fund_and_bencnmark_cum_return_series(setup_date, end_date)
benchmark_data = Index().get_index_factor(benchmark_code_2, attr=["CLOSE"])
fs = FinancialSeries(pd.DataFrame(fund_data), pd.DataFrame(benchmark_data))
cum_return2 = fs.get_bencnmark_cum_return_series(setup_date, end_date)
# 写入基金和基准时间序列
###########################################################################################
cum_return = pd.concat([cum_return, cum_return2], axis=1)
cum_return.columns = [fund_name, benchmark_name, benchmark_name_2]
cum_return = cum_return.dropna()
num_format_pd = pd.DataFrame([], columns=cum_return.columns, index=['format'])
num_format_pd.ix['format', :] = '0.00%'
excel.write_pandas(cum_return, worksheet, begin_row_number=0, begin_col_number=col_number,
num_format_pd=num_format_pd, color="blue", fillna=True)
# 基金和基准时间序列图
###########################################################################################
chart_name = fund_name + "累计收益（管理以来）"
series_name = [fund_name, benchmark_name, benchmark_name_2]
insert_pos = 'B12'
excel.line_chart_time_series_plot(worksheet, 0, col_number, cum_return,
series_name, chart_name, insert_pos, sheet_name)
excel.close()
###########################################################################################
return True
def write_public_qf(end_date, save_path):
# 参数
###########################################################################################
fund_name = '泰达宏利启富'
fund_code = '003912.OF'
fund_type = "公募"
benchmark_code = '885003.WI'
benchmark_name = '偏债混合型基金总指数'
benchmark_code_2 = "881001.WI"
benchmark_name_2 = "WIND全A"
benchmark_ratio = 0.95
setup_date = '20170315'
date_array = np.array([["2019年", '20190101', end_date, '20180930'],
["2018年", "20180101", '20181231', "20170930"],
["2017年", setup_date, '20171231', setup_date],
["成立以来", setup_date, end_date, setup_date]])
benchmark_array = np.array([["沪深300",
"000300.SH"], ["WIND全A", "881001.WI"],
["中证全债", "H11001.CSI"],
["偏债混合基金指数", '885003.WI']])
from quant.fund.fund import Fund
fund_pct = Fund().get_fund_factor("Repair_Nav_Pct")
bench_pct = Fund().get_fund_factor("Fund_Bench_Pct") * 100
# 准备文件
###########################################################################################
file_name = os.path.join(save_path, "OutFile", fund_name + '.xlsx')
sheet_name = fund_name
excel = WriteExcel(file_name)
worksheet = excel.add_worksheet(sheet_name)
# 写入基金表现 和基金排名
###########################################################################################
performance_table = MfcTable().cal_summary_table(fund_name, fund_code,
fund_type, date_array,
benchmark_array)
rank0 = FundRank().rank_fund_array2(fund_pct,
bench_pct,
fund_code,
date_array,
"灵活配置型基金_30",
excess=False)
rank1 = FundRank().rank_fund_array2(fund_pct,
bench_pct,
fund_code,
date_array,
"wind",
excess=False)
performance_table = pd.concat([performance_table, rank0, rank1], axis=0)
col_number = 1
num_format_pd = pd.DataFrame([],
columns=performance_table.columns,
index=['format'])
num_format_pd.ix['format', :] = '0.00%'
excel.write_pandas(performance_table,
worksheet,
begin_row_number=0,
begin_col_number=col_number,
num_format_pd=num_format_pd,
color="red",
fillna=True)
col_number = col_number + performance_table.shape[1] + 2
# 读取基金和基准时间序列
###########################################################################################
fund_data = MfcData().get_mfc_nav(fund_code, fund_name, fund_type)
benchmark_data = Index().get_index_factor(benchmark_code, attr=["CLOSE"])
fs = FinancialSeries(pd.DataFrame(fund_data), pd.DataFrame(benchmark_data))
cum_return = fs.get_fund_and_bencnmark_cum_return_series(
setup_date, end_date)
benchmark_data = Index().get_index_factor(benchmark_code_2, attr=["CLOSE"])
fs = FinancialSeries(pd.DataFrame(fund_data), pd.DataFrame(benchmark_data))
cum_return2 = fs.get_bencnmark_cum_return_series(setup_date, end_date)
# 写入基金和基准时间序列
###########################################################################################
cum_return = pd.concat([cum_return, cum_return2], axis=1)
cum_return.columns = [fund_name, benchmark_name, benchmark_name_2]
cum_return = cum_return.dropna()
num_format_pd = pd.DataFrame([],
columns=cum_return.columns,
index=['format'])
num_format_pd.ix['format', :] = '0.00%'
excel.write_pandas(cum_return,
worksheet,
begin_row_number=0,
begin_col_number=col_number,
num_format_pd=num_format_pd,
color="blue",
fillna=True)
# 基金和基准时间序列图
###########################################################################################
chart_name = fund_name + "累计收益（成立以来）"
series_name = [fund_name, benchmark_name, benchmark_name_2]
insert_pos = 'B12'
excel.line_chart_time_series_plot(worksheet, 0, col_number, cum_return,
series_name, chart_name, insert_pos,
sheet_name)
excel.close()
###########################################################################################
return True