def run_alpha(self):
fund_code = self.get_fund_code_by_filter(ALPHA_FILTER)
run_cnt = 0
fd_num = len(fund_code)
logging.info('funds number: {}'.format(fd_num))
for code in fund_code:
run_cnt += 1
logging.info('code: {} pct: {} / {}'.format(code, run_cnt, fd_num))
for date_list in self.run_date_list:
report_date = date_list[0]
# 只跑近一年
for year_lag in range(1, 4):
tmp_date = date_list[4 - year_lag]
start_date = pd.date_range(
start=tmp_date, periods=2,
freq='D').strftime('%Y%m%d').tolist()[-1]
try:
rst_value = compute_alpha_categroy(code,
start_date,
report_date,
run_type=0)
logging.info('start_date: {} end_date: {}'.format(
start_date, report_date))
logging.info('code {} year_lag {} alpha{}'.format(
code, year_lag, rst_value))
except Exception as err:
logging.warning(err)
rst_value = None
rec = (code,
'AlphaCategroyBenchmark{}Year'.format(year_lag),
str(rst_value), None, self.algid, report_date,
self.thisfilename, self.todaydate)
self.db_insert_session.add_info(rec)
# 跑半年
for date_list in self.half_year_date_list:
report_date = date_list[0]
tmp_date = date_list[1]
start_date = pd.date_range(
start=tmp_date, periods=2,
freq='D').strftime('%Y%m%d').tolist()[-1]
try:
rst_value = compute_alpha_categroy(code,
start_date,
report_date,
run_type=0)
my_logger.info('start_date: {} end_date: {}'.format(
start_date, report_date))
my_logger.info('code {} year_lag {} alpha:{}'.format(
code, 'half', rst_value))
except Exception as err:
my_logger.warning(err)
rst_value = None
rec = (code, 'AlphaCategroyBenchmark6Month'.format(year_lag),
str(rst_value), None, self.algid, report_date,
self.thisfilename, self.todaydate)
self.db_insert_session.add_info(rec)
self.db_insert_session.finish()
return
def run_alpha0(self):
fund_code = self.get_fund_code_by_filter(ALPHA_FILTER)
run_cnt = 0
fd_num = len(fund_code)
logging.info('funds number: {}'.format(fd_num))
for code in fund_code:
run_cnt += 1
logging.info('code: {} pct: {} / {}'.format(code, run_cnt, fd_num))
for date_list in self.run_date_list:
report_date = date_list[0]
start_date = self.find_fund_clr(code)
if start_date > report_date:
continue
try:
rst_value = compute_alpha_categroy(code, start_date, report_date, run_type=0)
logging.info('start_date: {} end_date: {}'.format(start_date, report_date))
logging.info('code {} year_lag {} alpha{}'.format(code, "", rst_value))
except Exception as err:
logging.warning(err)
rst_value = None
rec = (
code, 'AlphaCategroyBenchmarkAll', str(rst_value), None, self.algid, report_date, self.thisfilename,
self.todaydate)
print(rec)
self.db_insert_session.add_info(rec)
self.db_insert_session.finish()
def compute_alpha(code, start_date, end_date):
''' 计算相对收益alpha
'''
# to do
try:
alpha = compute_alpha_categroy(code, start_date, end_date)
except Exception as err:
print(err)
logging.debug(err)
alpha = None
logging.info('\t alpha: {}'.format(alpha))
return alpha
def test_compute_alpha_categroy():
codes = '960042'
codes = '370010'
codes = '110011'
codes = '002073'
start, end = '20151231', '20181231'
# run_type: 0 同类基准, 1 同类平均, 2 基金基准
# 基金基准 空值过多
codes, start, end = '519644', '20150101', '20161231'
codes, start, end = '370010', '20151001', '20180930'
'''
run_type = 2
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
run_type = 1
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
'''
run_type = 0
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
'''
# 同类基准
run_type = 0
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
# 测试是否根据不同净值取不同基准
start, end = '20120101', '20180101'
run_type = 0
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
return
'''
'''
# 同类平均, 时间开销测试
s_time = time.time()
start, end = '20160331', '20190331'
run_type = 1
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
e_time = time.time()
print('caculate cost {}'.format(e_time - s_time))
'''
return
def test_compute_alpha_categroy():
# 计算基金基准
code, start, end = '050004', '20040622', '20150710'
run_type = 2
rst = compute_alpha_categroy(code, start, end, run_type)
print(rst)
# 基金基准不足，改取同类基准进行计算
code, start, end = '050004', '20040622', '20190710'
run_type = 2
rst = compute_alpha_categroy(code, start, end, run_type)
print(rst)
codes, start, end = '519644', '20150101', '20161231'
run_type = 2
rst = compute_alpha_categroy(code, start, end, run_type)
print(rst)
'''
# 货币型 没有同类基准
code, start, end = '370010', '20151001', '20180930'
run_type = 0
rst = compute_alpha_categroy(code, start, end, run_type)
print(rst)
'''
# 测试 基准不够去同类基准流程
code, start, end = '184691', '19990504', '20140409'
run_type = 2
rst = compute_alpha_categroy(code, start, end, run_type)
print(rst)
'''
# run_type: 0 同类基准, 1 同类平均, 2 基金基准
# 基金基准 空值过多
codes, start, end = '519644', '20150101', '20161231'
codes, start, end = '370010', '20151001', '20180930'
run_type = 2
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
run_type = 1
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
run_type = 0
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
# 同类基准
run_type = 0
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
# 测试是否根据不同净值取不同基准
start, end = '20120101', '20180101'
run_type = 0
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
return
# 同类平均, 时间开销测试
s_time = time.time()
start, end = '20160331', '20190331'
run_type = 1
rst = compute_alpha_categroy(codes, start, end, run_type)
print(rst)
e_time = time.time()
print('caculate cost {}'.format(e_time - s_time))
'''
return