def test_cross_ma():
factor = CrossMaFactor(codes=['000338'],
start_timestamp='2019-01-01',
end_timestamp='2019-06-10',
level=IntervalLevel.LEVEL_1DAY,
provider=Provider.JoinQuant,
windows=[5, 10],
adjust_type='qfq')
print(factor.factor_df.tail())
print(factor.result_df.tail())
score = factor.result_df['score']
assert score[('stock_sz_000338', '2019-06-03')] == True
assert score[('stock_sz_000338', '2019-06-04')] == True
assert ('stock_sz_000338',
'2019-06-05') not in score or score[('stock_sz_000338',
'2019-06-05')] == False
assert ('stock_sz_000338',
'2019-06-06') not in score or score[('stock_sz_000338',
'2019-06-06')] == False
assert ('stock_sz_000338',
'2019-06-10') not in score or score[('stock_sz_000338',
'2019-06-10')] == False
factor.move_on()
score = factor.result_df['score']
assert score[('stock_sz_000338', '2019-06-17')] == True
def test_cross_ma_selector():
region = Region.CHN
entity_ids = ['stock_sz_000338']
entity_type = EntityType.Stock
start_timestamp = '2018-01-01'
end_timestamp = '2019-06-30'
my_selector = TargetSelector(region=region,
entity_ids=entity_ids,
entity_schema=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp)
# add the factors
my_selector \
.add_filter_factor(CrossMaFactor(region=region,
entity_ids=entity_ids,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
computing_window=10,
windows=[5, 10],
need_persist=False,
level=IntervalLevel.LEVEL_1DAY,
adjust_type='qfq'))
my_selector.run()
print(my_selector.open_long_df)
print(my_selector.open_short_df)
assert 'stock_sz_000338' in my_selector.get_open_short_targets(
'2018-01-29')
def init_selectors(self,
entity_ids,
entity_schema,
exchanges,
codes,
start_timestamp,
end_timestamp,
adjust_type=None):
myselector = TargetSelector(
entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider="joinquant",
)
myselector.add_factor(
CrossMaFactor(
entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
windows=[5, 10],
need_persist=False,
adjust_type=adjust_type,
))
self.selectors.append(myselector)
def init_selectors(self,
region: Region,
entity_ids,
entity_schema,
exchanges,
codes,
start_timestamp,
end_timestamp,
adjust_type=None):
myselector = TargetSelector(region=region,
entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider=Provider.JoinQuant)
myselector.add_filter_factor(
CrossMaFactor(region=region,
entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
windows=[5, 10],
need_persist=False,
adjust_type=adjust_type))
self.selectors.append(myselector)
def test_cross_ma_selector():
entity_ids = ["stock_sz_000338"]
entity_type = "stock"
start_timestamp = "2018-01-01"
end_timestamp = "2019-06-30"
my_selector = TargetSelector(entity_ids=entity_ids,
entity_schema=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp)
# add the factors
my_selector.add_factor(
CrossMaFactor(
entity_ids=entity_ids,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
computing_window=10,
windows=[5, 10],
need_persist=False,
level=IntervalLevel.LEVEL_1DAY,
adjust_type="hfq",
))
my_selector.run()
print(my_selector.open_long_df)
print(my_selector.open_short_df)
assert "stock_sz_000338" in my_selector.get_open_short_targets(
"2018-01-29")
def report_cross_ma():
while True:
error_count = 0
email_action = EmailInformer()
try:
# 抓取k线数据
# StockTradeDay.record_data(provider='joinquant')
# Stock1dKdata.record_data(provider='joinquant')
latest_day: StockTradeDay = StockTradeDay.query_data(
order=StockTradeDay.timestamp.desc(),
limit=1,
return_type='domain')
if latest_day:
target_date = latest_day[0].timestamp
else:
target_date = now_pd_timestamp()
# 计算均线
my_selector = TargetSelector(start_timestamp='2018-01-01',
end_timestamp=target_date)
# add the factors
ma_factor = CrossMaFactor(start_timestamp='2018-01-01',
end_timestamp=target_date)
my_selector.add_filter_factor(ma_factor)
my_selector.run()
long_targets = my_selector.get_open_long_targets(
timestamp=target_date)
if long_targets:
stocks = get_entities(provider='joinquant',
entity_schema=Stock,
entity_ids=long_targets,
return_type='domain')
info = [f'{stock.name}({stock.code})' for stock in stocks]
msg = ' '.join(info)
else:
msg = 'no targets'
logger.info(msg)
email_action.send_message("*****@*****.**",
f'{target_date} 均线选股结果', msg)
break
except Exception as e:
logger.exception('report_cross_ma error:{}'.format(e))
time.sleep(60 * 3)
error_count = error_count + 1
if error_count == 10:
email_action.send_message("*****@*****.**",
f'report_cross_ma error',
'report_cross_ma error:{}'.format(e))
def every_day_report():
while True:
try:
t = now_pd_timestamp()
if t.dayofweek in (5, 6):
logger.info(f'today:{t} is {t.day_name()},just ignore')
today = to_time_str(t)
# 抓取k线数据
JqChinaStockKdataRecorder(level=IntervalLevel.LEVEL_1DAY).run()
JqChinaStockKdataRecorder(level=IntervalLevel.LEVEL_1WEEK).run()
JqChinaStockKdataRecorder(level=IntervalLevel.LEVEL_1MON).run()
# 计算均线
my_selector = TargetSelector(start_timestamp='2016-01-01',
end_timestamp=today)
# add the factors
# 设置dry_run为True，因为我们只需要最近的数据，不需要加载全量数据进行回测
ma_factor = CrossMaFactor(start_timestamp='2016-01-01',
end_timestamp=today,
dry_run=True)
my_selector.add_filter_factor(ma_factor)
my_selector.run()
long_targets = my_selector.get_open_long_targets(timestamp=today)
if long_targets:
df = get_entities(provider='eastmoney',
entity_schema=Stock,
entity_ids=long_targets,
columns=['code', 'name'])
info = [
df.loc[i, 'code'] + ' ' + df.loc[i, 'name']
for i in df.index
]
msg = ' '.join(info)
else:
msg = 'no targets'
logger.info(msg)
email_action = EmailInformer()
email_action.send_message("*****@*****.**", f'{today} 均线选股结果', msg)
break
except Exception as e:
logger.exception('report1 sched error:{}'.format(e))
time.sleep(60 * 3)
def every_day_report():
while True:
try:
today = now_pd_timestamp()
long_targets = select_by_finance(today)
logger.info(f'selected:{len(long_targets)}')
if long_targets:
ma_factor = CrossMaFactor(start_timestamp='2015-01-01',
end_timestamp=today,
dry_run=True,
persist_factor=False,
entity_ids=long_targets,
windows=[5, 30, 120])
my_selector = TargetSelector(start_timestamp='2015-01-01',
end_timestamp=today,
entity_ids=long_targets)
my_selector.add_filter_factor(ma_factor)
my_selector.run()
final_targets = my_selector.get_open_long_targets(today)
final_targets = list(set(final_targets))
logger.info(f'final selected:{len(final_targets)}')
if final_targets:
df = get_entities(provider='eastmoney',
entity_schema=Stock,
entity_ids=final_targets,
columns=['code', 'name'])
info = [
df.loc[i, 'code'] + ' ' + df.loc[i, 'name']
for i in df.index
]
msg = ' '.join(info)
else:
msg = 'no targets'
logger.info(msg)
email_action = EmailInformer()
email_action.send_message("*****@*****.**",
f'{today} 基本面 + 技术面选股结果', msg)
break
except Exception as e:
logger.exception('report3 sched error:{}'.format(e))
time.sleep(60 * 3)
def test_cross_ma():
factor = CrossMaFactor(
codes=["000338"],
start_timestamp="2019-01-01",
end_timestamp="2019-06-10",
level=IntervalLevel.LEVEL_1DAY,
provider="joinquant",
windows=[5, 10],
adjust_type="qfq",
)
print(factor.factor_df.tail())
print(factor.result_df.tail())
score = factor.result_df["filter_result"]
assert score[("stock_sz_000338", "2019-06-03")] == True
assert score[("stock_sz_000338", "2019-06-04")] == True
assert ("stock_sz_000338", "2019-06-05") not in score or score[("stock_sz_000338", "2019-06-05")] == False
assert ("stock_sz_000338", "2019-06-06") not in score or score[("stock_sz_000338", "2019-06-06")] == False
assert ("stock_sz_000338", "2019-06-10") not in score or score[("stock_sz_000338", "2019-06-10")] == False
factor.move_on()
score = factor.result_df["filter_result"]
assert score[("stock_sz_000338", "2019-06-17")] == True
def init_selectors(self, entity_ids, entity_schema, exchanges, codes,
start_timestamp, end_timestamp):
# 周线策略
week_selector = TargetSelector(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider='joinquant',
level=IntervalLevel.LEVEL_1WEEK)
week_bull_factor = GoldBullFactor(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider='joinquant',
level=IntervalLevel.LEVEL_1WEEK)
week_selector.add_filter_factor(week_bull_factor)
# 日线策略
day_selector = TargetSelector(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider='joinquant',
level=IntervalLevel.LEVEL_1DAY)
cross_ma_factor = CrossMaFactor(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider='joinquant',
level=IntervalLevel.LEVEL_1DAY,
windows=[5, 250])
day_selector.add_filter_factor(cross_ma_factor)
self.selectors.append(week_selector)
self.selectors.append(day_selector)
def test_cross_ma():
factor = CrossMaFactor(entity_type='stock',
codes=['000338'],
start_timestamp='2019-01-01',
end_timestamp='2019-06-10',
level=IntervalLevel.LEVEL_1DAY,
provider='joinquant',
windows=[5,10])
print(factor.get_factor_df().tail())
print(factor.get_result_df().tail())
score = factor.get_result_df()['score']
assert score[('stock_sz_000338', '2019-06-03')] == True
assert score[('stock_sz_000338', '2019-06-04')] == True
assert ('stock_sz_000338', '2019-06-05') not in score or score[('stock_sz_000338', '2019-06-05')] == False
assert ('stock_sz_000338', '2019-06-06') not in score or score[('stock_sz_000338', '2019-06-06')] == False
assert ('stock_sz_000338', '2019-06-10') not in score or score[('stock_sz_000338', '2019-06-10')] == False
factor.move_on()
score = factor.get_result_df()['score']
assert score[('stock_sz_000338', '2019-06-17')] == True
def init_selectors(self, entity_ids, entity_schema, exchanges, codes,
start_timestamp, end_timestamp):
myselector = TargetSelector(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider='joinquant')
myselector.add_filter_factor(
CrossMaFactor(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
windows=[5, 10],
need_persist=False))
self.selectors.append(myselector)
def init_selectors(self, entity_ids, entity_schema, exchanges, codes,
start_timestamp, end_timestamp):
myselector = TargetSelector(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider='ccxt',
level=IntervalLevel.LEVEL_1MIN)
myselector.add_filter_factor(
CrossMaFactor(entity_ids=entity_ids,
entity_type=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
provider='ccxt',
level=IntervalLevel.LEVEL_1MIN))
self.selectors.append(myselector)
def test_cross_ma_selector():
entity_ids = ['stock_sz_000338']
entity_type = 'stock'
start_timestamp = '2018-01-01'
end_timestamp = '2019-06-30'
my_selector = TargetSelector(entity_ids=entity_ids,
entity_type=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp)
# add the factors
my_selector \
.add_filter_factor(CrossMaFactor(entity_ids=entity_ids,
entity_type=entity_type,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
computing_window=10,
windows=[5,10],
persist_factor=False,
level=IntervalLevel.LEVEL_1DAY))
my_selector.run()
print(my_selector.open_long_df)
print(my_selector.open_short_df)
assert 'stock_sz_000338' in my_selector.get_open_short_targets(
'2018-01-29')
from zvdata.utils.time_utils import now_pd_timestamp
from zvt.factors.ma.ma_factor import CrossMaFactor
from zvt.factors.target_selector import TargetSelector
my_selector = TargetSelector(start_timestamp='2018-10-01',
end_timestamp=now_pd_timestamp())
# add the factors
ma_factor = CrossMaFactor(start_timestamp='2018-10-01',
end_timestamp=now_pd_timestamp())
my_selector.add_filter_factor(ma_factor)
my_selector.run()
long_targets = my_selector.get_open_long_targets(timestamp='2019-11-11')
print(long_targets)
print(len(long_targets))