def init_selectors(self,
entity_ids,
entity_schema,
exchanges,
codes,
start_timestamp,
end_timestamp,
adjust_type=None):
start_timestamp = next_date(start_timestamp, -50)
# 周线策略
week_selector = TargetSelector(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=next_date(
start_timestamp, -200),
end_timestamp=end_timestamp,
long_threshold=0.7,
level=IntervalLevel.LEVEL_1WEEK,
provider='joinquant')
week_bull_factor = BullFactor(entity_ids=entity_ids,
entity_schema=entity_schema,
exchanges=exchanges,
codes=codes,
start_timestamp=next_date(
start_timestamp, -200),
end_timestamp=end_timestamp,
provider='joinquant',
level=IntervalLevel.LEVEL_1WEEK)
week_selector.add_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,
long_threshold=0.7,
level=IntervalLevel.LEVEL_1DAY,
provider='joinquant')
day_gold_cross_factor = GoldCrossFactor(
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)
day_selector.add_factor(day_gold_cross_factor)
# 同时使用日线,周线级别
self.selectors.append(day_selector)
self.selectors.append(week_selector)
def run(self):
# 按不同类别抓取
# 编码 基金运作方式
# 401001 开放式基金
# 401002 封闭式基金
# 401003 QDII
# 401004 FOF
# 401005 ETF
# 401006 LOF
for operate_mode_id in (401001, 401002, 401005):
year_count = 2
while True:
latest = Fund.query_data(
region=self.region,
filters=[Fund.operate_mode_id == operate_mode_id],
order=Fund.timestamp.desc(),
limit=1,
return_type='domain')
start_timestamp = '2000-01-01'
if latest:
start_timestamp = latest[0].timestamp
end_timestamp = min(
next_date(start_timestamp, 365 * year_count),
now_pd_timestamp(self.region))
df = jq_run_query(
table='finance.FUND_MAIN_INFO',
conditions=
f'operate_mode_id#=#{operate_mode_id}&start_date#>=#{to_time_str(start_timestamp)}&start_date#<=#{to_time_str(end_timestamp)}',
parse_dates=['start_date', 'end_date'],
dtype={'main_code': str})
if not pd_is_not_null(df) or (df['start_date'].max().year <
end_timestamp.year):
year_count = year_count + 1
if pd_is_not_null(df):
df.rename(columns={'start_date': 'timestamp'},
inplace=True)
df['timestamp'] = pd.to_datetime(df['timestamp'])
df['list_date'] = df['timestamp']
df['end_date'] = pd.to_datetime(df['end_date'])
df['code'] = df['main_code']
df['entity_id'] = df['code'].apply(
lambda x: to_entity_id(entity_type='fund', jq_code=x))
df['id'] = df['entity_id']
df['entity_type'] = 'fund'
df['exchange'] = 'sz'
df_to_db(df,
ref_df=None,
region=self.region,
data_schema=Fund,
provider=self.provider)
self.logger.info(
f'persist fund {operate_mode_id} list success {start_timestamp} to {end_timestamp}'
)
if is_same_date(end_timestamp, now_pd_timestamp(self.region)):
break
def run(self):
# 按不同类别抓取
# 编码 基金运作方式
# 401001 开放式基金
# 401002 封闭式基金
# 401003 QDII
# 401004 FOF
# 401005 ETF
# 401006 LOF
for operate_mode_id in (401001, 401002, 401005):
year_count = 2
while True:
latest = Fund.query_data(
filters=[Fund.operate_mode_id == operate_mode_id],
order=Fund.timestamp.desc(),
limit=1,
return_type="domain",
)
start_timestamp = "2000-01-01"
if latest:
start_timestamp = latest[0].timestamp
end_timestamp = min(
next_date(start_timestamp, 365 * year_count),
now_pd_timestamp())
df = run_query(
table="finance.FUND_MAIN_INFO",
conditions=
f"operate_mode_id#=#{operate_mode_id}&start_date#>=#{to_time_str(start_timestamp)}&start_date#<=#{to_time_str(end_timestamp)}",
parse_dates=["start_date", "end_date"],
dtype={"main_code": str},
)
if not pd_is_not_null(df) or (df["start_date"].max().year <
end_timestamp.year):
year_count = year_count + 1
if pd_is_not_null(df):
df.rename(columns={"start_date": "timestamp"},
inplace=True)
df["timestamp"] = pd.to_datetime(df["timestamp"])
df["list_date"] = df["timestamp"]
df["end_date"] = pd.to_datetime(df["end_date"])
df["code"] = df["main_code"]
df["entity_id"] = df["code"].apply(
lambda x: to_entity_id(entity_type="fund", jq_code=x))
df["id"] = df["entity_id"]
df["entity_type"] = "fund"
df["exchange"] = "sz"
df_to_db(df,
data_schema=Fund,
provider=self.provider,
force_update=self.force_update)
self.logger.info(
f"persist fund {operate_mode_id} list success {start_timestamp} to {end_timestamp}"
)
if is_same_date(end_timestamp, now_pd_timestamp()):
break
def eval_fetch_timestamps(self, entity, ref_record, http_session):
latest_timestamp = None
try:
if pd_is_not_null(ref_record):
time_field = self.get_evaluated_time_field()
latest_timestamp = ref_record[time_field].max(axis=0)
except Exception as e:
self.logger.warning(f'get ref record failed with error: {e}')
if not latest_timestamp:
latest_timestamp = entity.timestamp
if not latest_timestamp:
return self.start_timestamp, self.end_timestamp, self.default_size, None
now = now_pd_timestamp(self.region)
now_end = now.replace(hour=18, minute=0, second=0)
trade_day_index = 0
if len(self.trade_day) > 0:
if is_same_date(self.trade_day[trade_day_index], now) and now < now_end:
trade_day_index = 1
end = self.trade_day[trade_day_index]
else:
end = now
start_timestamp = next_date(latest_timestamp)
start = max(self.start_timestamp, start_timestamp) if self.start_timestamp else start_timestamp
if start >= end:
return start, end, 0, None
size = eval_size_of_timestamp(start_timestamp=start,
end_timestamp=end,
level=self.level,
one_day_trading_minutes=self.one_day_trading_minutes)
return start, end, size, None
self.selectors.append(day_selector)
self.selectors.append(week_selector)
if __name__ == '__main__':
start = '2019-01-01'
end = '2021-01-01'
trader_name = 'keep_run_trader'
clear_trader(trader_name=trader_name)
for time_interval in split_time_interval(start=start, end=end,
interval=40):
start_timestamp = time_interval[0]
end_timestamp = time_interval[-1]
# 成交量
vol_df = get_top_volume_entities(entity_type='stock',
start_timestamp=next_date(
start_timestamp, -50),
end_timestamp=start_timestamp,
pct=0.3)
# 机构重仓
ii_df = get_top_fund_holding_stocks(timestamp=start_timestamp,
pct=0.3,
by='trading')
current_entity_pool = list(
set(vol_df.index.tolist()) & set(ii_df.index.tolist()))
logger.info(
f'current_entity_pool({len(current_entity_pool)}):{current_entity_pool}'
)
trader = MultipleLevelTrader(start_timestamp=start_timestamp,
def report_top_stats(periods=[7, 30, 180, 365], ignore_new_stock=True):
latest_day: Stock1dHfqKdata = Stock1dHfqKdata.query_data(order=Stock1dHfqKdata.timestamp.desc(), limit=1,
return_type='domain')
current_timestamp = latest_day[0].timestamp
email_action = EmailInformer()
# 至少上市一年
filters = None
if ignore_new_stock:
pre_year = next_date(current_timestamp, -365)
stocks = get_entity_ids(provider='joinquant', entity_schema=Stock, filters=[Stock.timestamp <= pre_year])
filters = [Stock1dHfqKdata.entity_id.in_(stocks)]
stats = []
ups = []
downs = []
msg = ''
for period in periods:
start = next_date(current_timestamp, -period)
df, _ = get_top_performance_entities(start_timestamp=start, filters=filters, pct=1, show_name=True)
df.rename(columns={'score': f'score_{period}'}, inplace=True)
ups.append(tabulate(df.iloc[:50], headers='keys'))
downs.append(tabulate(df.iloc[:-100], headers='keys'))
stats.append(tabulate(df.describe(), headers='keys'))
# 最近一个月最靓仔的
if period == 30:
# add them to eastmoney
try:
try:
eastmoneypy.del_group('最靓仔')
except:
pass
eastmoneypy.create_group('最靓仔')
for entity_id in df.index[:50]:
_, _, code = decode_entity_id(entity_id)
eastmoneypy.add_to_group(code=code, group_name='最靓仔')
except Exception as e:
logger.exception(e)
email_action.send_message("*****@*****.**", f'report_top_stats error',
'report_top_stats error:{}'.format(e))
# 一年内没怎么动的
if period == 365:
stable_df = df[(df['score_365'] > -0.1) & (df['score_365'] < 0.1)]
vol_df = get_top_volume_entities(entity_ids=stable_df.index.tolist(), start_timestamp=start)
# add them to eastmoney
try:
try:
eastmoneypy.del_group('躺尸一年')
except:
pass
eastmoneypy.create_group('躺尸一年')
for entity_id in vol_df.index[:50]:
_, _, code = decode_entity_id(entity_id)
eastmoneypy.add_to_group(code=code, group_name='躺尸一年')
except Exception as e:
logger.exception(e)
email_action.send_message("*****@*****.**", f'report_top_stats error',
'report_top_stats error:{}'.format(e))
for s in stats:
msg = msg + s + '\n'
for up in ups:
msg = msg + up + '\n'
for down in downs:
msg = msg + down + '\n'
email_action.send_message('*****@*****.**', f'{current_timestamp} 统计报告', msg)
filters=[
StockActorSummary.report_date >= report_date,
StockActorSummary.actor_type == ActorType.raised_fund.value,
StockActorSummary.holding_ratio >= fund_ratio_nums
],
columns=['entity_id', 'holding_ratio', 'actor_type'],
)
# fund_cap_df = FundStock.query_data(filters=[FundStock.report_date >= report_date, FundStock.timestamp <= current_timestamp, FundStock.proportion >= 0.01],
# columns=['stock_id', 'market_cap', 'proportion'])
top_holding_stocks = fund_cap_df['entity_id'].tolist()
# 至少上市
least_start_day_nums = 60
filters = None
pre_date = next_date(current_timestamp, -least_start_day_nums)
stocks = get_entity_ids(provider='joinquant',
entity_schema=Stock,
filters=[Stock.timestamp <= pre_date])
filters = [Stock1dHfqKdata.entity_id.in_(stocks)]
# 任一rps 大于90
top_rps_stocks = []
rps_rank_limit = 1000
periods = [50, 120, 250]
for period in periods:
start = next_date(current_timestamp, -period)
updf, _ = get_top_performance_entities(start_timestamp=start,
filters=filters,
pct=1,
show_name=True)