def cal_dcf(result_list: list, daily_store: mq_daily_store.MqDailyStore, quarter_store: mq_quarter_store.MqQuarterStore,
dcf_service: MqDcfService, ts_code: str, update_date: str):
'''
根据自由现金流估算市值
'''
call_add = partial(common_add, result_list=result_list, store=daily_store)
fcf = quarter_store.find_latest(ts_code, mq_quarter_metric_enum.fcf_ltm.name, update_date)
mv_10, mv = 0, 0
report_type = mq_report_type.report
period = '20000331'
if fcf is not None:
year = int(fcf.period[0:4])
report_type = fcf.report_type
period = fcf.period
mv_10, mv = dcf_service.cal_dcf(fcf.value, year, update_date)
else:
log.error('Cant find fcf %s %s' % (ts_code, update_date))
daily_mv_10 = MqDailyMetric(ts_code=ts_code, report_type=report_type, period=period, update_date=update_date,
name=mq_daily_metric_enum.mv_10.name, value=mv_10)
daily_mv = MqDailyMetric(ts_code=ts_code, report_type=report_type, period=period, update_date=update_date,
name=mq_daily_metric_enum.mv.name, value=mv)
call_add(to_add=daily_mv_10)
call_add(to_add=daily_mv)
def cal(daily_store: mq_daily_store.MqDailyStore,
quarter_store: mq_quarter_store.MqQuarterStore,
ts_code: str, update_date: str) -> MqDailyMetric:
score = 0
peg = 0
report_type = 0
period = '00000000'
pe: MqDailyMetric = daily_store.find_date_exact(ts_code, mq_daily_metric_enum.pe.name, update_date)
dprofit_quarter = quarter_store.find_latest(ts_code, mq_quarter_metric_enum.dprofit_quarter.name, update_date)
dprofit_quarter_ly = quarter_store.find_period_latest(
ts_code, mq_quarter_metric_enum.dprofit_quarter.name,
period=date_utils.period_delta(dprofit_quarter.period, -1),
update_date=update_date) if dprofit_quarter is not None else None
dprofit_ltm = quarter_store.find_latest(ts_code, mq_quarter_metric_enum.dprofit_ltm.name, update_date)
if pe is None or dprofit_quarter is None or dprofit_quarter_ly is None or dprofit_ltm is None:
score = -1
elif calculate.gt(pe, max_pe, field='value') or calculate.lt(pe, zero, field='value'):
score = -1
elif calculate.lt(dprofit_quarter, zero, field='value') or calculate.lt(dprofit_quarter, min_yoy, field='yoy'):
score = -1
elif calculate.lt(dprofit_quarter_ly, min_dprofit, field='value'):
score = -1
elif calculate.lt(dprofit_ltm, zero, field='value') or \
calculate.lt(decimal_utils.div(dprofit_quarter.value, dprofit_ltm.value), min_dprofit_percent):
score = -1
else:
peg = decimal_utils.div(decimal_utils.div(pe.value, dprofit_quarter.yoy), 100)
report_type = pe.report_type | dprofit_quarter.report_type
period = max(pe.period, dprofit_quarter.period)
if peg > max_peg:
score = -1
else:
score = (1 - peg / max_peg) * 100
peg_metric = MqDailyMetric(ts_code=ts_code, report_type=report_type,
period=period, update_date=update_date,
name=mq_daily_metric_enum.peg.name,
value=peg)
grow_score_metric = MqDailyMetric(ts_code=ts_code, report_type=report_type,
period=period, update_date=update_date,
name=mq_daily_metric_enum.grow_score.name,
value=valid_score(score))
return [peg_metric, grow_score_metric]
def qd_dividend(call_add: partial, call_log: partial, i1: MqQuarterMetric, i2: MqDailyMetric, name: str):
if i1 is None or i2 is None:
call_log(name=name)
return None
else:
to_add = MqDailyMetric(ts_code=i1.ts_code, report_type=i1.report_type | i2.report_type,
period=i1.period, update_date=i2.update_date,
name=name, value=decimal_utils.div(i1.value, i2.value))
call_add(to_add=to_add)
return to_add
def add_nx(ts_code: str, report_type: int, period: str, update_date: str,
name: str, value: Decimal,
result_list: list, store: mq_daily_store.MqDailyStore):
if value is None:
return
exist = store.find_date_exact(ts_code, name, period)
if exist is not None:
return
to_add = MqDailyMetric(ts_code=ts_code, report_type=(1 << report_type), period=period, update_date=update_date,
name=name, value=value)
common_add(result_list, store, to_add)
def add_trade_status(
result_list: dict(type=list, help="需要插入结果的列表"),
store: dict(type=mq_daily_store.MqDailyStore, help="日指标存放"),
ts_code: dict(type=str, help="股票编码"),
now_date: dict(type=str, help="日期"),
is_suspend: dict(type=int, help="是否停牌")):
"""
记录这天是否停牌
"""
to_add = MqDailyMetric(ts_code=ts_code, report_type=mq_report_type.none_report_type,
period='-', update_date=now_date,
name=mq_daily_metric_enum.suspend.name, value=is_suspend)
common_add(result_list, store, to_add)
def copy_for_suspend(
result_list: dict(type=list, help="需要插入结果的列表"),
store: dict(type=mq_daily_store.MqDailyStore, help="日指标存放"),
ts_code: dict(type=str, help="股票编码"),
now_date: dict(type=str, help="日期")):
"""
针对停牌日，从上一个交易日复制
"""
for i in mq_daily_metric_enum.copy_for_suspend:
now = store.find_date_exact(ts_code, i.name, now_date)
if now is not None:
continue
yesterday = store.find_latest(ts_code, i.name, now_date)
if yesterday is None:
log.error('Cant find latest daily data of %s %s to copy for non-trade-day' % (ts_code, now_date))
else:
to_add = MqDailyMetric(ts_code=yesterday.ts_code, report_type=yesterday.report_type,
period=yesterday.period, update_date=now_date,
name=yesterday.name, value=yesterday.value)
common_add(result_list, store, to_add)
def cal(daily_store: mq_daily_store.MqDailyStore,
quarter_store: mq_quarter_store.MqQuarterStore, ts_code: str,
update_date: str) -> MqDailyMetric:
daily_find = partial(daily_store.find_date_exact,
ts_code=ts_code,
update_date=update_date)
quarter_find = partial(quarter_store.find_latest,
ts_code=ts_code,
update_date=update_date)
score = -1
period = '00000000'
dividend_yields = daily_find(
name=mq_daily_metric_enum.dividend_yields.name)
risk_point = quarter_find(name=mq_quarter_metric_enum.risk_point.name)
revenue_quarter = quarter_find(
name=mq_quarter_metric_enum.revenue_quarter.name)
dprofit_quarter = quarter_find(
name=mq_quarter_metric_enum.dprofit_quarter.name)
if dividend_yields is None or \
calculate.gt(risk_point, 0, 'value', True) or \
calculate.lt(dividend_yields, 0.03, 'value', True) or \
not earn_and_dividend_in_year(quarter_store, ts_code, dividend_yields.period, update_date, 5) or \
not earn_in_period(quarter_store, ts_code, dividend_yields.period, update_date, 4) or \
calculate.lt(revenue_quarter, max_desc_yoy, 'yoy', True) or \
calculate.lt(revenue_quarter, dprofit_quarter, 'yoy', True):
score = -1
else:
period = dividend_yields.period
pe = daily_find(name=mq_daily_metric_enum.pe.name)
pb = daily_find(name=mq_daily_metric_enum.pb.name)
dividend_score = decimal_utils.mul(dividend_yields.value,
Decimal(1000)) # * 100 / 10 * 100
pe_score = decimal_utils.valid_score((1 - decimal_utils.div(
calculate.get_val(pe, 'value', max_pe), max_pe, err_default=0)) *
100)
pb_score = decimal_utils.valid_score((1 - decimal_utils.div(
calculate.get_val(pb, 'value', max_pb), max_pb, err_default=0)) *
100)
pepb_score = decimal_utils.valid_score((1 - decimal_utils.div(
decimal_utils.mul(calculate.get_val(pe, 'value', max_pe),
calculate.get_val(pb, 'value', max_pb)),
max_pepb)) * 100)
profit_yoy_score = history_profit_yoy_score(quarter_store, ts_code,
dividend_yields.period,
update_date, 5)
dividend_yoy_score = history_dividend_yoy_score(
quarter_store, ts_code, dividend_yields.period, update_date, 5)
if profit_yoy_score == 0 or dividend_yoy_score == 0:
score = 0
elif pe_score == 0 and pb_score == 0 and pepb_score == 0:
score = 0
else:
score = decimal_utils.add(
decimal_utils.mul(dividend_score, 0.3),
decimal_utils.mul(dividend_yoy_score, 0.2),
decimal_utils.mul((pe_score + pb_score + pepb_score), 0.1),
decimal_utils.mul(profit_yoy_score, 0.2))
val_score_metric = MqDailyMetric(ts_code=ts_code,
report_type=mq_report_type.mq_predict,
period=period,
update_date=update_date,
name=mq_daily_metric_enum.val_score.name,
value=decimal_utils.valid_score(score))
return [val_score_metric]
def find_latest(self, ts_code: str, name: str,
update_date: str) -> MqDailyMetric:
tree = self.get_tree(ts_code, name)
max_to_find = MqDailyMetric(update_date=update_date)
target = tree.find_max_under(max_to_find)
return self.val(target)