def quant_stock(stock_number, stock_name, **kwargs):
qr_date = kwargs['qr_date']
if not pre_sdt_check(stock_number, **kwargs):
return
strategy_name = "depart_long_week"
last_trade_date = qr_date + datetime.timedelta(days=7)
swt = SWT.objects(
Q(stock_number=stock_number)
& Q(last_trade_date__lte=last_trade_date)).order_by(
'-last_trade_date')[:ema_volume]
use_ad_price, swt = is_ad_price(stock_number, qr_date, swt)
if not swt:
return
trading_data = format_trading_data(swt, use_ad_price)
df = calculate_macd(DataFrame(trading_data), short_ema, long_ema, dif_ema)
df = calculate_ma(df, short_ma, long_ma)
this_week = df.iloc[-1]
last_week = df.iloc[-2]
if last_week['close_price'] < last_week['long_ma'] and this_week['close_price'] > this_week['short_ma']\
and this_week['close_price'] > this_week['long_ma']:
if use_ad_price:
init_price = swt[0].weekly_close_price
else:
init_price = this_week['close_price']
increase_rate = round(
(this_week['close_price'] - last_week['close_price']) /
last_week['close_price'], 4) * 100
short_point = -1
for i in range(1, len(df)):
if df.iloc[-i].diff_ma > 0:
short_point = i
break
# if short_point < period:
# return
if df.iloc[-short_point:].macd.sum() > 0:
# print(stock_number)
# pd.set_option('display.max_columns', 500)
# pd.set_option('display.width', 1000)
# print(df.iloc[-short_point:])
qr = QR(stock_number=stock_number,
stock_name=stock_name,
date=qr_date,
strategy_direction='long',
strategy_name=strategy_name,
init_price=init_price,
industry_involved=kwargs.get('industry_involved'),
increase_rate=increase_rate)
if not check_duplicate_strategy(qr):
qr.save()
return qr
def quant_stock(stock_number, stock_name, **kwargs):
short_ma = kwargs['short_ma']
long_ma = kwargs['long_ma']
qr_date = kwargs['qr_date']
if not pre_sdt_check(stock_number, **kwargs):
return
if short_ma < long_ma:
strategy_direction = 'long'
quant_count = long_ma + 5
else:
strategy_direction = 'short'
quant_count = short_ma + 5
strategy_name = 'week_through_%s_%s_%s' % (strategy_direction, short_ma,
long_ma)
last_trade_date = qr_date + datetime.timedelta(days=7)
swt = SWT.objects(
Q(stock_number=stock_number)
& Q(last_trade_date__lte=last_trade_date)).order_by(
'-last_trade_date')[:quant_count]
use_ad_price, swt = is_ad_price(stock_number, qr_date, swt)
if not swt:
return
trading_data = format_trading_data(swt, use_ad_price)
# end_date = qr_date.strftime('%Y-%m-%d')
# start_date = (qr_date - datetime.timedelta(days=max(short_ma, long_ma) * 7)).strftime('%Y-%m-%d')
# trading_data = get_week_trading(stock_number, start_date, end_date)
df = calculate_ma(DataFrame(trading_data), short_ma, long_ma)
this_week = df.iloc[-1]
last_week = df.iloc[-2]
if last_week['close_price'] < last_week['long_ma'] and this_week['close_price'] > this_week['short_ma']\
and this_week['close_price'] > this_week['long_ma']:
if use_ad_price:
init_price = swt[0].weekly_close_price
else:
init_price = this_week['close_price']
increase_rate = round(
(this_week['close_price'] - last_week['close_price']) /
last_week['close_price'], 4) * 100
qr = QR(stock_number=stock_number,
stock_name=stock_name,
date=qr_date,
strategy_direction=strategy_direction,
strategy_name=strategy_name,
init_price=init_price,
industry_involved=kwargs.get('industry_involved'),
increase_rate=increase_rate)
if not check_duplicate_strategy(qr):
qr.save()
return qr
return
def quant_stock(stock_number, stock_name, **kwargs):
short_ma = kwargs['short_ma']
long_ma = kwargs['long_ma']
qr_date = kwargs['qr_date']
if not pre_sdt_check(stock_number, **kwargs):
return
if short_ma < long_ma:
strategy_direction = 'long'
quant_count = long_ma + 5
else:
strategy_direction = 'short'
quant_count = short_ma + 5
strategy_name = 'maweek_%s_%s_%s' % (strategy_direction, short_ma, long_ma)
swt = SWT.objects(
Q(stock_number=stock_number)
& Q(last_trade_date__lte=qr_date)).order_by(
'-last_trade_date')[:quant_count]
if not swt:
return
use_ad_price, swt = is_ad_price(stock_number, qr_date, swt)
if not swt:
return
trading_data = format_trading_data(swt, use_ad_price)
df = calculate_ma(DataFrame(trading_data), short_ma, long_ma)
this_week = df.iloc[-1]
last_week = df.iloc[-2]
if this_week['diff_ma'] > 0 > last_week['diff_ma']:
if use_ad_price:
init_price = swt[0].weekly_close_price
else:
init_price = this_week['close_price']
increase_rate = round(
(this_week['close_price'] - last_week['close_price']) /
last_week['close_price'], 4) * 100
qr = QR(stock_number=stock_number,
stock_name=stock_name,
date=this_week.name,
strategy_direction=strategy_direction,
strategy_name=strategy_name,
init_price=init_price,
industry_involved=kwargs.get('industry_involved'),
increase_rate=increase_rate)
if not check_duplicate_strategy(qr):
qr.save()
return qr
return
def quant_stock(stock_number, stock_name, **kwargs):
short_ema = kwargs['short_ema']
long_ema = kwargs['long_ema']
dif_ema = kwargs['dif_ema']
qr_date = kwargs['qr_date']
if not pre_sdt_check(stock_number, **kwargs):
return
strategy_direction = 'long'
quant_count = 150
strategy_name = 'week_macd_%s_%s_%s_%s' % (strategy_direction, short_ema,
long_ema, dif_ema)
last_trade_date = qr_date + datetime.timedelta(days=7)
swt = SWT.objects(
Q(stock_number=stock_number)
& Q(last_trade_date__lte=last_trade_date)).order_by(
'-last_trade_date')[:quant_count]
use_ad_price, swt = is_ad_price(stock_number, qr_date, swt)
if not swt:
return
trading_data = format_trading_data(swt, use_ad_price)
df = calculate_macd(DataFrame(trading_data), short_ema, long_ema, dif_ema)
this_week = df.iloc[-1]
last_week = df.iloc[-2]
if last_week['macd'] < 0 < this_week['macd']:
if use_ad_price:
init_price = swt[0].weekly_close_price
else:
init_price = this_week['close_price']
increase_rate = round(
(this_week['close_price'] - last_week['close_price']) /
last_week['close_price'], 4) * 100
qr = QR(stock_number=stock_number,
stock_name=stock_name,
date=qr_date,
strategy_direction=strategy_direction,
strategy_name=strategy_name,
init_price=init_price,
industry_involved=kwargs.get('industry_involved'),
increase_rate=increase_rate)
if not check_duplicate_strategy(qr):
qr.save()