def stock(code):
stock = db.stock_by_code(code)
filters = db.all_filters()
return render_template('stock_detail.html',
VERSION=VERSION,
stock=stock,
filters=filters)
def stocks_new_filter():
filters = db.all_filters()
name = '새필터' + str(len(filters) + 1)
filter_id = db.save_filter({
'name': name,
'options': [],
})
return redirect(url_for('stocks', filter_id=filter_id))
def etfs(etf_type='domestic'):
momentum_base = 'month3' if etf_type == 'domestic' else 'month6'
momentum_base_kr = '3개월' if etf_type == 'domestic' else '6개월'
order_by = request.args.get('order_by', momentum_base)
ordering = request.args.get('ordering', 'desc')
etfs = db.all_etf(order_by=order_by, ordering=ordering, etf_type=etf_type)
bond_etfs = ['148070', '152380']
tags = defaultdict(list)
for etf in etfs:
for tag in etf.get('tags'):
tags[tag].append(etf)
tags = {k: ETFTag(k, v) for k, v in tags.items()}
stat = {}
etfs_by_momentum_base = [
etf for etf in db.all_etf(
order_by=momentum_base, ordering='desc', etf_type=etf_type)
if etf[momentum_base] != 0
]
no_bond_etfs = sorted(
[etf for etf in etfs_by_momentum_base if etf['code'] not in bond_etfs],
key=lambda x: x.get(momentum_base, 0),
reverse=True)
stat['absolute_momentum_momentum_base_avg'] = mean_or_zero(
[etf[momentum_base] for etf in no_bond_etfs])
stat['absolute_momentum_high'] = no_bond_etfs[0]
stat['relative_momentum_etf'] = etfs_by_momentum_base[0]
tags = sorted(tags.values(),
key=lambda t: getattr(t, momentum_base),
reverse=True)
filters = db.all_filters()
return render_template('etfs.html',
VERSION=VERSION,
INTEREST=INTEREST,
filters=filters,
etfs=etfs,
order_by=order_by,
ordering=ordering,
stat=stat,
tags=tags,
etf_type=etf_type,
momentum_base=momentum_base,
momentum_base_kr=momentum_base_kr)
def stocks(status=None, filter_id=None):
find = None
filter_fscore = False
stat = {}
if status == 'starred':
find = {'starred': True}
elif status == 'owned':
find = {'owned': True}
elif status == 'starredorowned':
find = {'$or': [{'starred': True}, {'owned': True}]}
elif status == 'doubtful':
find = {'doubtful': True}
elif status == 'fscore':
filter_fscore = True
order_by = request.args.get('order_by', 'expected_rate')
ordering = request.args.get('ordering', 'desc')
filters = db.all_filters()
current_filter = None
if filter_id:
current_filter = db.filter_by_id(filter_id)
stocks = db.all_stocks(order_by=order_by,
ordering=ordering, find=find,
filter_by_expected_rate=find==None,
filter_bad=status!='bad',
filter_fscore=filter_fscore,
filter_options=(current_filter.filter_options if current_filter else []))
if status in ['owned', 'starred', 'starredorowned']:
stat['low_pbr'] = len([stock for stock in stocks if stock.pbr <= 1])
stat['high_expected_rate'] = len([stock for stock in stocks if stock.expected_rate >= 15])
stat['fscore'] = len([stock for stock in stocks if stock.latest_fscore >= 3])
stat['mean_expected_rate'] = mean_or_zero([stock.expected_rate for stock in stocks])
stat['mean_expected_rate_by_low_pbr'] = mean_or_zero([stock.expected_rate_by_low_pbr for stock in stocks])
stat['mean_future_roe'] = mean_or_zero([stock.future_roe for stock in stocks])
qROE_numbers = [stock.QROEs[0][1] for stock in stocks if len(stock.QROEs) > 0]
qROE_numbers = [float(roe_number) for roe_number in qROE_numbers if roe_number]
stat['mean_qROEs'] = mean_or_zero(qROE_numbers)
stat['qROEs_count'] = len(qROE_numbers)
return render_template('stocks.html', stocks=stocks, order_by=order_by, ordering=ordering, status=status,
available_filter_options=db.available_filter_options, filters=filters,
current_filter=current_filter, stat=stat)
