def strategy_statistics(strategy_name, strategy_count, stock_model=''):
all_qr = QR.objects(strategy_name=strategy_name)
if not all_qr:
print('Wrong Strategy Name!')
return
trading_date = QR.objects().distinct('date')
trading_date.sort()
trading_date = trading_date[0 - strategy_count:]
bt_result = {}
for d in trading_date:
bt_result[str(d.date())] = back_test_success(strategy_name, d,
stock_model)
frame = DataFrame(bt_result)
pd.set_option('display.width', 200)
pd.set_option('display.max_rows', strategy_count + 100)
print(
frame.reindex([
'count', 'one_back_test', 'one_yield', 'three_back_test',
'three_yield', 'five_back_test', 'five_yield', 'ten_back_test',
'ten_yield'
]).T)
pd.set_option('display.width', None)
pd.set_option('display.max_rows', None)
def back_test_success(strategy_name, date, stock_model=''):
if stock_model:
cursor = QR.objects(
Q(strategy_name=strategy_name) & Q(date=date)
& Q(stock_number__startswith=stock_model))
else:
cursor = QR.objects(Q(strategy_name=strategy_name) & Q(date=date))
res_by_date = {}
for k, v in back_test_attr.iteritems():
qualified_sample = [qr for qr in cursor if qr[k] is not None]
if not qualified_sample:
res_by_date['count'] = cursor.count()
continue
succ_sample = [q for q in qualified_sample if q[k] is True]
res_by_date[k] = str(
round(float(len(succ_sample)) / float(len(qualified_sample)), 4) *
100) + '%'
yield_exp = 0.0
if 'long' in strategy_name:
for i in qualified_sample:
yield_exp += (i[v[0]] - i.init_price) / i.init_price
elif 'short' in strategy_name:
for i in qualified_sample:
yield_exp += (i.init_price - i[v[0]]) / i.init_price
res_by_date[v[1]] = str(
round(yield_exp / len(qualified_sample), 4) * 100) + '%'
res_by_date['count'] = cursor.count()
return res_by_date
def back_test_success(strategy_name, date):
cursor = QR.objects(Q(strategy_name=strategy_name) & Q(date=date))
res_by_date = {}
for k, v in back_test_attr.iteritems():
qualified_sample = [qr for qr in cursor if qr[k] is not None]
if not qualified_sample:
continue
succ_sample = [q for q in qualified_sample if q[k] is True]
res_by_date[k] = str(
round(float(len(succ_sample)) / float(len(qualified_sample)), 4) *
100) + '%'
yield_expectation = 0.0
if 'long' in strategy_name:
for i in qualified_sample:
yield_expectation += (i[v[0]] - i.init_price) / i.init_price
elif 'short' in strategy_name:
for i in qualified_sample:
yield_expectation += (i.init_price - i[v[0]]) / i.init_price
res_by_date[v[1]] = str(
round(yield_expectation / len(qualified_sample), 4) * 100) + '%'
return res_by_date
def strategy_statistics(strategy_name):
all_qr = QR.objects(strategy_name=strategy_name)
if not all_qr:
print "Wrong Strategy Name!"
return
trading_date = SDT.objects(stock_number__startswith="300").distinct("date")
trading_date.sort()
bt_result = {}
for d in trading_date:
bt_result[str(d.date())] = back_test_success(strategy_name, d)
frame = DataFrame(bt_result)
pd.set_option("display.width", 200)
pd.set_option("display.max_rows", 400)
print frame.reindex(
[
"count",
"one_back_test",
"one_yield_expectation",
"three_back_test",
"three_yield_expectation",
"five_back_test",
"five_yield_expectation",
]
).T
pd.set_option("display.width", None)
pd.set_option("display.max_rows", None)
def check_duplicate(stock_number, date, strategy_name):
cursor = QR.objects(Q(stock_number=stock_number) & Q(date=date) & Q(strategy_name=strategy_name))
if cursor:
return True
else:
return False
def is_duplicate(stock_number, date, strategy_name):
try:
cursor = QR.objects(
Q(stock_number=stock_number) & Q(date=date)
& Q(strategy_name=strategy_name))
except Exception, e:
logging.error('Query %s QR failed:%s' % (stock_number, e))
def check_duplicate(stock_number, date, strategy_name):
cursor = QR.objects(
Q(stock_number=stock_number) & Q(date=date)
& Q(strategy_name=strategy_name))
if cursor:
return True
else:
return False
def back_testing():
quant_result = QR.objects()
for i in quant_result:
for t in test_pattern:
if i[test_pattern[t]['test']] is None and i[test_pattern[t]['price']] is None:
try:
test_by_day(i, t)
except Exception, e:
logging.error('Error occur when back testing %s: %s' % (i.stock_number, e))
def strategy_statistics(strategy_name, strategy_count):
all_qr = QR.objects(strategy_name=strategy_name)
if not all_qr:
print 'Wrong Strategy Name!'
return
trading_date = QR.objects().distinct('date')
trading_date.sort()
trading_date = trading_date[0-strategy_count:]
bt_result = {}
for d in trading_date:
bt_result[str(d.date())] = back_test_success(strategy_name, d)
frame = DataFrame(bt_result)
pd.set_option('display.width', 200)
pd.set_option('display.max_rows', 2000)
print frame.reindex(['count', 'one_back_test', 'one_yield_expectation', 'three_back_test', 'three_yield_expectation',
'five_back_test', 'five_yield_expectation']).T
pd.set_option('display.width', None)
pd.set_option('display.max_rows', None)
def check_duplicate(qr):
if isinstance(qr, QR):
try:
cursor = QR.objects(Q(stock_number=qr.stock_number) & Q(strategy_name=qr.strategy_name) &
Q(date=qr.date))
except Exception, e:
logging.error('Error when check dupliate %s strategy %s date %s: %s' % (qr.stock_number, qr.strategy_name,
qr.date, e))
if cursor:
return True
else:
return False
def check_duplicate_strategy(qr):
if isinstance(qr, QR):
try:
cursor = QR.objects(Q(stock_number=qr.stock_number) & Q(strategy_name=qr.strategy_name) &
Q(date=qr.date))
except Exception, e:
logging.error('Error when check dupliate %s strategy %s date %s: %s' % (qr.stock_number, qr.strategy_name,
qr.date, e))
if cursor:
return True
else:
return False
def generate_statement():
today = datetime.date.today()
quant_res = QR.objects(date=today)
if not quant_res:
return
file_name = today.strftime('%Y-%m-%d') + '.txt'
strategy_li = []
for i in quant_res:
if i.strategy_name not in strategy_li:
strategy_li.append(i.strategy_name)
current_path = dirname(abspath(__file__))
for s in strategy_li:
strategy_path = join(current_path, s)
if not isdir(strategy_path):
mkdir(strategy_path)
file_path = join(strategy_path, file_name)
if exists(file_path):
continue
with codecs.open(file_path, 'w+', 'utf-8') as fd:
fd.write('-------------%s-------------\n' % str(QR.objects(Q(strategy_name=s) & Q(date=today)).count()))
for i in trade_sector:
cursor = QR.objects(Q(strategy_name=s) & Q(date=today) &
Q(stock_number__startswith=i['market_code'])).order_by('stock_number')
fd.write(u'-----------%s--%s-----------\n' % (i['market_name'], cursor.count()))
for j in cursor:
fd.write('%s %s %s\n' % (j.stock_number, j.stock_name, j.init_price))
chdir(current_path)
system('git add -A')
system("git commit -m \'" + today.strftime('%Y-%m-%d') + " statement\'")
system('git push origin')
time.sleep(10)
system('git push origin')
def strategy_statistics(strategy_name):
all_qr = QR.objects(strategy_name=strategy_name)
if not all_qr:
print 'Wrong Strategy Name!'
return
trading_date = SDT.objects(stock_number__startswith='300').distinct('date')
trading_date.sort()
bt_result = {}
for d in trading_date:
bt_result[str(d.date())] = back_test_success(strategy_name, d)
frame = DataFrame(bt_result)
pd.set_option('display.width', 200)
pd.set_option('display.max_rows', 200)
print frame.reindex([
'count', 'one_back_test', 'one_yield_expectation', 'three_back_test',
'three_yield_expectation', 'five_back_test', 'five_yield_expectation'
]).T
pd.set_option('display.width', None)
pd.set_option('display.max_rows', None)
def strategy_statistics(strategy_name):
all_qr = QR.objects(strategy_name=strategy_name)
if not all_qr:
print 'Wrong Strategy Name!'
return
all_date = []
for i in all_qr:
if i.date not in all_date:
all_date.append(i.date)
all_date.sort()
bt_result = {}
for d in all_date:
bt_result[str(d.date())] = back_test_success(strategy_name, d)
frame = DataFrame(bt_result)
pd.set_option('display.width', 200)
print frame.reindex(['one_back_test', 'one_yield_expectation', 'three_back_test', 'three_yield_expectation',
'five_back_test', 'five_yield_expectation']).T
pd.set_option('display.width', None)
def back_test_success(strategy_name, date):
cursor = QR.objects(Q(strategy_name=strategy_name) & Q(date=date))
res_by_date = {}
for k, v in back_test_attr.iteritems():
qualified_sample = [qr for qr in cursor if qr[k] is not None]
if not qualified_sample:
continue
succ_sample = [q for q in qualified_sample if q[k] is True]
res_by_date[k] = str(round(float(len(succ_sample))/float(len(qualified_sample)), 4) * 100) + '%'
yield_expectation = 0.0
if 'long' in strategy_name:
for i in qualified_sample:
yield_expectation += (i[v[0]] - i.init_price)/i.init_price
elif 'short' in strategy_name:
for i in qualified_sample:
yield_expectation += (i.init_price - i[v[0]])/i.init_price
res_by_date[v[1]] = str(round(yield_expectation/len(qualified_sample), 4) * 100) + '%'
return res_by_date
def strategy_statistics(strategy_name):
all_qr = QR.objects(strategy_name=strategy_name)
if not all_qr:
print 'Wrong Strategy Name!'
return
all_date = []
for i in all_qr:
if i.date not in all_date:
all_date.append(i.date)
all_date.sort()
bt_result = {}
for d in all_date:
bt_result[str(d.date())] = back_test_success(strategy_name, d)
frame = DataFrame(bt_result)
pd.set_option('display.width', 200)
print frame.reindex([
'one_back_test', 'one_yield_expectation', 'three_back_test',
'three_yield_expectation', 'five_back_test', 'five_yield_expectation'
]).T
pd.set_option('display.width', None)
def is_duplicate(stock_number, date, strategy_name):
try:
cursor = QR.objects(Q(stock_number=stock_number) & Q(date=date) & Q(strategy_name=strategy_name))
except Exception, e:
logging.error("Query %s QR failed:%s" % (stock_number, e))
