def test_talib_ATR(self):
#
# code_name = ('300623', '捷捷微电')
# code_name = ('600145', '*ST新亿')
# code_name = ('601700', '风范股份')
# code_name = ('000725', '京东方Ａ')
# code_name = ('002157', '正邦科技')
code_name = ('300663', '科蓝软件')
end = '2020-12-30'
data = utils.read_data(code_name)
print(data.head())
result = enter.check_volume(code_name, data, end_date=end)
print("\nlow atr check {0}'s result: {1}".format(code_name, result))
rolling_window = 21
moving_average = 20
average_true_range = ATR(data.high.values[-rolling_window:],
data.low.values[-rolling_window:],
data.close.values[-rolling_window:],
timeperiod=moving_average)
print("*" * 50)
print(data['high'].values)
print("*" * 50)
print(average_true_range)
print("*" * 10)
def end_date_filter(code_name):
stock = code_name[0]
name = code_name[1]
data = utils.read_data(stock, name)
if data is None:
return False
return \
enter.check_ma(stock, data, end_date=end_date) \
and enter.check_max_price(stock, data, end_date=end_date) \
and enter.check_volume(code_name, data, end_date=end_date)
def end_date_filter(code_name):
stock = code_name[0]
data = utils.read_data(code_name)
result = enter.check_ma(stock, data, end_date=end_date) \
and enter.check_volume(stock, data, end_date=end_date)
if result:
message = turtle_trade.calculate(code_name, data)
logging.info("{0} {1}".format(code_name, message))
notify.notify("{0} {1}".format(code_name, message))
return result
def check(code_name, data, end_date=None, threshold=60):
origin_data = data
if len(data) < 250:
logging.info("{0}:样本小于250天...\n".format(code_name))
return
data['ma60'] = pd.Series(tl.MA(data['close'].values, 60),
index=data.index.values)
begin_date = data.iloc[0].date
if end_date is not None:
if end_date < begin_date: # 该股票在end_date时还未上市
logging.info("{}在{}时还未上市".format(code_name, end_date))
return False
if end_date is not None:
mask = (data['date'] <= end_date)
data = data.loc[mask]
data = data.tail(n=threshold)
breakthrough_row = None
for index, row in data.iterrows():
if row['open'] < row['ma60'] <= row['close']:
if enter.check_volume(code_name, origin_data, row['date'],
threshold):
breakthrough_row = row
if breakthrough_row is None:
return False
data_front = data.loc[(data['date'] < breakthrough_row['date'])]
data_end = data.loc[(data['date'] >= breakthrough_row['date'])]
for index, row in data_front.iterrows():
if not (-0.05 < (row['ma60'] - row['close']) / row['ma60'] < 0.2):
return False
logging.info("股票{0} 突破日期：{1}".format(code_name, breakthrough_row['date']))
return True
#
# average_true_range = average_true_range_list[-1]
#
settings.init()
# code_name = ('300623', '捷捷微电')
# code_name = ('600145', '*ST新亿')
# code_name = ('601700', '风范股份')
# code_name = ('000725', '京东方Ａ')
code_name = ('002157', '正邦科技')
# code_name = ('300663', '科蓝软件')
# end = '2017-09-26'
end = '2019-02-15'
data = utils.read_data(code_name)
# print(data)
result = enter.check_volume(code_name, data, end_date=end)
print("low atr check {0}'s result: {1}".format(code_name, result))
#
# rolling_window = 21
# moving_average = 20
#
# average_true_range = ATR(
# data.high.values[-rolling_window:],
# data.low.values[-rolling_window:],
# data.close.values[-rolling_window:],
# timeperiod=moving_average
# )
# print(data['high'].values)
#
# print(average_true_range)
