[update] 天勤tick回测
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msincenselee
parent
a7775d5124
commit
09b57bbd7d
@ -30,12 +30,22 @@ from vnpy.trader.constant import (
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)
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from vnpy.trader.utility import (
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get_trading_date,
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extract_vt_symbol,
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get_underlying_symbol,
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get_trading_date,
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import_module_by_str
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)
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from .back_testing import BackTestingEngine
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# vnpy交易所，与淘宝数据tick目录得对应关系
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VN_EXCHANGE_TICKFOLDER_MAP = {
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Exchange.SHFE.value: 'SQ',
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Exchange.DCE.value: 'DL',
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Exchange.CZCE.value: 'ZZ',
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Exchange.CFFEX.value: 'ZJ',
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Exchange.INE.value: 'SQ'
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}
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class PortfolioTestingEngine(BackTestingEngine):
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"""
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@ -57,6 +67,8 @@ class PortfolioTestingEngine(BackTestingEngine):
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self.bar_interval_seconds = 60 # bar csv文件，属于K线类型，K线的周期（秒数）,缺省是1分钟
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self.tick_path = None # tick级别回测， 路径
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self.use_tq = False # True:使用tq csv数据; False:使用淘宝购买的csv数据(19年之前)
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self.use_pkb2 = True # 使用tdx下载的逐笔成交数据（pkb2压缩格式），模拟tick
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def load_bar_csv_to_df(self, vt_symbol, bar_file, data_start_date=None, data_end_date=None):
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"""加载回测bar数据到DataFrame"""
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@ -144,6 +156,11 @@ class PortfolioTestingEngine(BackTestingEngine):
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self.output('portfolio prepare_env')
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super().prepare_env(test_setting)
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self.use_tq = test_setting.get('use_tq', False)
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self.use_pkb2 = test_setting.get('use_pkb2', True)
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if self.use_tq:
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self.use_pkb2 = False
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def prepare_data(self, data_dict):
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"""
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准备组合数据
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@ -345,6 +362,138 @@ class PortfolioTestingEngine(BackTestingEngine):
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traceback.print_exc()
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return
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def load_csv_file(self, tick_folder, vt_symbol, tick_date):
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"""从文件中读取tick，返回list[{dict}]"""
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# 使用天勤tick数据
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if self.use_tq:
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return self.load_tq_csv_file(tick_folder, vt_symbol, tick_date)
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# 使用淘宝下载的tick数据（2019年前）
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symbol, exchange = extract_vt_symbol(vt_symbol)
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underly_symbol = get_underlying_symbol(symbol)
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exchange_folder = VN_EXCHANGE_TICKFOLDER_MAP.get(exchange.value)
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if exchange == Exchange.INE:
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file_path = os.path.abspath(
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os.path.join(
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tick_folder,
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exchange_folder,
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tick_date.strftime('%Y'),
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tick_date.strftime('%Y%m'),
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tick_date.strftime('%Y%m%d'),
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'{}_{}.csv'.format(symbol.upper(), tick_date.strftime('%Y%m%d'))))
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else:
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file_path = os.path.abspath(
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os.path.join(
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tick_folder,
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exchange_folder,
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tick_date.strftime('%Y'),
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tick_date.strftime('%Y%m'),
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tick_date.strftime('%Y%m%d'),
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'{}{}_{}.csv'.format(underly_symbol.upper(), symbol[-2:], tick_date.strftime('%Y%m%d'))))
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ticks = []
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if not os.path.isfile(file_path):
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self.write_log(f'{file_path}文件不存在')
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return None
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df = pd.read_csv(file_path, encoding='gbk', parse_dates=False)
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df.columns = ['date', 'time', 'last_price', 'volume', 'last_volume', 'open_interest',
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'bid_price_1', 'bid_volume_1', 'bid_price_2', 'bid_volume_2', 'bid_price_3', 'bid_volume_3',
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'ask_price_1', 'ask_volume_1', 'ask_price_2', 'ask_volume_2', 'ask_price_3', 'ask_volume_3', 'BS']
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self.write_log(u'加载csv文件{}'.format(file_path))
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last_time = None
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for index, row in df.iterrows():
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# 日期, 时间, 成交价, 成交量, 总量, 属性(持仓增减), B1价, B1量, B2价, B2量, B3价, B3量, S1价, S1量, S2价, S2量, S3价, S3量, BS
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# 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
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tick = row.to_dict()
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tick.update({'symbol': symbol, 'exchange': exchange.value, 'trading_day': tick_date.strftime('%Y-%m-%d')})
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tick_datetime = datetime.strptime(tick['date'] + ' ' + tick['time'], '%Y-%m-%d %H:%M:%S')
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# 修正毫秒
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if tick['time'] == last_time:
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# 与上一个tick的时间（去除毫秒后）相同,修改为500毫秒
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tick_datetime = tick_datetime.replace(microsecond=500)
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tick['time'] = tick_datetime.strftime('%H:%M:%S.%f')
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else:
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last_time = tick['time']
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tick_datetime = tick_datetime.replace(microsecond=0)
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tick['time'] = tick_datetime.strftime('%H:%M:%S.%f')
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tick['datetime'] = tick_datetime
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# 排除涨停/跌停的数据
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if (float(tick['bid_price_1']) == float('1.79769E308') and int(tick['bid_volume_1']) == 0) \
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or (float(tick['ask_price_1']) == float('1.79769E308') and int(tick['ask_volume_1']) == 0):
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continue
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ticks.append(tick)
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del df
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return ticks
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def load_tq_csv_file(self, tick_folder, vt_symbol, tick_date):
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"""从天勤下载的csv文件中读取tick，返回list[{dict}]"""
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symbol, exchange = extract_vt_symbol(vt_symbol)
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underly_symbol = get_underlying_symbol(symbol)
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exchange_folder = VN_EXCHANGE_TICKFOLDER_MAP.get(exchange.value)
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file_path = os.path.abspath(
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os.path.join(
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tick_folder,
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tick_date.strftime('%Y%m'),
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'{}_{}.csv'.format(symbol, tick_date.strftime('%Y%m%d'))))
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ticks = []
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if not os.path.isfile(file_path):
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self.write_log(u'{}文件不存在'.format(file_path))
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return None
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try:
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df = pd.read_csv(file_path, parse_dates=False)
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# datetime,symbol,exchange,last_price,highest,lowest,volume,amount,open_interest,upper_limit,lower_limit,
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# bid_price_1,bid_volume_1,ask_price_1,ask_volume_1,
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# bid_price_2,bid_volume_2,ask_price_2,ask_volume_2,
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# bid_price_3,bid_volume_3,ask_price_3,ask_volume_3,
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# bid_price_4,bid_volume_4,ask_price_4,ask_volume_4,
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# bid_price_5,bid_volume_5,ask_price_5,ask_volume_5
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self.write_log(u'加载csv文件{}'.format(file_path))
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last_time = None
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for index, row in df.iterrows():
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tick = row.to_dict()
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tick['date'], tick['time'] = tick['datetime'].split(' ')
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tick.update({'trading_day': tick_date.strftime('%Y-%m-%d')})
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tick_datetime = datetime.strptime(tick['datetime'], '%Y-%m-%d %H:%M:%S.%f')
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# 修正毫秒
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if tick['time'] == last_time:
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# 与上一个tick的时间（去除毫秒后）相同,修改为500毫秒
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tick_datetime = tick_datetime.replace(microsecond=500)
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tick['time'] = tick_datetime.strftime('%H:%M:%S.%f')
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else:
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last_time = tick['time']
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tick_datetime = tick_datetime.replace(microsecond=0)
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tick['time'] = tick_datetime.strftime('%H:%M:%S.%f')
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tick['datetime'] = tick_datetime
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# 排除涨停/跌停的数据
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if (float(tick['bid_price_1']) == float('1.79769E308') and int(tick['bid_volume_1']) == 0) \
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or (float(tick['ask_price_1']) == float('1.79769E308') and int(tick['ask_volume_1']) == 0):
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continue
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ticks.append(tick)
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del df
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except Exception as ex:
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self.write_log(f'{file_path}文件读取不成功: {str(ex)}')
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return None
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return ticks
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def load_bz2_cache(self, cache_folder, cache_symbol, cache_date):
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"""加载缓存数据"""
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if not os.path.exists(cache_folder):
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@ -374,9 +523,15 @@ class PortfolioTestingEngine(BackTestingEngine):
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for vt_symbol in list(self.symbol_strategy_map.keys()):
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symbol, exchange = extract_vt_symbol(vt_symbol)
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if self.use_pkb2:
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tick_list = self.load_bz2_cache(cache_folder=self.tick_path,
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cache_symbol=symbol,
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cache_date=test_day.strftime('%Y%m%d'))
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else:
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tick_list = self.load_csv_file(tick_folder=self.tick_path,
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vt_symbol=vt_symbol,
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tick_date=test_day)
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if not tick_list or len(tick_list) == 0:
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continue
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@ -417,6 +572,13 @@ class PortfolioTestingEngine(BackTestingEngine):
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try:
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for (dt, vt_symbol), tick_data in combined_df.iterrows():
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symbol, exchange = extract_vt_symbol(vt_symbol)
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last_price = tick_data.get('last_price',None)
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if not last_price:
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last_price = tick_data.get('price',None)
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if not isinstance(last_price, float):
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continue
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if np.isnan(last_price):
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continue
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tick = TickData(
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gateway_name='backtesting',
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symbol=symbol,
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@ -425,13 +587,10 @@ class PortfolioTestingEngine(BackTestingEngine):
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date=dt.strftime('%Y-%m-%d'),
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time=dt.strftime('%H:%M:%S.%f'),
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trading_day=test_day.strftime('%Y-%m-%d'),
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last_price=tick_data['price'],
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last_price=last_price,
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volume=tick_data['volume']
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)
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if not isinstance(tick.last_price,float):
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continue
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if np.isnan(tick.last_price):
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continue
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self.new_tick(tick)
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# 结束一个交易日后，更新每日净值
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