def _load_data_from_db(self, conn: MongoConnection, db: str,
collection: str, time_key: str):
"""
helper function to load data from database
:param conn:
:param db:
:param collection:
:param time_key:
:return:
"""
if self.start is not None and self.end is not None:
bar = conn.read_mongo_df(
db, collection,
{time_key: {
'$gt': self.start,
'$lt': self.end
}})
elif self.start is not None and self.end is None:
bar = conn.read_mongo_df(
db,
collection,
{time_key: {
'$gt': self.start
}},
)
elif self.start is not None and self.end is None:
bar = conn.read_mongo_df(db, collection,
{time_key: {
'$lt': self.end
}})
bar[time_key] = pd.to_datetime(bar[time_key])
bar.set_index(time_key, inplace=True)
return bar
def _load_data(self):
"""
helper function to load the data
:return:
"""
self.data = dict()
if self.backtesting_setting['data_source'] == 'csv':
time_key = self.backtesting_setting['time_key']
for symbol, bar_data in self.backtesting_setting['data'].items():
self.data[symbol] = dict()
for bar_type, path in bar_data.items():
self.data[symbol][bar_type] = self._load_data_from_csv(
path, time_key)
if 'benchmark' in self.backtesting_setting.keys():
self.benchmark = self._load_data_from_csv(
self.backtesting_setting['benchmark'], time_key)
self.benchmark = self.benchmark['close']
elif self.backtesting_setting['data_source'] == 'mongo':
time_key = self.backtesting_setting['time_key']
host = self.backtesting_setting['host']
port = self.backtesting_setting['port']
user = self.backtesting_setting['user']
password = self.backtesting_setting['password']
conn = MongoConnection(host, port, user, password)
for symbol, bar_data in self.backtesting_setting['data'].items():
self.data[symbol] = dict()
for bar_type, dbs in bar_data.items():
self.data[symbol][bar_type] = self._load_data_from_db(
conn, dbs['db'], dbs['collections'], time_key)
if 'benchmark' in self.backtesting_setting.keys():
self.benchmark = self._load_data_from_db(
self.backtesting_setting['benchmark']['db'],
self.backtesting_setting['benchmark']['collections'],
time_key)
self.benchmark = self.benchmark['close']
self.quote_ctx.set_history_data(self.data)
"HK_FUTURE.999010": {
"K_1M": {
"MA1": {
"indicator": "MA",
"period": 20
},
"MA2": {
"indicator": "MA",
"period": 30,
"matype": "MA_Type.SMA",
"price_type": "'close'"
},
}
}
},
"traded_code": "HK_FUTURE.999010"
}
backtesting = VectorizedBacktesting(
quote,
broker,
strategy,
strategy_parameter,
backtesting_setting=backtesting_setting)
backtesting.run()
# backtesting.backtesting_result_save_pickle(strategy.strategy_name + '_' + strategy.strategy_version + '_2.pickle')
conn = MongoConnection('120.55.45.12', 27017, 'root', 'AlphaFactory2020')
print('save db')
backtesting.save_backtesting_result_to_db(conn, 'backtesting', 'ljy')
def connect_server(self, ip, port, username, password):
self.connect = MongoConnection(ip, port, username, password)
self.manager = AlphaManager(self.connect)
return self.connect.client.list_database_names()
def save_backtesting_result_to_db(
self,
conn: MongoConnection,
db: str,
collections: str,
):
d = {
'strategy_name':
self.strategy.strategy_name,
'strategy_version':
self.strategy.strategy_version,
'strategy_para':
json.dumps(self.strategy.strategy_parameters).replace(),
# because key has '.' mongodb doesn't allow this.
'strategy_logic':
inspect.getsource(self.strategy.strategy_logic),
'backtesting_date':
datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
'backtesting_setting':
json.dumps(self.backtesting_setting),
# because key has '.' mongodb doesn't allow this.
'backtesting_result': {
'first_traded':
self.backtesting_result['first_traded'],
'last_traded':
self.backtesting_result['last_traded'],
'num_trade':
self.backtesting_result['num_trade'],
'time_in_market':
self.backtesting_result['time_in_market'],
'win_rate':
self.backtesting_result['win_rate'],
'avg_win':
self.backtesting_result['avg_win'],
'avg_loss':
self.backtesting_result['avg_loss'],
'payoff_ratio':
self.backtesting_result['payoff_ratio'],
'cagr':
self.backtesting_result['cagr'],
'cumulative_return':
self.backtesting_result['cumulative_return'],
'sharpe':
self.backtesting_result['sharpe'],
'sortino':
self.backtesting_result['sortino'],
'volatility':
self.backtesting_result['volatility'],
'skew':
self.backtesting_result['skew'],
'Kurtosis':
self.backtesting_result['Kurtosis'],
'kelly':
self.backtesting_result['kelly'],
'value_at_risk':
self.backtesting_result['value_at_risk'],
'max_drawdown_value':
self.backtesting_result['drawdown_value'].min(),
'max_drawdown_percent':
self.backtesting_result['drawdown_percent'].min(),
'Avg Drawdown Days':
"{:.2f}".format(
self.backtesting_result['drawdown_detail']['days'].mean()),
'Max Drawdown Days':
"{:.2f}".format(
self.backtesting_result['drawdown_detail']['days'].max()),
}
}
r = conn.insert_from_dict(db, collections, d)
print('finish insert. Object id {}'.format(r.inserted_id))