def main():
config = Config(load_from_yaml("../../config/backtest.yaml"),
load_from_yaml("../../config/down2%.yaml"))
app_context = ApplicationContext(config=config)
BacktestRunner().start(app_context)
def main():
config = Config(load_from_yaml("../../config/live_ib.yaml"),
load_from_yaml("../../config/down2%.yaml"))
app_context = ApplicationContext(config=config)
ATSRunner().start(app_context)
def main():
config = Config(load_from_yaml("../../config/data_import.yaml"),
{"Application": {
"feedId": "Yahoo"
}})
app_context = ApplicationContext(config=config)
MktDataImporter().start(app_context)
def create_app_context(self, override):
return ApplicationContext(config=Config(
load_from_yaml("../config/backtest.yaml"),
load_from_yaml("../config/down2%.yaml"),
test_override,
StrategyPersistenceTest.stg_override,
override))
def create_app_context(self, conf):
return ApplicationContext(config=Config(
load_from_yaml("../config/backtest.yaml"),
load_from_yaml("../config/down2%.yaml"), test_override, {
"Application": {
"ceateAtStart": True,
"deleteDBAtStop": False,
"persistenceMode": "RealTime"
}
}, conf))
def __init__(self, config: Config = None):
super(ApplicationContext, self).__init__()
self.config = config if config else Config()
self.clock = self.add_startable(self.__get_clock())
self.provider_mgr = self.add_startable(ProviderManager())
self.seq_mgr = self.add_startable(SequenceManager())
self.inst_data_mgr = self.add_startable(InstrumentDataManager())
self.ref_data_mgr = self.add_startable(RefDataManager())
self.order_mgr = self.add_startable(OrderManager())
self.acct_mgr = self.add_startable(AccountManager())
self.portf_mgr = self.add_startable(PortfolioManager())
self.stg_mgr = self.add_startable(StrategyManager())
self.event_bus = EventBus()
self.model_factory = ModelFactory
"plot": False
},
"DataStore": {"InMemory":
{
"file": "../data/algotrader_backtest_db.p",
"instCSV": "../data/refdata/instrument.csv",
"ccyCSV": "../data/refdata/ccy.csv",
"exchCSV": "../data/refdata/exch.csv"
}
},
"Feed": {"CSV":
{"path": "/mnt/data/dev/workspaces/python-trading/data/tradedata"}
}
}
config = Config(test_override)
empty_config = Config({
"Application": {
"dataStoreId": "InMemory",
"createDBAtStart": True,
"deleteDBAtStop": False
},
"DataStore": {"InMemory":
{
"file": "../data/algotrader_backtest_db.p",
}
},
"Feed": {"CSV":
{"path": "/mnt/data/dev/workspaces/python-trading/data/tradedata"}
}
# from algotrader.utils import logger
# def app_context():
# persistence_config = PersistenceConfig(None,
# DataStore.Mongo, PersistenceMode.RealTime,
# DataStore.Mongo, PersistenceMode.RealTime,
# DataStore.Mongo, PersistenceMode.RealTime,
# DataStore.Mongo, PersistenceMode.RealTime)
# app_config = ApplicationConfig(id=None, ref_data_mgr_type=RefDataManager.DB, clock_type=Clock.RealTime,
# persistence_config=persistence_config,
# provider_configs=[MongoDBConfig(), IBConfig(client_id=2, use_gevent=True)])
# app_context = ApplicationContext(app_config=app_config)
#
# return app_context
config = Config(load_from_yaml("../config/data_import.yaml"))
app_context = ApplicationContext(config=config)
def init_ib(app_context):
app_context.start()
broker = app_context.provider_mgr.get(Broker.IB)
broker.start(app_context)
return broker
def import_inst_from_ib(broker,
symbol,
sec_type='STK',
def test_with_sma(self):
sigma = 0.3
x0 = 100
dt = 1. / 252
dW = np.random.normal(0, math.sqrt(dt), TestCompareWithFunctionalBacktest.num_days)
asset = []
asset.append(x0)
for i in range(1, TestCompareWithFunctionalBacktest.num_days):
xprev = asset[-1]
x = xprev + xprev * 0.02 * dt + sigma * xprev * dW[i]
asset.append(x)
instrument = 0
lot_size = 10000
symbols = ['SPY', 'VXX', 'XLV', 'XIV']
dict_df = {}
self.df = self.get_df(asset=asset)
for symbol in symbols:
dict_df[symbol] = self.df
config = Config({
"Application": {
"type": "BackTesting",
"clockId": "Simulation",
"dataStoreId": "InMemory",
"persistenceMode": "Disable",
"createDBAtStart": True,
"deleteDBAtStop": False,
"feedId": "PandasMemory",
"brokerId": "Simulator",
"portfolioId": "test2",
"stg": "down2%",
"stgCls": "algotrader.strategy.down_2pct_strategy.Down2PctStrategy",
"instrumentIds": ["0"],
"subscriptionTypes": ["Bar.Yahoo.Time.D1"],
"fromDate": TestCompareWithFunctionalBacktest.dates[0],
"toDate": TestCompareWithFunctionalBacktest.dates[-1],
"plot": False
},
"DataStore": {"InMemory":
{
"file": "../data/algotrader_db.p",
"instCSV": "../data/refdata/instrument.csv",
"ccyCSV": "../data/refdata/ccy.csv",
"exchCSV": "../data/refdata/exch.csv"
}
},
"Strategy": {
"down2%": {
"qty": lot_size
}
}
})
self.init_context(symbols=symbols, asset=asset, config=config)
feed = self.app_context.get_feed()
feed.set_data_frame(dict_df)
close = self.app_context.inst_data_mgr.get_series("Bar.%s.Time.86400" % instrument)
close.start(self.app_context)
strategy = SMAStrategy("sma")
strategy.start(self.app_context)
rets = strategy.get_portfolio().get_return()
bt_result = strategy.get_portfolio().get_result()
sma10 = talib.SMA(self.df.Close.values, 10)
sma25 = talib.SMA(self.df.Close.values, 25)
signal = pd.Series(1 * (sma10 > sma25), index=self.df.index)
cash = []
stock_value = []
cash.append(TestCompareWithFunctionalBacktest.init_cash)
stock_value.append(0)
for i in range(1, signal.shape[0]):
cash.append(cash[-1] - lot_size * (signal[i] - signal[i - 1]) * self.df['Close'][i])
stock_value.append(lot_size * signal[i] * self.df['Close'][i])
target_port = pd.DataFrame({"cash": cash,
"stock_value": stock_value})
target_port["total_equity"] = target_port["cash"] + target_port["stock_value"]
target_port["return"] = target_port["total_equity"].pct_change()
try:
np.testing.assert_almost_equal(target_port["return"].values[1:], rets.values, 5)
except AssertionError as e:
self.fail(e.message)
finally:
strategy.stop()
def test_multiple(self):
config = Config(
load_from_yaml("../config/backtest.yaml"),
load_from_yaml("../config/down2%.yaml"))
self.assertEquals(1, config.get_strategy_config("down2%", "qty"))