def test_price_based_slippage(self):
slippage_model = PriceBasedSlippage(slippage_rate=0.1)
actual_fill_prices, actual_fill_volumes = slippage_model.apply_slippage(
self.orders, self.prices_without_slippage)
expected_fill_prices = [1.1, 90.0, 1100.0]
expected_fill_volumes = [1000, -10, 1]
assert_lists_equal(expected_fill_prices, actual_fill_prices)
assert_lists_equal(expected_fill_volumes, actual_fill_volumes)
def test_price_based_slippage__nan_prices(self):
slippage_rate = 0.1
slippage_model = PriceBasedSlippage(slippage_rate, self.data_provider, self.contract_ticker_mapper)
prices_without_slippage = [float('nan'), np.nan, float('nan')]
expected_fill_prices = [float('nan'), float('nan'), float('nan')]
actual_fill_prices, actual_fill_volumes = slippage_model.process_orders(str_to_date("2020-01-01"),
self.orders,
prices_without_slippage)
assert_lists_equal(expected_fill_prices, actual_fill_prices)
def test_price_based_slippage__no_volume_limits(self):
"""Volume should remain the same. Prices should be increased by the slippage rate."""
slippage_rate = 0.1
slippage_model = PriceBasedSlippage(slippage_rate, self.data_provider, self.contract_ticker_mapper)
prices_without_slippage = [20.0, 30.0, 40.0]
# Each price should be changed by +0.1 / -0.1 depending on whether it is a BUY or SELL
expected_fill_prices = [22.0, 27.0, 44.0]
# Volumes should remain equal to the initial quantities
expected_fill_volumes = [order.quantity for order in self.orders] # [1250, -200, 1]
actual_fill_prices, actual_fill_volumes = slippage_model.process_orders(str_to_date("2020-01-01"),
self.orders,
prices_without_slippage)
assert_lists_equal(expected_fill_prices, actual_fill_prices)
assert_lists_equal(expected_fill_volumes, actual_fill_volumes)
def test_price_based_slippage__with_volume(self):
"""Volume should be changed in case of exceeding limits. Slippage rate is set to 0.0, so the prices should
remain unchanged."""
slippage_rate = 0.0
max_volume_share_limit = 0.1
slippage_model = PriceBasedSlippage(slippage_rate, self.data_provider, max_volume_share_limit)
prices_without_slippage = [20.0, 30.0, 40.0]
expected_fill_prices = prices_without_slippage
# Mean historical volume is set to 50.0 for each of the tickers. As the max_volume_share_limit = 0.1, the limit
# is set to +/-5.0
expected_fill_volumes = [5.0, -5.0, 1]
actual_fill_prices, actual_fill_volumes = slippage_model.process_orders(str_to_date("2020-01-01"),
self.orders,
prices_without_slippage)
assert_lists_equal(expected_fill_prices, actual_fill_prices)
assert_lists_equal(expected_fill_volumes, actual_fill_volumes)
def setUp(self):
self.scheduling_time_delay = 1
start_date = str_to_date("2018-02-04")
before_close = start_date + MarketCloseEvent.trigger_time(
) - RelativeDelta(minutes=self.scheduling_time_delay)
self.timer = SettableTimer(initial_time=before_close)
contracts_to_tickers_mapper = SimulatedBloombergContractTickerMapper()
msft_contract = Contract("MSFT US Equity",
security_type='STK',
exchange='TEST')
self.msft_ticker = contracts_to_tickers_mapper.contract_to_ticker(
msft_contract)
self.data_handler = Mock(spec=DataHandler)
self.scheduler = Mock(spec=Scheduler)
self.commission_model = FixedCommissionModel(commission=0.0)
self.monitor = Mock(spec=AbstractMonitor)
self.portfolio = Mock(spec=Portfolio)
slippage_model = PriceBasedSlippage(0.0, self.data_handler,
contracts_to_tickers_mapper)
self.exec_handler = SimulatedExecutionHandler(
self.data_handler, self.timer, self.scheduler, self.monitor,
self.commission_model, contracts_to_tickers_mapper, self.portfolio,
slippage_model, RelativeDelta(minutes=self.scheduling_time_delay))
self.order_1 = Order(msft_contract,
quantity=10,
execution_style=MarketOrder(),
time_in_force=TimeInForce.OPG)
self.order_2 = Order(msft_contract,
quantity=-5,
execution_style=MarketOrder(),
time_in_force=TimeInForce.OPG)
self.order_3 = Order(msft_contract,
quantity=-7,
execution_style=MarketOrder(),
time_in_force=TimeInForce.OPG)
self.order_4 = Order(msft_contract,
quantity=4,
execution_style=MarketOnCloseOrder(),
time_in_force=TimeInForce.DAY)
def __init__(self, data_provider: GeneralPriceProvider, settings: Settings, pdf_exporter: PDFExporter,
excel_exporter: ExcelExporter):
self._logger = qf_logger.getChild(self.__class__.__name__)
self._backtest_name = "Backtest Results"
self._initial_cash = 100000
self._monitor_type = LightBacktestMonitor
self._logging_level = logging.WARNING
self._contract_ticker_mapper = DummyBloombergContractTickerMapper()
self._commission_model = FixedCommissionModel(0.0)
self._slippage_model = PriceBasedSlippage(0.0)
self._position_sizer_type = SimplePositionSizer
self._position_sizer_param = None
self._data_provider = data_provider
self._settings = settings
self._pdf_exporter = pdf_exporter
self._excel_exporter = excel_exporter
def setUp(self):
self.start_date = str_to_date("2018-02-04")
self.msft_contract = Contract(self.MSFT_TICKER_STR,
security_type='SEK',
exchange='TEST')
self.msft_ticker = BloombergTicker(self.MSFT_TICKER_STR)
self.contracts_to_tickers_mapper = DummyBloombergContractTickerMapper()
timer = SettableTimer(initial_time=self.start_date)
self.data_handler = mock(strict=True)
self.scheduler = mock()
self.commission_model = FixedCommissionModel(commission=0.0)
self.monitor = _MonitorMock()
self.spied_monitor = spy(self.monitor)
self.portfolio = mock()
slippage_model = PriceBasedSlippage(0.0)
self.exec_hanlder = SimulatedExecutionHandler(
self.data_handler, timer, self.scheduler, self.spied_monitor,
self.commission_model, self.contracts_to_tickers_mapper,
self.portfolio, slippage_model)
self._set_current_msft_price(100.0)
self.stop_loss_order_1 = Order(self.msft_contract,
quantity=-1,
execution_style=StopOrder(95.0),
time_in_force=TimeInForce.GTC)
self.stop_loss_order_2 = Order(self.msft_contract,
quantity=-1,
execution_style=StopOrder(90.0),
time_in_force=TimeInForce.GTC)
self.stop_loss_order_3 = Order(self.msft_contract,
quantity=-1,
execution_style=StopOrder(50.0),
time_in_force=TimeInForce.DAY)
self.exec_hanlder.accept_orders([
self.stop_loss_order_1, self.stop_loss_order_2,
self.stop_loss_order_3
])
def setUp(self):
self.scheduling_time_delay = 1
start_date = str_to_date("2018-02-04")
before_close = start_date + MarketCloseEvent.trigger_time(
) - RelativeDelta(minutes=self.scheduling_time_delay)
self.timer = SettableTimer(initial_time=before_close)
self.msft_ticker = BloombergTicker("MSFT US Equity")
self.data_handler = Mock(spec=DataHandler)
self.data_handler.frequency = Frequency.DAILY
self.data_handler.data_provider = Mock(spec=DataProvider)
self.scheduler = Mock(spec=Scheduler)
self.commission_model = FixedCommissionModel(commission=0.0)
self.monitor = Mock(spec=AbstractMonitor)
self.portfolio = Mock(spec=Portfolio)
slippage_model = PriceBasedSlippage(0.0, self.data_handler)
self.exec_handler = SimulatedExecutionHandler(
self.data_handler, self.timer, self.scheduler, self.monitor,
self.commission_model, self.portfolio, slippage_model,
RelativeDelta(minutes=self.scheduling_time_delay))
self.order_1 = Order(self.msft_ticker,
quantity=10,
execution_style=MarketOrder(),
time_in_force=TimeInForce.OPG)
self.order_2 = Order(self.msft_ticker,
quantity=-5,
execution_style=MarketOrder(),
time_in_force=TimeInForce.OPG)
self.order_3 = Order(self.msft_ticker,
quantity=-7,
execution_style=MarketOrder(),
time_in_force=TimeInForce.OPG)
self.order_4 = Order(self.msft_ticker,
quantity=4,
execution_style=MarketOnCloseOrder(),
time_in_force=TimeInForce.DAY)
def setUp(self):
MarketOpenEvent.set_trigger_time({"hour": 13, "minute": 30, "second": 0, "microsecond": 0})
MarketCloseEvent.set_trigger_time({"hour": 20, "minute": 0, "second": 0, "microsecond": 0})
self.start_date = str_to_date("2018-02-04")
self.number_of_minutes = 5
before_close = self.start_date + MarketCloseEvent.trigger_time() - RelativeDelta(minutes=self.number_of_minutes)
self.msft_ticker = BloombergTicker(self.MSFT_TICKER_STR)
self.timer = SettableTimer(initial_time=before_close)
self.data_handler = Mock(spec=DataHandler)
self.data_handler.data_provider = Mock(spec=DataProvider)
scheduler = Mock(spec=Scheduler)
ScheduleOrderExecutionEvent.clear()
# Set the periodic bar events to intraday trading
IntradayBarEvent.frequency = Frequency.MIN_1
commission_model = FixedCommissionModel(commission=0.0)
self.monitor = Mock(spec=AbstractMonitor)
self.portfolio = Mock(spec=Portfolio)
slippage_model = PriceBasedSlippage(0.0, self.data_handler)
self.exec_handler = SimulatedExecutionHandler(self.data_handler, self.timer, scheduler, self.monitor,
commission_model, self.portfolio, slippage_model,
RelativeDelta(minutes=self.number_of_minutes))
self._set_last_available_price(100.0)
self.stop_loss_order_1 = Order(self.msft_ticker, quantity=-1, execution_style=StopOrder(95.0),
time_in_force=TimeInForce.GTC)
self.stop_loss_order_2 = Order(self.msft_ticker, quantity=-1, execution_style=StopOrder(90.0),
time_in_force=TimeInForce.GTC)
self.stop_loss_order_3 = Order(self.msft_ticker, quantity=-1, execution_style=StopOrder(50.0),
time_in_force=TimeInForce.DAY)
self.exec_handler.assign_order_ids([self.stop_loss_order_1, self.stop_loss_order_2, self.stop_loss_order_3])
def __init__(self, data_provider: DataProvider, start_date, end_date, initial_cash,
frequency: Frequency = Frequency.MIN_1):
"""
Set up the backtest variables according to what has been passed in.
"""
super().__init__()
self.logger = qf_logger.getChild(self.__class__.__name__)
self.logger.info(
"\n".join([
"Testing the Backtester:",
"Start date: {:s}".format(date_to_str(start_date)),
"End date: {:s}".format(date_to_str(end_date)),
"Initial cash: {:.2f}".format(initial_cash),
"Frequency of the simulated execution handler: {}".format(frequency)
])
)
timer = SettableTimer(start_date)
notifiers = Notifiers(timer)
if frequency <= Frequency.DAILY:
data_handler = DailyDataHandler(data_provider, timer)
else:
data_handler = IntradayDataHandler(data_provider, timer)
contract_ticker_mapper = SimulatedBloombergContractTickerMapper()
portfolio = Portfolio(data_handler, initial_cash, timer, contract_ticker_mapper)
signals_register = BacktestSignalsRegister()
backtest_result = BacktestResult(portfolio=portfolio, backtest_name="Testing the Backtester",
start_date=start_date, end_date=end_date, signals_register=signals_register)
monitor = Mock(spec=BacktestMonitor)
commission_model = FixedCommissionModel(0.0)
slippage_model = PriceBasedSlippage(0.0, data_provider, contract_ticker_mapper)
execution_handler = SimulatedExecutionHandler(
data_handler, timer, notifiers.scheduler, monitor, commission_model,
contract_ticker_mapper, portfolio, slippage_model)
broker = BacktestBroker(portfolio, execution_handler)
order_factory = OrderFactory(broker, data_handler, contract_ticker_mapper)
event_manager = self._create_event_manager(timer, notifiers)
time_flow_controller = BacktestTimeFlowController(
notifiers.scheduler, event_manager, timer, notifiers.empty_queue_event_notifier, end_date
)
position_sizer = SimplePositionSizer(broker, data_handler, order_factory, contract_ticker_mapper,
signals_register)
self.logger.info(
"\n".join([
"Configuration of components:",
"Position sizer: {:s}".format(position_sizer.__class__.__name__),
"Timer: {:s}".format(timer.__class__.__name__),
"Data Provider: {:s}".format(data_provider.__class__.__name__),
"Backtest Result: {:s}".format(backtest_result.__class__.__name__),
"Monitor: {:s}".format(monitor.__class__.__name__),
"Execution Handler: {:s}".format(execution_handler.__class__.__name__),
"Commission Model: {:s}".format(commission_model.__class__.__name__),
"Broker: {:s}".format(broker.__class__.__name__),
"Contract-Ticker Mapper: {:s}".format(contract_ticker_mapper.__class__.__name__)
])
)
self.broker = broker
self.notifiers = notifiers
self.initial_cash = initial_cash
self.start_date = start_date
self.end_date = end_date
self.event_manager = event_manager
self.contract_ticker_mapper = contract_ticker_mapper
self.data_handler = data_handler
self.portfolio = portfolio
self.execution_handler = execution_handler
self.position_sizer = position_sizer
self.orders_filters = []
self.monitor = monitor
self.timer = timer
self.order_factory = order_factory
self.time_flow_controller = time_flow_controller
