def test_volume_share_slippage(self): slippage_model = VolumeShareSlippage() open_orders = [ Order(dt=datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), amount=100, filled=0, sid=self.ASSET133) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[0], ) orders_txns = list( slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.0001875), 'dt': datetime.datetime(2006, 1, 5, 14, 31, tzinfo=pytz.utc), 'amount': int(5), 'sid': int(133), 'commission': None, 'type': DATASOURCE_TYPE.TRANSACTION, 'order_id': open_orders[0].id } self.assertIsNotNone(txn) # TODO: Make expected_txn an Transaction object and ensure there # is a __eq__ for that class. self.assertEquals(expected_txn, txn.__dict__) open_orders = [ Order(dt=datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), amount=100, filled=0, sid=self.ASSET133) ] # Set bar_data to be a minute ahead of last trade. # Volume share slippage should not execute when there is no trade. bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[1], ) orders_txns = list( slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0)
def trades_with_txns(self, events, no_txn_dt): for event in events: # create a transaction for all but # first trade in each sid, to simulate None transaction if event.dt != no_txn_dt: order = Order( sid=event.sid, amount=-25, dt=event.dt ) order.source_id = 'MockOrderSource' yield order yield event txn = Transaction( sid=event.sid, amount=-25, dt=event.dt, price=10.0, commission=0.50, order_id=order.id ) txn.source_id = 'MockTransactionSource' yield txn else: yield event
def create_txn(trade_event, price, amount): """ Create a fake transaction to be filled and processed prior to the execution of a given trade event. """ mock_order = Order(trade_event.dt, trade_event.sid, amount, id=None) return create_transaction(trade_event, mock_order, price, amount)
def trades_with_txns(self, events, no_txn_dt): for event in events: # create a transaction for all but # first trade in each sid, to simulate None transaction if event.dt != no_txn_dt: order = Order(**{ 'sid': event.sid, 'amount': -25, 'dt': event.dt }) yield order yield event txn = Transaction( **{ 'sid': event.sid, 'amount': -25, 'dt': event.dt, 'price': 10.0, 'commission': 0.50, 'order_id': order.id }) yield txn else: yield event
def test_orders_stop(self, name, order_data, event_data, expected): tempdir = TempDirectory() try: data = order_data data['sid'] = self.ASSET133 order = Order(**data) assets = { 133: pd.DataFrame({ "open": [event_data["open"]], "high": [event_data["high"]], "low": [event_data["low"]], "close": [event_data["close"]], "volume": [event_data["volume"]], "dt": [pd.Timestamp('2006-01-05 14:31', tz='UTC')] }).set_index("dt") } write_bcolz_minute_data( self.env, pd.date_range( start=normalize_date(self.minutes[0]), end=normalize_date(self.minutes[-1]) ), tempdir.path, assets ) equity_minute_reader = BcolzMinuteBarReader(tempdir.path) data_portal = DataPortal( self.env, equity_minute_reader=equity_minute_reader, ) slippage_model = VolumeShareSlippage() try: dt = pd.Timestamp('2006-01-05 14:31', tz='UTC') bar_data = BarData(data_portal, lambda: dt, 'minute') _, txn = next(slippage_model.simulate( bar_data, self.ASSET133, [order], )) except StopIteration: txn = None if expected['transaction'] is None: self.assertIsNone(txn) else: self.assertIsNotNone(txn) for key, value in expected['transaction'].items(): self.assertEquals(value, txn[key]) finally: tempdir.cleanup()
def test_volume_share_slippage(self): event = Event({ 'volume': 200, 'type': 4, 'price': 3.0, 'datetime': datetime.datetime(2006, 1, 5, 14, 31, tzinfo=pytz.utc), 'high': 3.15, 'low': 2.85, 'sid': 133, 'source_id': 'test_source', 'close': 3.0, 'dt': datetime.datetime(2006, 1, 5, 14, 31, tzinfo=pytz.utc), 'open': 3.0 }) slippage_model = VolumeShareSlippage() open_orders = [ Order( **{ 'dt': datetime.datetime( 2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': 133 }) ] orders_txns = list(slippage_model.simulate(event, open_orders)) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.01875), 'dt': datetime.datetime(2006, 1, 5, 14, 31, tzinfo=pytz.utc), 'amount': int(50), 'sid': int(133), 'commission': None, 'type': DATASOURCE_TYPE.TRANSACTION, 'order_id': open_orders[0].id } self.assertIsNotNone(txn) # TODO: Make expected_txn an Transaction object and ensure there # is a __eq__ for that class. self.assertEquals(expected_txn, txn.__dict__)
def test_orders_stop(self, name, order_data, event_data, expected): data = order_data data['asset'] = self.ASSET133 order = Order(**data) if expected['transaction']: expected['transaction']['asset'] = self.ASSET133 event_data['asset'] = self.ASSET133 assets = ((133, pd.DataFrame( { 'open': [event_data['open']], 'high': [event_data['high']], 'low': [event_data['low']], 'close': [event_data['close']], 'volume': [event_data['volume']], }, index=[pd.Timestamp('2006-01-05 14:31', tz='UTC')], )), ) days = pd.date_range(start=normalize_date(self.minutes[0]), end=normalize_date(self.minutes[-1])) with tmp_bcolz_equity_minute_bar_reader(self.trading_calendar, days, assets) as reader: data_portal = DataPortal( self.env.asset_finder, self.trading_calendar, first_trading_day=reader.first_trading_day, equity_minute_reader=reader, ) slippage_model = VolumeShareSlippage() try: dt = pd.Timestamp('2006-01-05 14:31', tz='UTC') bar_data = BarData( data_portal, lambda: dt, self.sim_params.data_frequency, self.trading_calendar, NoRestrictions(), ) _, txn = next( slippage_model.simulate( bar_data, self.ASSET133, [order], )) except StopIteration: txn = None if expected['transaction'] is None: self.assertIsNone(txn) else: self.assertIsNotNone(txn) for key, value in expected['transaction'].items(): self.assertEquals(value, txn[key])
def test_orders_stop(self, name, order_data, event_data, expected): order = Order(**order_data) event = Event(initial_values=event_data) slippage_model = VolumeShareSlippage() try: _, txn = slippage_model.simulate(event, [order]).next() except StopIteration: txn = None if expected['transaction'] is None: self.assertIsNone(txn) else: self.assertIsNotNone(txn) for key, value in expected['transaction'].items(): self.assertEquals(value, txn[key])
def test_volume_share_slippage(self): tempdir = TempDirectory() try: assets = { 133: pd.DataFrame({ "open": [3.00], "high": [3.15], "low": [2.85], "close": [3.00], "volume": [200], "dt": [self.minutes[0]] }).set_index("dt") } write_bcolz_minute_data( self.env, pd.date_range( start=normalize_date(self.minutes[0]), end=normalize_date(self.minutes[-1]) ), tempdir.path, assets ) equity_minute_reader = BcolzMinuteBarReader(tempdir.path) data_portal = DataPortal( self.env, equity_minute_reader=equity_minute_reader, ) slippage_model = VolumeShareSlippage() open_orders = [ Order( dt=datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), amount=100, filled=0, sid=self.ASSET133 ) ] bar_data = BarData(data_portal, lambda: self.minutes[0], 'minute') orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.0001875), 'dt': datetime.datetime( 2006, 1, 5, 14, 31, tzinfo=pytz.utc), 'amount': int(5), 'sid': int(133), 'commission': None, 'type': DATASOURCE_TYPE.TRANSACTION, 'order_id': open_orders[0].id } self.assertIsNotNone(txn) # TODO: Make expected_txn an Transaction object and ensure there # is a __eq__ for that class. self.assertEquals(expected_txn, txn.__dict__) open_orders = [ Order( dt=datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), amount=100, filled=0, sid=self.ASSET133 ) ] # Set bar_data to be a minute ahead of last trade. # Volume share slippage should not execute when there is no trade. bar_data = BarData(data_portal, lambda: self.minutes[1], 'minute') orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) finally: tempdir.cleanup()
def test_orders_stop_limit(self): slippage_model = VolumeShareSlippage() slippage_model.data_portal = self.data_portal # long, does not trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': self.ASSET133, 'stop': 4.0, 'limit': 3.0}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[2], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[3], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # long, does not trade - impacted price worse than limit price open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': self.ASSET133, 'stop': 4.0, 'limit': 3.5}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[2], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[3], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # long, does trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': self.ASSET133, 'stop': 4.0, 'limit': 3.6}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[2], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[3], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.50021875), 'dt': datetime.datetime( 2006, 1, 5, 14, 34, tzinfo=pytz.utc), 'amount': int(50), 'sid': int(133) } for key, value in expected_txn.items(): self.assertEquals(value, txn[key]) # short, does not trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': self.ASSET133, 'stop': 3.0, 'limit': 4.0}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[0], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[1], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # short, does not trade - impacted price worse than limit price open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': self.ASSET133, 'stop': 3.0, 'limit': 3.5}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[0], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[1], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # short, does trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': self.ASSET133, 'stop': 3.0, 'limit': 3.4}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[0], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[1], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.49978125), 'dt': datetime.datetime( 2006, 1, 5, 14, 32, tzinfo=pytz.utc), 'amount': int(-50), 'sid': int(133) } for key, value in expected_txn.items(): self.assertEquals(value, txn[key])
def test_orders_limit(self): slippage_model = VolumeShareSlippage() slippage_model.data_portal = self.data_portal # long, does not trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': self.ASSET133, 'limit': 3.5}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[3], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # long, does not trade - impacted price worse than limit price open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': self.ASSET133, 'limit': 3.5}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[3], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # long, does trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': self.ASSET133, 'limit': 3.6}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[3], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 1) txn = orders_txns[0][1] expected_txn = { 'price': float(3.50021875), 'dt': datetime.datetime( 2006, 1, 5, 14, 34, tzinfo=pytz.utc), # we ordered 100 shares, but default volume slippage only allows # for 2.5% of the volume. 2.5% * 2000 = 50 shares 'amount': int(50), 'sid': int(133), 'order_id': open_orders[0].id } self.assertIsNotNone(txn) for key, value in expected_txn.items(): self.assertEquals(value, txn[key]) # short, does not trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': self.ASSET133, 'limit': 3.5}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[0], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # short, does not trade - impacted price worse than limit price open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': self.ASSET133, 'limit': 3.5}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[0], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) # short, does trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': self.ASSET133, 'limit': 3.4}) ] bar_data = self.create_bardata( simulation_dt_func=lambda: self.minutes[1], ) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.49978125), 'dt': datetime.datetime( 2006, 1, 5, 14, 32, tzinfo=pytz.utc), 'amount': int(-50), 'sid': int(133) } self.assertIsNotNone(txn) for key, value in expected_txn.items(): self.assertEquals(value, txn[key])
def create_txn(event, price, amount): mock_order = Order(None, None, event.sid, id=None) txn = create_transaction(event, mock_order, price, amount) txn.source_id = 'MockTransactionSource' return txn
def test_minute_tracker(self): """ Tests minute performance tracking.""" with trading.TradingEnvironment(): start_dt = trading.environment.exchange_dt_in_utc( datetime.datetime(2013, 3, 1, 9, 31)) end_dt = trading.environment.exchange_dt_in_utc( datetime.datetime(2013, 3, 1, 16, 0)) sim_params = SimulationParameters( period_start=start_dt, period_end=end_dt, emission_rate='minute' ) tracker = perf.PerformanceTracker(sim_params) foo_event_1 = factory.create_trade('foo', 10.0, 20, start_dt) order_event_1 = Order(sid=foo_event_1.sid, amount=-25, dt=foo_event_1.dt) bar_event_1 = factory.create_trade('bar', 100.0, 200, start_dt) txn_event_1 = Transaction(sid=foo_event_1.sid, amount=-25, dt=foo_event_1.dt, price=10.0, commission=0.50, order_id=order_event_1.id) benchmark_event_1 = Event({ 'dt': start_dt, 'returns': 0.01, 'type': DATASOURCE_TYPE.BENCHMARK }) foo_event_2 = factory.create_trade( 'foo', 11.0, 20, start_dt + datetime.timedelta(minutes=1)) bar_event_2 = factory.create_trade( 'bar', 11.0, 20, start_dt + datetime.timedelta(minutes=1)) benchmark_event_2 = Event({ 'dt': start_dt + datetime.timedelta(minutes=1), 'returns': 0.02, 'type': DATASOURCE_TYPE.BENCHMARK }) events = [ foo_event_1, order_event_1, benchmark_event_1, txn_event_1, bar_event_1, foo_event_2, benchmark_event_2, bar_event_2, ] grouped_events = itertools.groupby( events, operator.attrgetter('dt')) messages = {} for date, group in grouped_events: tracker.set_date(date) for event in group: tracker.process_event(event) tracker.handle_minute_close(date) msg = tracker.to_dict() messages[date] = msg self.assertEquals(2, len(messages)) msg_1 = messages[foo_event_1.dt] msg_2 = messages[foo_event_2.dt] self.assertEquals(1, len(msg_1['minute_perf']['transactions']), "The first message should contain one " "transaction.") # Check that transactions aren't emitted for previous events. self.assertEquals(0, len(msg_2['minute_perf']['transactions']), "The second message should have no " "transactions.") self.assertEquals(1, len(msg_1['minute_perf']['orders']), "The first message should contain one orders.") # Check that orders aren't emitted for previous events. self.assertEquals(0, len(msg_2['minute_perf']['orders']), "The second message should have no orders.") # Ensure that period_close moves through time. # Also, ensure that the period_closes are the expected dts. self.assertEquals(foo_event_1.dt, msg_1['minute_perf']['period_close']) self.assertEquals(foo_event_2.dt, msg_2['minute_perf']['period_close']) # Ensure that a Sharpe value for cumulative metrics is being # created. self.assertIsNotNone(msg_1['cumulative_risk_metrics']['sharpe']) self.assertIsNotNone(msg_2['cumulative_risk_metrics']['sharpe'])
def create_txn(event, price, amount): mock_order = Order(None, None, event.sid, id=None) return create_transaction(event, mock_order, price, amount)
def test_orders_limit(self): events = self.gen_trades() slippage_model = VolumeShareSlippage() # long, does not trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': 133, 'limit': 3.5}) ] orders_txns = list(slippage_model.simulate( events[2], open_orders )) self.assertEquals(len(orders_txns), 0) # long, does trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': 100, 'filled': 0, 'sid': 133, 'limit': 3.5}) ] orders_txns = list(slippage_model.simulate( events[3], open_orders )) self.assertEquals(len(orders_txns), 1) txn = orders_txns[0][1] expected_txn = { 'price': float(3.500875), 'dt': datetime.datetime( 2006, 1, 5, 14, 34, tzinfo=pytz.utc), 'amount': int(100), 'sid': int(133), 'order_id': open_orders[0].id } self.assertIsNotNone(txn) for key, value in expected_txn.items(): self.assertEquals(value, txn[key]) # short, does not trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': 133, 'limit': 3.5}) ] orders_txns = list(slippage_model.simulate( events[0], open_orders )) expected_txn = {} self.assertEquals(len(orders_txns), 0) # short, does trade open_orders = [ Order(**{ 'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), 'amount': -100, 'filled': 0, 'sid': 133, 'limit': 3.5}) ] orders_txns = list(slippage_model.simulate( events[1], open_orders )) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.499125), 'dt': datetime.datetime( 2006, 1, 5, 14, 32, tzinfo=pytz.utc), 'amount': int(-100), 'sid': int(133) } self.assertIsNotNone(txn) for key, value in expected_txn.items(): self.assertEquals(value, txn[key])
def test_volume_share_slippage(self): assets = { 133: pd.DataFrame( { 'open': [3.00], 'high': [3.15], 'low': [2.85], 'close': [3.00], 'volume': [200], }, index=[self.minutes[0]], ), } days = pd.date_range( start=normalize_date(self.minutes[0]), end=normalize_date(self.minutes[-1]) ) with tmp_bcolz_minute_bar_reader(self.env, days, assets) as reader: data_portal = DataPortal( self.env, equity_minute_reader=reader, ) slippage_model = VolumeShareSlippage() open_orders = [ Order( dt=datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), amount=100, filled=0, sid=self.ASSET133 ) ] bar_data = BarData(data_portal, lambda: self.minutes[0], 'minute') orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 1) _, txn = orders_txns[0] expected_txn = { 'price': float(3.0001875), 'dt': datetime.datetime( 2006, 1, 5, 14, 31, tzinfo=pytz.utc), 'amount': int(5), 'sid': int(133), 'commission': None, 'type': DATASOURCE_TYPE.TRANSACTION, 'order_id': open_orders[0].id } self.assertIsNotNone(txn) # TODO: Make expected_txn an Transaction object and ensure there # is a __eq__ for that class. self.assertEquals(expected_txn, txn.__dict__) open_orders = [ Order( dt=datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc), amount=100, filled=0, sid=self.ASSET133 ) ] # Set bar_data to be a minute ahead of last trade. # Volume share slippage should not execute when there is no trade. bar_data = BarData(data_portal, lambda: self.minutes[1], 'minute') orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0)