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 = BarData(self.data_portal, lambda: self.minutes[2], self.sim_params.data_frequency) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = BarData(self.data_portal, lambda: self.minutes[3], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[2], self.sim_params.data_frequency) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = BarData(self.data_portal, lambda: self.minutes[3], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[2], self.sim_params.data_frequency) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = BarData(self.data_portal, lambda: self.minutes[3], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[0], self.sim_params.data_frequency) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = BarData(self.data_portal, lambda: self.minutes[1], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[0], self.sim_params.data_frequency) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = BarData(self.data_portal, lambda: self.minutes[1], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[0], self.sim_params.data_frequency) orders_txns = list(slippage_model.simulate( bar_data, self.ASSET133, open_orders, )) self.assertEquals(len(orders_txns), 0) bar_data = BarData(self.data_portal, lambda: self.minutes[1], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[3], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[3], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[3], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[0], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[0], self.sim_params.data_frequency) 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 = BarData(self.data_portal, lambda: self.minutes[1], self.sim_params.data_frequency) 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 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 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, "asset": 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, )) assert 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, )) assert 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, "asset": 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, )) assert 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, )) assert 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, "asset": 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, )) assert 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, )) assert 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), "asset": self.ASSET133, } for key, value in expected_txn.items(): assert 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, "asset": 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, )) assert 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, )) assert 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, "asset": 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, )) assert 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, )) assert 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, "asset": 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, )) assert 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, )) assert 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), "asset": self.ASSET133, } for key, value in expected_txn.items(): assert 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, "asset": 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, )) assert 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, "asset": 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, )) assert 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, "asset": 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, )) assert 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), "asset": self.ASSET133, "order_id": open_orders[0].id, } assert txn is not None for key, value in expected_txn.items(): assert 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, "asset": 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, )) assert 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, "asset": 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, )) assert 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, "asset": 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, )) assert 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), "asset": self.ASSET133, } assert txn is not None for key, value in expected_txn.items(): assert value == txn[key]