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]
