Files
catalyst/tests/finance/test_slippage.py
T
Eddie Hebert 36f8b77290 MAINT: Support both Python 2 and 3 next interfaces.
Python 3 uses the `__next__` method instead of `next`,
and uses the syntax of `next(foo)` accordingly.

Add `__next__` and `next` side-by-side so both Python 2 and 3 have
a method that can be used during iteration.
2014-01-07 11:46:57 -05:00

557 lines
16 KiB
Python

#
# Copyright 2013 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Unit tests for finance.slippage
"""
import datetime
import pytz
from unittest import TestCase
from nose_parameterized import parameterized
import pandas as pd
from zipline.finance.slippage import VolumeShareSlippage
from zipline.protocol import Event, DATASOURCE_TYPE
from zipline.finance.blotter import Order
class SlippageTestCase(TestCase):
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_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])
STOP_ORDER_CASES = {
# Stop orders can be long/short and have their price greater or
# less than the stop.
#
# A stop being reached is conditional on the order direction.
# Long orders reach the stop when the price is greater than the stop.
# Short orders reach the stop when the price is less than the stop.
#
# Which leads to the following 4 cases:
#
# | long | short |
# | price > stop | | |
# | price < stop | | |
#
# Currently the slippage module acts according to the following table,
# where 'X' represents triggering a transaction
# | long | short |
# | price > stop | | X |
# | price < stop | X | |
#
# However, the following behavior *should* be followed.
#
# | long | short |
# | price > stop | X | |
# | price < stop | | X |
'long | price gt stop': {
'order': {
'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
'amount': 100,
'filled': 0,
'sid': 133,
'stop': 3.5
},
'event': {
'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
'volume': 2000,
'price': 4.0,
'high': 3.15,
'low': 2.85,
'sid': 133,
'close': 4.0,
'open': 3.5
},
'expected': {
'transaction': {
'price': 4.001,
'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
'amount': 100,
'sid': 133,
}
}
},
'long | price lt stop': {
'order': {
'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
'amount': 100,
'filled': 0,
'sid': 133,
'stop': 3.6
},
'event': {
'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
'volume': 2000,
'price': 3.5,
'high': 3.15,
'low': 2.85,
'sid': 133,
'close': 3.5,
'open': 4.0
},
'expected': {
'transaction': None
}
},
'short | price gt stop': {
'order': {
'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
'amount': -100,
'filled': 0,
'sid': 133,
'stop': 3.4
},
'event': {
'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
'volume': 2000,
'price': 3.5,
'high': 3.15,
'low': 2.85,
'sid': 133,
'close': 3.5,
'open': 3.0
},
'expected': {
'transaction': None
}
},
'short | price lt stop': {
'order': {
'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
'amount': -100,
'filled': 0,
'sid': 133,
'stop': 3.5
},
'event': {
'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
'volume': 2000,
'price': 3.0,
'high': 3.15,
'low': 2.85,
'sid': 133,
'close': 3.0,
'open': 3.0
},
'expected': {
'transaction': {
'price': 2.99925,
'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
'amount': -100,
'sid': 133,
}
}
},
}
@parameterized.expand([
(name, case['order'], case['event'], case['expected'])
for name, case in STOP_ORDER_CASES.items()
])
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 = next(slippage_model.simulate(event, [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_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,
'stop': 4.0,
'limit': 3.0})
]
orders_txns = list(slippage_model.simulate(
events[2],
open_orders
))
self.assertEquals(len(orders_txns), 0)
orders_txns = list(slippage_model.simulate(
events[3],
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,
'stop': 4.0,
'limit': 3.5})
]
orders_txns = list(slippage_model.simulate(
events[2],
open_orders
))
self.assertEquals(len(orders_txns), 0)
orders_txns = list(slippage_model.simulate(
events[3],
open_orders
))
self.assertEquals(len(orders_txns), 1)
_, txn = orders_txns[0]
expected_txn = {
'price': float(3.500875),
'dt': datetime.datetime(
2006, 1, 5, 14, 34, tzinfo=pytz.utc),
'amount': int(100),
'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': 133,
'stop': 3.0,
'limit': 4.0})
]
orders_txns = list(slippage_model.simulate(
events[0],
open_orders
))
self.assertEquals(len(orders_txns), 0)
orders_txns = list(slippage_model.simulate(
events[1],
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': 133,
'stop': 3.0,
'limit': 3.5})
]
orders_txns = list(slippage_model.simulate(
events[0],
open_orders
))
self.assertEquals(len(orders_txns), 0)
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)
}
for key, value in expected_txn.items():
self.assertEquals(value, txn[key])
def gen_trades(self):
# create a sequence of trades
events = [
Event({
'volume': 2000,
'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
}),
Event({
'volume': 2000,
'type': 4,
'price': 3.5,
'datetime': datetime.datetime(
2006, 1, 5, 14, 32, tzinfo=pytz.utc),
'high': 3.15,
'low': 2.85,
'sid': 133,
'source_id': 'test_source',
'close': 3.5,
'dt':
datetime.datetime(2006, 1, 5, 14, 32, tzinfo=pytz.utc),
'open': 3.0
}),
Event({
'volume': 2000,
'type': 4,
'price': 4.0,
'datetime': datetime.datetime(
2006, 1, 5, 14, 33, tzinfo=pytz.utc),
'high': 3.15,
'low': 2.85,
'sid': 133,
'source_id': 'test_source',
'close': 4.0,
'dt':
datetime.datetime(2006, 1, 5, 14, 33, tzinfo=pytz.utc),
'open': 3.5
}),
Event({
'volume': 2000,
'type': 4,
'price': 3.5,
'datetime': datetime.datetime(
2006, 1, 5, 14, 34, tzinfo=pytz.utc),
'high': 3.15,
'low': 2.85,
'sid': 133,
'source_id': 'test_source',
'close': 3.5,
'dt':
datetime.datetime(2006, 1, 5, 14, 34, tzinfo=pytz.utc),
'open': 4.0
}),
Event({
'volume': 2000,
'type': 4,
'price': 3.0,
'datetime': datetime.datetime(
2006, 1, 5, 14, 35, 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, 35, tzinfo=pytz.utc),
'open': 3.5
})
]
return events