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TST: Parameterize stop order test.
So that we can more clearly demarcate each case of buy/sell and price compared to stop, and their expected outputs. Also, add comment about the current behavior versus the behavior that will be moved to in an upcoming fix.
This commit is contained in:
Eddie Hebert
+134
-84
@@ -22,6 +22,10 @@ import pytz
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from unittest import TestCase
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from nose_parameterized import parameterized
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import pandas as pd
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from zipline.finance.slippage import VolumeShareSlippage
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from zipline.protocol import Event, DATASOURCE_TYPE
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@@ -189,108 +193,154 @@ class SlippageTestCase(TestCase):
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for key, value in expected_txn.items():
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self.assertEquals(value, txn[key])
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def test_orders_stop(self):
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events = self.gen_trades()
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STOP_ORDER_CASES = {
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# Stop orders can be long/short and have their price greater or
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# less than the stop.
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#
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# A stop being reached is conditional on the order direction.
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# Long orders reach the stop when the price is greater than the stop.
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# Short orders reach the stop when the price is less than the stop.
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#
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# Which leads to the following 4 cases:
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#
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# | long | short |
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# | price > stop | | |
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# | price < stop | | |
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#
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# Currently the slippage module acts according to the following table,
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# where 'X' represents triggering a transaction
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# | long | short |
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# | price > stop | | X |
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# | price < stop | X | |
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#
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# However, the following behavior *should* be followed.
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#
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# | long | short |
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# | price > stop | X | |
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# | price < stop | | X |
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slippage_model = VolumeShareSlippage()
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# long, does not trade
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open_orders = [
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Order(**{
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'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc),
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'long | price gt stop': {
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'order': {
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'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
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'amount': 100,
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'filled': 0,
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'sid': 133,
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'stop': 3.5})
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]
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orders_txns = list(slippage_model.simulate(
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events[2],
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open_orders
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))
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self.assertEquals(len(orders_txns), 0)
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# long, does trade
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open_orders = [
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Order(**{
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'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc),
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'stop': 3.5
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},
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'event': {
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'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
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'volume': 2000,
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'price': 4.0,
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'high': 3.15,
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'low': 2.85,
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'sid': 133,
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'close': 4.0,
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'open': 3.5
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},
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'expected': {
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'transaction': None
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}
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},
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'long | price lt stop': {
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'order': {
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'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
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'amount': 100,
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'filled': 0,
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'sid': 133,
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'stop': 3.6
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})
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]
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orders_txns = list(slippage_model.simulate(
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events[3],
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open_orders
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))
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self.assertEquals(len(orders_txns), 1)
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_, txn = orders_txns[0]
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expected_txn = {
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'price': float(3.500875),
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'dt': datetime.datetime(
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2006, 1, 5, 14, 34, tzinfo=pytz.utc),
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'amount': int(100),
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'sid': int(133),
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'order_id': open_orders[0].id
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}
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for key, value in expected_txn.items():
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self.assertEquals(value, txn[key])
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# short, does not trade
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open_orders = [
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Order(**{
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'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc),
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},
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'event': {
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'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
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'volume': 2000,
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'price': 3.5,
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'high': 3.15,
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'low': 2.85,
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'sid': 133,
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'close': 3.5,
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'open': 4.0
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},
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'expected': {
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'transaction': {
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'price': 3.500875,
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'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
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'amount': 100,
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'sid': 133,
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}
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},
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},
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'short | price gt stop': {
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'order': {
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'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
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'amount': -100,
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'filled': 0,
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'sid': 133,
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'stop': 3.5})
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]
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orders_txns = list(slippage_model.simulate(
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events[0],
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open_orders
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))
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self.assertEquals(len(orders_txns), 0)
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# short, does trade
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open_orders = [
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Order(**{
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'dt': datetime.datetime(2006, 1, 5, 14, 30, tzinfo=pytz.utc),
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'stop': 3.4
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},
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'event': {
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'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
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'volume': 2000,
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'price': 3.5,
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'high': 3.15,
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'low': 2.85,
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'sid': 133,
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'close': 3.5,
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'open': 3.0
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},
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'expected': {
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'transaction': {
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'price': 3.499125,
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'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
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'amount': -100,
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'sid': 133,
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}
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}
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},
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'short | price lt stop': {
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'order': {
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'dt': pd.Timestamp('2006-01-05 14:30', tz='UTC'),
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'amount': -100,
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'filled': 0,
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'sid': 133,
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'stop': 3.4})
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]
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'stop': 3.5
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},
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'event': {
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'dt': pd.Timestamp('2006-01-05 14:31', tz='UTC'),
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'volume': 2000,
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'price': 3.0,
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'high': 3.15,
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'low': 2.85,
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'sid': 133,
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'close': 3.0,
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'open': 3.0
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},
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'expected': {
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'transaction': None
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}
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},
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}
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orders_txns = list(slippage_model.simulate(
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events[1],
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open_orders
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))
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@parameterized.expand([
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(name, case['order'], case['event'], case['expected'])
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for name, case in STOP_ORDER_CASES.items()
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])
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def test_orders_stop(self, name, order_data, event_data, expected):
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order = Order(**order_data)
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event = Event(initial_values=event_data)
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self.assertEquals(len(orders_txns), 1)
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_, txn = orders_txns[0]
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slippage_model = VolumeShareSlippage()
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expected_txn = {
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'price': float(3.499125),
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'dt': datetime.datetime(
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2006, 1, 5, 14, 32, tzinfo=pytz.utc),
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'amount': int(-100),
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'sid': int(133)
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}
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try:
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_, txn = slippage_model.simulate(event, [order]).next()
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except StopIteration:
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txn = None
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for key, value in expected_txn.items():
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self.assertEquals(value, txn[key])
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if expected['transaction'] is None:
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self.assertIsNone(txn)
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else:
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self.assertIsNotNone(txn)
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for key, value in expected['transaction'].items():
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self.assertEquals(value, txn[key])
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def test_orders_stop_limit(self):
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