def setUp(self):
self.sim_params = factory.create_simulation_parameters(num_days=4)
self.sid = 133
self.trade_history = factory.create_trade_history(
self.sid, [10.0, 10.0, 11.0, 11.0], [100, 100, 100, 300],
timedelta(days=1), self.sim_params)
self.source = SpecificEquityTrades(event_list=self.trade_history)
def test_single_source(self):
# Just using the built-in defaults. See
# zipline.sources.py
source = SpecificEquityTrades()
expected = list(source)
source.rewind()
# The raw source doesn't handle done messaging, so we need to
# append a done message for sort to work properly.
with_done = chain(source, [done_message(source.get_hash())])
self.run_date_sort(with_done, expected, [source.get_hash()])
class TestAccountControls(TestCase):
def setUp(self):
self.sim_params = factory.create_simulation_parameters(num_days=4)
self.sid = 133
self.trade_history = factory.create_trade_history(
self.sid,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
self.sim_params
)
self.source = SpecificEquityTrades(event_list=self.trade_history)
def _check_algo(self,
algo,
handle_data,
expected_exc):
algo._handle_data = handle_data
with self.assertRaises(expected_exc) if expected_exc else nullctx():
algo.run(self.source)
self.source.rewind()
def check_algo_succeeds(self, algo, handle_data):
# Default for order_count assumes one order per handle_data call.
self._check_algo(algo, handle_data, None)
def check_algo_fails(self, algo, handle_data):
self._check_algo(algo,
handle_data,
AccountControlViolation)
def test_set_max_leverage(self):
# Set max leverage to 0 so buying one share fails.
def handle_data(algo, data):
algo.order(self.sid, 1)
algo = SetMaxLeverageAlgorithm(0)
self.check_algo_fails(algo, handle_data)
# Set max leverage to 1 so buying one share passes
def handle_data(algo, data):
algo.order(self.sid, 1)
algo = SetMaxLeverageAlgorithm(1)
self.check_algo_succeeds(algo, handle_data)
class TestAccountControls(TestCase):
def setUp(self):
self.sim_params = factory.create_simulation_parameters(num_days=4)
self.sidint = 133
self.trade_history = factory.create_trade_history(
self.sidint,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
self.sim_params
)
self.source = SpecificEquityTrades(event_list=self.trade_history)
def _check_algo(self,
algo,
handle_data,
expected_exc):
algo._handle_data = handle_data
with self.assertRaises(expected_exc) if expected_exc else nullctx():
algo.run(self.source)
self.source.rewind()
def check_algo_succeeds(self, algo, handle_data):
# Default for order_count assumes one order per handle_data call.
self._check_algo(algo, handle_data, None)
def check_algo_fails(self, algo, handle_data):
self._check_algo(algo,
handle_data,
AccountControlViolation)
def test_set_max_leverage(self):
# Set max leverage to 0 so buying one share fails.
def handle_data(algo, data):
algo.order(algo.sid(self.sidint), 1)
algo = SetMaxLeverageAlgorithm(0)
self.check_algo_fails(algo, handle_data)
# Set max leverage to 1 so buying one share passes
def handle_data(algo, data):
algo.order(algo.sid(self.sidint), 1)
algo = SetMaxLeverageAlgorithm(1)
self.check_algo_succeeds(algo, handle_data)
def test_moving_stddev(self):
trade_history = factory.create_trade_history(
133,
[10.0, 15.0, 13.0, 12.0],
[100, 100, 100, 100],
timedelta(days=1),
self.sim_params
)
stddev = MovingStandardDev(
market_aware=True,
window_length=3,
)
self.source = SpecificEquityTrades(event_list=trade_history)
transformed = list(stddev.transform(self.source))
vals = [message[stddev.get_hash()] for message in transformed]
expected = [
None,
np.std([10.0, 15.0], ddof=1),
np.std([10.0, 15.0, 13.0], ddof=1),
np.std([15.0, 13.0, 12.0], ddof=1),
]
# np has odd rounding behavior, cf.
# http://docs.scipy.org/doc/np/reference/generated/np.std.html
for v1, v2 in zip(vals, expected):
if v1 is None:
self.assertIsNone(v2)
continue
self.assertEquals(round(v1, 5), round(v2, 5))
def test_returns(self):
# Daily returns.
returns = Returns(1)
transformed = list(returns.transform(self.source))
tnfm_vals = [message.tnfm_value for message in transformed]
# No returns for the first event because we don't have a
# previous close.
expected = [0.0, 0.0, 0.1, 0.0]
assert tnfm_vals == expected
# Two-day returns. An extra kink here is that the
# factory will automatically skip a weekend for the
# last event. Results shouldn't notice this blip.
trade_history = factory.create_trade_history(
133, [10.0, 15.0, 13.0, 12.0, 13.0], [100, 100, 100, 300, 100],
timedelta(days=1), self.trading_environment)
self.source = SpecificEquityTrades(event_list=trade_history)
returns = StatefulTransform(Returns, 2)
transformed = list(returns.transform(self.source))
tnfm_vals = [message.tnfm_value for message in transformed]
expected = [
0.0, 0.0, (13.0 - 10.0) / 10.0, (12.0 - 15.0) / 15.0,
(13.0 - 13.0) / 13.0
]
assert tnfm_vals == expected
def test_moving_stddev(self):
trade_history = factory.create_trade_history(133,
[10.0, 15.0, 13.0, 12.0],
[100, 100, 100, 100],
timedelta(hours=1),
self.trading_environment)
stddev = MovingStandardDev(
market_aware=False,
delta=timedelta(minutes=150),
)
self.source = SpecificEquityTrades(event_list=trade_history)
transformed = list(stddev.transform(self.source))
vals = [message.tnfm_value for message in transformed]
expected = [
None,
np.std([10.0, 15.0], ddof=1),
np.std([10.0, 15.0, 13.0], ddof=1),
np.std([15.0, 13.0, 12.0], ddof=1),
]
# np has odd rounding behavior, cf.
# http://docs.scipy.org/doc/np/reference/generated/np.std.html
for v1, v2 in zip(vals, expected):
if v1 is None:
assert v2 is None
continue
assert round(v1, 5) == round(v2, 5)
def create_trade_source(sids,
trade_time_increment,
sim_params,
asset_finder,
trading_calendar):
# If the sim_params define an end that is during market hours, that will be
# used as the end of the data source
if trading_calendar.is_open_on_minute(sim_params.end_session):
end = sim_params.end_session
# Otherwise, the last_close after the end_session is used as the end of the
# data source
else:
end = sim_params.last_close
args = tuple()
kwargs = {
'sids': sids,
'start': sim_params.first_open,
'end': end,
'delta': trade_time_increment,
'trading_calendar': trading_calendar,
'asset_finder': asset_finder,
}
source = SpecificEquityTrades(*args, **kwargs)
return source
def test_algo_with_rl_violation_cumulative(self):
"""
Add a new restriction, run a test long after both
knowledge dates, make sure stock from original restriction
set is still disallowed.
"""
sim_params = factory.create_simulation_parameters(
start=list(LEVERAGED_ETFS.keys())[0] + timedelta(days=7),
num_days=4)
with security_list_copy():
add_security_data(['AAPL'], [])
trade_history = factory.create_trade_history(
'BZQ',
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
sim_params,
env=self.env,
)
self.source = SpecificEquityTrades(event_list=trade_history,
env=self.env)
algo = RestrictedAlgoWithoutCheck(symbol='BZQ',
sim_params=sim_params,
env=self.env)
with self.assertRaises(TradingControlViolation) as ctx:
algo.run(self.source)
self.check_algo_exception(algo, ctx, 0)
def test_set_max_order_count(self):
# Override the default setUp to use six-hour intervals instead of full
# days so we can exercise trading-session rollover logic.
trade_history = factory.create_trade_history(
self.sid,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(hours=6),
self.sim_params
)
self.source = SpecificEquityTrades(event_list=trade_history)
def handle_data(algo, data):
for i in range(5):
algo.order(self.sid, 1)
algo.order_count += 1
algo = SetMaxOrderCountAlgorithm(3)
self.check_algo_fails(algo, handle_data, 3)
# Second call to handle_data is the same day as the first, so the last
# order of the second call should fail.
algo = SetMaxOrderCountAlgorithm(9)
self.check_algo_fails(algo, handle_data, 9)
# Only ten orders are placed per day, so this should pass even though
# in total more than 20 orders are placed.
algo = SetMaxOrderCountAlgorithm(10)
self.check_algo_succeeds(algo, handle_data, order_count=20)
def create_trade_source(sids,
trade_time_increment,
sim_params,
env,
concurrent=False):
# If the sim_params define an end that is during market hours, that will be
# used as the end of the data source
if env.is_market_hours(sim_params.period_end):
end = sim_params.period_end
# Otherwise, the last_close after the period_end is used as the end of the
# data source
else:
end = sim_params.last_close
args = tuple()
kwargs = {
'sids': sids,
'start': sim_params.first_open,
'end': end,
'delta': trade_time_increment,
'filter': sids,
'concurrent': concurrent,
'env': env,
}
source = SpecificEquityTrades(*args, **kwargs)
return source
def setUp(self):
self.trading_environment = factory.create_trading_environment()
setup_logger(self)
trade_history = factory.create_trade_history(133,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
self.trading_environment)
self.source = SpecificEquityTrades(event_list=trade_history)
def setUp(self):
self.sim_params = factory.create_simulation_parameters()
trade_history = factory.create_trade_history(133,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
self.sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
self.df_source, self.df = \
factory.create_test_df_source(self.sim_params)
def test_algo_with_rl_violation(self):
sim_params = factory.create_simulation_parameters(
start=list(LEVERAGED_ETFS.keys())[0], num_days=4)
trade_history = factory.create_trade_history(
'BZQ',
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
sim_params
)
self.source = SpecificEquityTrades(event_list=trade_history)
self.df_source, self.df = \
factory.create_test_df_source(sim_params)
algo = RestrictedAlgoWithoutCheck(sid='BZQ', sim_params=sim_params)
with self.assertRaises(TradingControlViolation) as ctx:
algo.run(self.source)
self.check_algo_exception(algo, ctx, 0)
# repeat with a symbol from a different lookup date
trade_history = factory.create_trade_history(
'JFT',
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
sim_params
)
self.source = SpecificEquityTrades(event_list=trade_history)
self.df_source, self.df = \
factory.create_test_df_source(sim_params)
algo = RestrictedAlgoWithoutCheck(sid='JFT', sim_params=sim_params)
with self.assertRaises(TradingControlViolation) as ctx:
algo.run(self.source)
self.check_algo_exception(algo, ctx, 0)
def setUp(self):
self.sim_params = factory.create_simulation_parameters(num_days=4)
self.sid = 133
self.trade_history = factory.create_trade_history(
self.sid,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
self.sim_params
)
self.source = SpecificEquityTrades(event_list=self.trade_history)
def test_algo_without_rl_violation(self):
sim_params = factory.create_simulation_parameters(start=list(
LEVERAGED_ETFS.keys())[0],
num_days=4)
trade_history = factory.create_trade_history('AAPL',
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
algo = RestrictedAlgoWithoutCheck(symbol='AAPL', sim_params=sim_params)
algo.run(self.source)
def test_iterate_over_rl(self):
sim_params = factory.create_simulation_parameters(start=list(
LEVERAGED_ETFS.keys())[0],
num_days=4)
trade_history = factory.create_trade_history('BZQ',
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
algo = IterateRLAlgo(symbol='BZQ', sim_params=sim_params)
algo.run(self.source)
self.assertTrue(algo.found)
def test_algo_with_rl_violation_after_add(self):
with security_list_copy():
add_security_data(['AAPL'], [])
sim_params = factory.create_simulation_parameters(
start=self.trading_day_before_first_kd, num_days=4)
trade_history = factory.create_trade_history(
'AAPL', [10.0, 10.0, 11.0, 11.0], [100, 100, 100, 300],
timedelta(days=1), sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
algo = RestrictedAlgoWithoutCheck(symbol='AAPL',
sim_params=sim_params)
with self.assertRaises(TradingControlViolation) as ctx:
algo.run(self.source)
self.check_algo_exception(algo, ctx, 2)
def test_algo_without_rl_violation_after_delete(self):
with security_list_copy():
# add a delete statement removing bzq
# write a new delete statement file to disk
add_security_data([], ['BZQ'])
sim_params = factory.create_simulation_parameters(
start=self.extra_knowledge_date, num_days=3)
trade_history = factory.create_trade_history(
'BZQ', [10.0, 10.0, 11.0, 11.0], [100, 100, 100, 300],
timedelta(days=1), sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
algo = RestrictedAlgoWithoutCheck(symbol='BZQ',
sim_params=sim_params)
algo.run(self.source)
def test_algo_with_rl_violation_after_knowledge_date(self):
sim_params = factory.create_simulation_parameters(
start=list(LEVERAGED_ETFS.keys())[0] + timedelta(days=7),
num_days=5)
trade_history = factory.create_trade_history('BZQ',
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
algo = RestrictedAlgoWithoutCheck(symbol='BZQ', sim_params=sim_params)
with self.assertRaises(TradingControlViolation) as ctx:
algo.run(self.source)
self.check_algo_exception(algo, ctx, 0)
def test_algo_with_rl_violation_on_knowledge_date(self):
sim_params = factory.create_simulation_parameters(
start=self.trading_day_before_first_kd, num_days=4)
trade_history = factory.create_trade_history('BZQ',
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
algo = RestrictedAlgoWithoutCheck(sid='BZQ', sim_params=sim_params)
with self.assertRaises(TradingControlViolation) as ctx:
algo.run(self.source)
self.check_algo_exception(algo, ctx, 1)
def test_single_source(self):
# Just using the built-in defaults. See
# zipline.sources.py
source = SpecificEquityTrades()
expected = list(source)
source.rewind()
# The raw source doesn't handle done messaging, so we need to
# append a done message for sort to work properly.
with_done = chain(source, [done_message(source.get_hash())])
self.run_date_sort(with_done, expected, [source.get_hash()])
def setUp(self):
days = 251
self.sim_params = factory.create_simulation_parameters(num_days=days)
setup_logger(self)
trade_history = factory.create_trade_history(133, [10.0] * days,
[100] * days,
timedelta(days=1),
self.sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
self.df_source, self.df = \
factory.create_test_df_source(self.sim_params)
self.zipline_test_config = {
'sid': 0,
}
def create_trade_source(sids, trade_count,
trade_time_increment, sim_params,
concurrent=False):
args = tuple()
kwargs = {
'count': trade_count,
'sids': sids,
'start': sim_params.first_open,
'delta': trade_time_increment,
'filter': sids,
'concurrent': concurrent
}
source = SpecificEquityTrades(*args, **kwargs)
# TODO: do we need to set the trading environment's end to same dt as
# the last trade in the history?
# sim_params.period_end = trade_history[-1].dt
return source
def test_returns(self, name, add_custom_events):
# Daily returns.
returns = Returns(1)
if add_custom_events:
self.source = self.intersperse_custom_events(self.source)
transformed = list(returns.transform(self.source))
tnfm_vals = [
message[returns.get_hash()] for message in transformed
if message.type != DATASOURCE_TYPE.CUSTOM
]
# No returns for the first event because we don't have a
# previous close.
expected = [0.0, 0.0, 0.1, 0.0]
self.assertEquals(tnfm_vals, expected)
# Two-day returns. An extra kink here is that the
# factory will automatically skip a weekend for the
# last event. Results shouldn't notice this blip.
trade_history = factory.create_trade_history(
133, [10.0, 15.0, 13.0, 12.0, 13.0], [100, 100, 100, 300, 100],
timedelta(days=1), self.sim_params)
self.source = SpecificEquityTrades(event_list=trade_history)
returns = StatefulTransform(Returns, 2)
transformed = list(returns.transform(self.source))
tnfm_vals = [message[returns.get_hash()] for message in transformed]
expected = [
0.0, 0.0, (13.0 - 10.0) / 10.0, (12.0 - 15.0) / 15.0,
(13.0 - 13.0) / 13.0
]
self.assertEquals(tnfm_vals, expected)
def test_sort_composite(self):
filter = [1, 2]
#Set up source a. One hour between events.
args_a = tuple()
kwargs_a = {
'count': 100,
'sids': [1],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(hours=1),
'filter': filter
}
source_a = SpecificEquityTrades(*args_a, **kwargs_a)
#Set up source b. One day between events.
args_b = tuple()
kwargs_b = {
'count': 50,
'sids': [2],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(days=1),
'filter': filter
}
source_b = SpecificEquityTrades(*args_b, **kwargs_b)
#Set up source c. One minute between events.
args_c = tuple()
kwargs_c = {
'count': 150,
'sids': [1, 2],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(minutes=1),
'filter': filter
}
source_c = SpecificEquityTrades(*args_c, **kwargs_c)
# Set up source d. This should produce no events because the
# internal sids don't match the filter.
args_d = tuple()
kwargs_d = {
'count': 50,
'sids': [3],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(minutes=1),
'filter': filter
}
source_d = SpecificEquityTrades(*args_d, **kwargs_d)
sources = [source_a, source_b, source_c, source_d]
hashes = [source.get_hash() for source in sources]
sort_out = date_sorted_sources(*sources)
# Read all the values from sort and assert that they arrive in
# the correct sorting with the expected hash values.
to_list = list(sort_out)
copy = to_list[:]
# We should have 300 events (100 from a, 150 from b, 50 from c)
assert len(to_list) == 300
for e in to_list:
# All events should match one of our expected source_ids.
assert e.source_id in hashes
# But none of them should match source_d.
assert e.source_id != source_d.get_hash()
# The events should be sorted by dt, with source_id as tiebreaker.
expected = sorted(copy, comp)
assert to_list == expected
def test_multi_source(self):
filter = [2, 3]
args_a = tuple()
kwargs_a = {
'count': 100,
'sids': [1, 2, 3],
'start': datetime(2012, 1, 3, 15, tzinfo=pytz.utc),
'delta': timedelta(minutes=6),
'filter': filter
}
source_a = SpecificEquityTrades(*args_a, **kwargs_a)
args_b = tuple()
kwargs_b = {
'count': 100,
'sids': [2, 3, 4],
'start': datetime(2012, 1, 3, 15, tzinfo=pytz.utc),
'delta': timedelta(minutes=5),
'filter': filter
}
source_b = SpecificEquityTrades(*args_b, **kwargs_b)
all_events = list(chain(source_a, source_b))
# The expected output is all events, sorted by dt with
# source_id as a tiebreaker.
expected = sorted(all_events, comp)
source_ids = [source_a.get_hash(), source_b.get_hash()]
# Generating the events list consumes the sources. Rewind them
# for testing.
source_a.rewind()
source_b.rewind()
# Append a done message to each source.
with_done_a = chain(source_a, [done_message(source_a.get_hash())])
with_done_b = chain(source_b, [done_message(source_b.get_hash())])
interleaved = alternate(with_done_a, with_done_b)
# Test sort with alternating messages from source_a and
# source_b.
self.run_date_sort(interleaved, expected, source_ids)
source_a.rewind()
source_b.rewind()
with_done_a = chain(source_a, [done_message(source_a.get_hash())])
with_done_b = chain(source_b, [done_message(source_b.get_hash())])
sequential = chain(with_done_a, with_done_b)
# Test sort with all messages from a, followed by all messages
# from b.
self.run_date_sort(sequential, expected, source_ids)
def test_multi_source(self):
filter = [2, 3]
args_a = tuple()
kwargs_a = {
'count': 100,
'sids': [1, 2, 3],
'start': datetime(2012, 1, 3, 15, tzinfo=pytz.utc),
'delta': timedelta(minutes=6),
'filter': filter
}
source_a = SpecificEquityTrades(*args_a, **kwargs_a)
args_b = tuple()
kwargs_b = {
'count': 100,
'sids': [2, 3, 4],
'start': datetime(2012, 1, 3, 15, tzinfo=pytz.utc),
'delta': timedelta(minutes=5),
'filter': filter
}
source_b = SpecificEquityTrades(*args_b, **kwargs_b)
all_events = list(chain(source_a, source_b))
# The expected output is all events, sorted by dt with
# source_id as a tiebreaker.
expected = sorted(all_events, comp)
source_ids = [source_a.get_hash(), source_b.get_hash()]
# Generating the events list consumes the sources. Rewind them
# for testing.
source_a.rewind()
source_b.rewind()
# Append a done message to each source.
with_done_a = chain(source_a, [done_message(source_a.get_hash())])
with_done_b = chain(source_b, [done_message(source_b.get_hash())])
interleaved = alternate(with_done_a, with_done_b)
# Test sort with alternating messages from source_a and
# source_b.
self.run_date_sort(interleaved, expected, source_ids)
source_a.rewind()
source_b.rewind()
with_done_a = chain(source_a, [done_message(source_a.get_hash())])
with_done_b = chain(source_b, [done_message(source_b.get_hash())])
sequential = chain(with_done_a, with_done_b)
# Test sort with all messages from a, followed by all messages
# from b.
self.run_date_sort(sequential, expected, source_ids)
def test_sort_composite(self):
filter = [1, 2]
#Set up source a. One hour between events.
args_a = tuple()
kwargs_a = {
'count': 100,
'sids': [1],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(hours=1),
'filter': filter
}
source_a = SpecificEquityTrades(*args_a, **kwargs_a)
#Set up source b. One day between events.
args_b = tuple()
kwargs_b = {
'count': 50,
'sids': [2],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(days=1),
'filter': filter
}
source_b = SpecificEquityTrades(*args_b, **kwargs_b)
#Set up source c. One minute between events.
args_c = tuple()
kwargs_c = {
'count': 150,
'sids': [1, 2],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(minutes=1),
'filter': filter
}
source_c = SpecificEquityTrades(*args_c, **kwargs_c)
# Set up source d. This should produce no events because the
# internal sids don't match the filter.
args_d = tuple()
kwargs_d = {
'count': 50,
'sids': [3],
'start': datetime(2012, 6, 6, 0),
'delta': timedelta(minutes=1),
'filter': filter
}
source_d = SpecificEquityTrades(*args_d, **kwargs_d)
sources = [source_a, source_b, source_c, source_d]
hashes = [source.get_hash() for source in sources]
sort_out = date_sorted_sources(*sources)
# Read all the values from sort and assert that they arrive in
# the correct sorting with the expected hash values.
to_list = list(sort_out)
copy = to_list[:]
# We should have 300 events (100 from a, 150 from b, 50 from c)
assert len(to_list) == 300
for e in to_list:
# All events should match one of our expected source_ids.
assert e.source_id in hashes
# But none of them should match source_d.
assert e.source_id != source_d.get_hash()
# The events should be sorted by dt, with source_id as tiebreaker.
expected = sorted(copy, comp)
assert to_list == expected
class TestTradingControls(TestCase):
def setUp(self):
self.sim_params = factory.create_simulation_parameters(num_days=4)
self.sid = 133
self.trade_history = factory.create_trade_history(
self.sid,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(days=1),
self.sim_params
)
self.source = SpecificEquityTrades(event_list=self.trade_history)
def _check_algo(self,
algo,
handle_data,
expected_order_count,
expected_exc):
algo._handle_data = handle_data
with self.assertRaises(expected_exc) if expected_exc else nullctx():
algo.run(self.source)
self.assertEqual(algo.order_count, expected_order_count)
self.source.rewind()
def check_algo_succeeds(self, algo, handle_data, order_count=4):
# Default for order_count assumes one order per handle_data call.
self._check_algo(algo, handle_data, order_count, None)
def check_algo_fails(self, algo, handle_data, order_count):
self._check_algo(algo,
handle_data,
order_count,
TradingControlViolation)
def test_set_max_position_size(self):
# Buy one share four times. Should be fine.
def handle_data(algo, data):
algo.order(self.sid, 1)
algo.order_count += 1
algo = SetMaxPositionSizeAlgorithm(sid=self.sid,
max_shares=10,
max_notional=500.0)
self.check_algo_succeeds(algo, handle_data)
# Buy three shares four times. Should bail on the fourth before it's
# placed.
def handle_data(algo, data):
algo.order(self.sid, 3)
algo.order_count += 1
algo = SetMaxPositionSizeAlgorithm(sid=self.sid,
max_shares=10,
max_notional=500.0)
self.check_algo_fails(algo, handle_data, 3)
# Buy two shares four times. Should bail due to max_notional on the
# third attempt.
def handle_data(algo, data):
algo.order(self.sid, 3)
algo.order_count += 1
algo = SetMaxPositionSizeAlgorithm(sid=self.sid,
max_shares=10,
max_notional=61.0)
self.check_algo_fails(algo, handle_data, 2)
# Set the trading control to a different sid, then BUY ALL THE THINGS!.
# Should continue normally.
def handle_data(algo, data):
algo.order(self.sid, 10000)
algo.order_count += 1
algo = SetMaxPositionSizeAlgorithm(sid=self.sid + 1,
max_shares=10,
max_notional=61.0)
self.check_algo_succeeds(algo, handle_data)
# Set the trading control sid to None, then BUY ALL THE THINGS!. Should
# fail because setting sid to None makes the control apply to all sids.
def handle_data(algo, data):
algo.order(self.sid, 10000)
algo.order_count += 1
algo = SetMaxPositionSizeAlgorithm(max_shares=10, max_notional=61.0)
self.check_algo_fails(algo, handle_data, 0)
def test_set_max_order_size(self):
# Buy one share.
def handle_data(algo, data):
algo.order(self.sid, 1)
algo.order_count += 1
algo = SetMaxOrderSizeAlgorithm(sid=self.sid,
max_shares=10,
max_notional=500.0)
self.check_algo_succeeds(algo, handle_data)
# Buy 1, then 2, then 3, then 4 shares. Bail on the last attempt
# because we exceed shares.
def handle_data(algo, data):
algo.order(self.sid, algo.order_count + 1)
algo.order_count += 1
algo = SetMaxOrderSizeAlgorithm(sid=self.sid,
max_shares=3,
max_notional=500.0)
self.check_algo_fails(algo, handle_data, 3)
# Buy 1, then 2, then 3, then 4 shares. Bail on the last attempt
# because we exceed notional.
def handle_data(algo, data):
algo.order(self.sid, algo.order_count + 1)
algo.order_count += 1
algo = SetMaxOrderSizeAlgorithm(sid=self.sid,
max_shares=10,
max_notional=40.0)
self.check_algo_fails(algo, handle_data, 3)
# Set the trading control to a different sid, then BUY ALL THE THINGS!.
# Should continue normally.
def handle_data(algo, data):
algo.order(self.sid, 10000)
algo.order_count += 1
algo = SetMaxOrderSizeAlgorithm(sid=self.sid + 1,
max_shares=1,
max_notional=1.0)
self.check_algo_succeeds(algo, handle_data)
# Set the trading control sid to None, then BUY ALL THE THINGS!.
# Should fail because not specifying a sid makes the trading control
# apply to all sids.
def handle_data(algo, data):
algo.order(self.sid, 10000)
algo.order_count += 1
algo = SetMaxOrderSizeAlgorithm(max_shares=1,
max_notional=1.0)
self.check_algo_fails(algo, handle_data, 0)
def test_set_max_order_count(self):
# Override the default setUp to use six-hour intervals instead of full
# days so we can exercise trading-session rollover logic.
trade_history = factory.create_trade_history(
self.sid,
[10.0, 10.0, 11.0, 11.0],
[100, 100, 100, 300],
timedelta(hours=6),
self.sim_params
)
self.source = SpecificEquityTrades(event_list=trade_history)
def handle_data(algo, data):
for i in range(5):
algo.order(self.sid, 1)
algo.order_count += 1
algo = SetMaxOrderCountAlgorithm(3)
self.check_algo_fails(algo, handle_data, 3)
# Second call to handle_data is the same day as the first, so the last
# order of the second call should fail.
algo = SetMaxOrderCountAlgorithm(9)
self.check_algo_fails(algo, handle_data, 9)
# Only ten orders are placed per day, so this should pass even though
# in total more than 20 orders are placed.
algo = SetMaxOrderCountAlgorithm(10)
self.check_algo_succeeds(algo, handle_data, order_count=20)
def test_long_only(self):
# Sell immediately -> fail immediately.
def handle_data(algo, data):
algo.order(self.sid, -1)
algo.order_count += 1
algo = SetLongOnlyAlgorithm()
self.check_algo_fails(algo, handle_data, 0)
# Buy on even days, sell on odd days. Never takes a short position, so
# should succeed.
def handle_data(algo, data):
if (algo.order_count % 2) == 0:
algo.order(self.sid, 1)
else:
algo.order(self.sid, -1)
algo.order_count += 1
algo = SetLongOnlyAlgorithm()
self.check_algo_succeeds(algo, handle_data)
# Buy on first three days, then sell off holdings. Should succeed.
def handle_data(algo, data):
amounts = [1, 1, 1, -3]
algo.order(self.sid, amounts[algo.order_count])
algo.order_count += 1
algo = SetLongOnlyAlgorithm()
self.check_algo_succeeds(algo, handle_data)
# Buy on first three days, then sell off holdings plus an extra share.
# Should fail on the last sale.
def handle_data(algo, data):
amounts = [1, 1, 1, -4]
algo.order(self.sid, amounts[algo.order_count])
algo.order_count += 1
algo = SetLongOnlyAlgorithm()
self.check_algo_fails(algo, handle_data, 3)
def test_register_post_init(self):
def initialize(algo):
algo.initialized = True
def handle_data(algo, data):
with self.assertRaises(RegisterTradingControlPostInit):
algo.set_max_position_size(self.sid, 1, 1)
with self.assertRaises(RegisterTradingControlPostInit):
algo.set_max_order_size(self.sid, 1, 1)
with self.assertRaises(RegisterTradingControlPostInit):
algo.set_max_order_count(1)
with self.assertRaises(RegisterTradingControlPostInit):
algo.set_long_only()
algo = TradingAlgorithm(initialize=initialize,
handle_data=handle_data)
algo.run(self.source)
self.source.rewind()
