def setUp(self):
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
for n in range(100):
random_index = random.randint(
0,
len(self.treasury_curves)
)
self.dt = self.treasury_curves.keys()[random_index]
self.end_dt = self.dt + datetime.timedelta(days=365)
now = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
if self.end_dt <= now:
break
assert self.end_dt <= now, """
failed to find a date suitable daterange after 100 attempts. please double
check treasury and benchmark data in findb, and re-run the test."""
self.trading_environment = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=self.dt,
period_end=self.end_dt
)
self.onesec = datetime.timedelta(seconds=1)
self.oneday = datetime.timedelta(days=1)
self.tradingday = datetime.timedelta(hours=6, minutes=30)
self.dt = self.trading_environment.trading_days[random_index]
def setUp(self):
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
for n in range(100):
random_index = random.randint(0, len(self.treasury_curves))
self.dt = self.treasury_curves.keys()[random_index]
self.end_dt = self.dt + datetime.timedelta(days=365)
now = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
if self.end_dt <= now:
break
assert self.end_dt <= now, """
failed to find a date suitable daterange after 100 attempts. please double
check treasury and benchmark data in findb, and re-run the test."""
self.trading_environment = TradingEnvironment(self.benchmark_returns,
self.treasury_curves,
period_start=self.dt,
period_end=self.end_dt)
self.onesec = datetime.timedelta(seconds=1)
self.oneday = datetime.timedelta(days=1)
self.tradingday = datetime.timedelta(hours=6, minutes=30)
self.dt = self.trading_environment.trading_days[random_index]
def setUp(self):
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
self.trading_env = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=start_date,
period_end=end_date
)
self.onesec = datetime.timedelta(seconds=1)
self.oneday = datetime.timedelta(days=1)
self.tradingday = datetime.timedelta(hours=6, minutes=30)
self.dt = datetime.datetime.utcnow()
self.algo_returns_06 = factory.create_returns_from_list(
RETURNS,
self.trading_env
)
self.metrics_06 = risk.RiskReport(
self.algo_returns_06,
self.trading_env
)
start_08 = datetime.datetime(
year=2008,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_08 = datetime.datetime(
year=2008,
month=12,
day=31,
tzinfo=pytz.utc
)
self.trading_env08 = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=start_08,
period_end=end_08
)
def setUp(self):
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
self.trading_env = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=start_date,
period_end=end_date
)
self.onesec = datetime.timedelta(seconds=1)
self.oneday = datetime.timedelta(days=1)
self.tradingday = datetime.timedelta(hours=6, minutes=30)
self.dt = datetime.datetime.utcnow()
self.algo_returns_06 = factory.create_returns_from_list(
RETURNS,
self.trading_env
)
self.metrics_06 = risk.RiskReport(
self.algo_returns_06,
self.trading_env
)
start_08 = datetime.datetime(
year=2008,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_08 = datetime.datetime(
year=2008,
month=12,
day=31,
tzinfo=pytz.utc
)
self.trading_env08 = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=start_08,
period_end=end_08
)
def test_trading_environment(self):
benchmark_returns, treasury_curves = \
factory.load_market_data()
env = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=datetime(2008, 1, 1, tzinfo=pytz.utc),
period_end=datetime(2008, 12, 31, tzinfo=pytz.utc),
capital_base=100000,
)
#holidays taken from: http://www.nyse.com/press/1191407641943.html
new_years = datetime(2008, 1, 1, tzinfo=pytz.utc)
mlk_day = datetime(2008, 1, 21, tzinfo=pytz.utc)
presidents = datetime(2008, 2, 18, tzinfo=pytz.utc)
good_friday = datetime(2008, 3, 21, tzinfo=pytz.utc)
memorial_day = datetime(2008, 5, 26, tzinfo=pytz.utc)
july_4th = datetime(2008, 7, 4, tzinfo=pytz.utc)
labor_day = datetime(2008, 9, 1, tzinfo=pytz.utc)
tgiving = datetime(2008, 11, 27, tzinfo=pytz.utc)
christmas = datetime(2008, 5, 25, tzinfo=pytz.utc)
a_saturday = datetime(2008, 8, 2, tzinfo=pytz.utc)
a_sunday = datetime(2008, 10, 12, tzinfo=pytz.utc)
holidays = [
new_years,
mlk_day,
presidents,
good_friday,
memorial_day,
july_4th,
labor_day,
tgiving,
christmas,
a_saturday,
a_sunday
]
for holiday in holidays:
self.assertTrue(not env.is_trading_day(holiday))
first_trading_day = datetime(2008, 1, 2, tzinfo=pytz.utc)
last_trading_day = datetime(2008, 12, 31, tzinfo=pytz.utc)
workdays = [first_trading_day, last_trading_day]
for workday in workdays:
self.assertTrue(env.is_trading_day(workday))
self.assertTrue(env.last_close.month == 12)
self.assertTrue(env.last_close.day == 31)
def test_trading_environment(self):
benchmark_returns, treasury_curves = \
factory.load_market_data()
env = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=datetime(2008, 1, 1, tzinfo=pytz.utc),
period_end=datetime(2008, 12, 31, tzinfo=pytz.utc),
capital_base=100000,
)
#holidays taken from: http://www.nyse.com/press/1191407641943.html
new_years = datetime(2008, 1, 1, tzinfo=pytz.utc)
mlk_day = datetime(2008, 1, 21, tzinfo=pytz.utc)
presidents = datetime(2008, 2, 18, tzinfo=pytz.utc)
good_friday = datetime(2008, 3, 21, tzinfo=pytz.utc)
memorial_day = datetime(2008, 5, 26, tzinfo=pytz.utc)
july_4th = datetime(2008, 7, 4, tzinfo=pytz.utc)
labor_day = datetime(2008, 9, 1, tzinfo=pytz.utc)
tgiving = datetime(2008, 11, 27, tzinfo=pytz.utc)
christmas = datetime(2008, 5, 25, tzinfo=pytz.utc)
a_saturday = datetime(2008, 8, 2, tzinfo=pytz.utc)
a_sunday = datetime(2008, 10, 12, tzinfo=pytz.utc)
holidays = [
new_years, mlk_day, presidents, good_friday, memorial_day,
july_4th, labor_day, tgiving, christmas, a_saturday, a_sunday
]
for holiday in holidays:
self.assertTrue(not env.is_trading_day(holiday))
first_trading_day = datetime(2008, 1, 2, tzinfo=pytz.utc)
last_trading_day = datetime(2008, 12, 31, tzinfo=pytz.utc)
workdays = [first_trading_day, last_trading_day]
for workday in workdays:
self.assertTrue(env.is_trading_day(workday))
self.assertTrue(env.last_close.month == 12)
self.assertTrue(env.last_close.day == 31)
def setUp(self):
self.start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
self.end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
self.trading_env = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=self.start_date,
period_end=self.end_date,
capital_base=1000.0
)
self.oneday = datetime.timedelta(days=1)
def setUp(self):
self.start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
self.end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
self.trading_env = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=self.start_date,
period_end=self.end_date,
capital_base=1000.0
)
self.oneday = datetime.timedelta(days=1)
def test_trading_environment_days_in_period(self):
benchmark_returns, treasury_curves = \
factory.load_market_data()
# January 2008
# Su Mo Tu We Th Fr Sa
# 1 2 3 4 5
# 6 7 8 9 10 11 12
# 13 14 15 16 17 18 19
# 20 21 22 23 24 25 26
# 27 28 29 30 31
env = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=datetime(2007, 12, 31, tzinfo=pytz.utc),
period_end=datetime(2008, 1, 7, tzinfo=pytz.utc),
capital_base=100000,
)
expected_trading_days = (
datetime(2007, 12, 31, tzinfo=pytz.utc),
# Skip new years
#holidays taken from: http://www.nyse.com/press/1191407641943.html
datetime(2008, 1, 2, tzinfo=pytz.utc),
datetime(2008, 1, 3, tzinfo=pytz.utc),
datetime(2008, 1, 4, tzinfo=pytz.utc),
# Skip Saturday
# Skip Sunday
datetime(2008, 1, 7, tzinfo=pytz.utc)
)
num_expected_trading_days = 5
self.assertEquals(num_expected_trading_days, env.days_in_period)
np.testing.assert_array_equal(expected_trading_days,
env.period_trading_days)
def create_env(self, start_dt=None):
benchmark_returns, treasury_curves = \
factory.load_market_data()
if not start_dt:
for n in range(100):
random_index = random.randint(
0,
len(treasury_curves)
)
start_dt = treasury_curves.keys()[random_index]
end_dt = start_dt + datetime.timedelta(days=365)
now = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
if end_dt <= now:
break
else:
end_dt = start_dt + datetime.timedelta(days=365)
now = datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
assert end_dt <= now, """
failed to find a date suitable daterange after 100 attempts. please double
check treasury and benchmark data in findb, and re-run the test."""
assert start_dt < end_dt, "start_dt must be less than end_dt"
trading_environment = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=start_dt,
period_end=end_dt
)
return trading_environment, start_dt, end_dt
def test_tracker(self, parameter_comment, days_to_delete):
"""
@days_to_delete - configures which days in the data set we should
remove, used for ensuring that we still return performance messages
even when there is no data.
"""
# This date range covers Columbus day,
# however Columbus day is not a market holiday
#
# October 2008
# Su Mo Tu We Th Fr Sa
# 1 2 3 4
# 5 6 7 8 9 10 11
# 12 13 14 15 16 17 18
# 19 20 21 22 23 24 25
# 26 27 28 29 30 31
start_dt = datetime.datetime(year=2008,
month=10,
day=9,
tzinfo=pytz.utc)
end_dt = datetime.datetime(year=2008,
month=10,
day=16,
tzinfo=pytz.utc)
trade_count = 6
sid = 133
price = 10.1
price_list = [price] * trade_count
volume = [100] * trade_count
trade_time_increment = datetime.timedelta(days=1)
benchmark_returns, treasury_curves = \
factory.load_market_data()
trading_environment = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=start_dt,
period_end=end_dt
)
trade_history = factory.create_trade_history(
sid,
price_list,
volume,
trade_time_increment,
trading_environment,
source_id="factory1"
)
sid2 = 134
price2 = 12.12
price2_list = [price2] * trade_count
trade_history2 = factory.create_trade_history(
sid2,
price2_list,
volume,
trade_time_increment,
trading_environment,
source_id="factory2"
)
# 'middle' start of 3 depends on number of days == 7
middle = 3
# First delete from middle
if days_to_delete.middle:
del trade_history[middle:(middle + days_to_delete.middle)]
del trade_history2[middle:(middle + days_to_delete.middle)]
# Delete start
if days_to_delete.start:
del trade_history[:days_to_delete.start]
del trade_history2[:days_to_delete.start]
# Delete from end
if days_to_delete.end:
del trade_history[-days_to_delete.end:]
del trade_history2[-days_to_delete.end:]
trading_environment.first_open = \
trading_environment.calculate_first_open()
trading_environment.last_close = \
trading_environment.calculate_last_close()
trading_environment.capital_base = 1000.0
trading_environment.frame_index = [
'sid',
'volume',
'dt',
'price',
'changed']
perf_tracker = perf.PerformanceTracker(
trading_environment
)
events = date_sorted_sources(trade_history, trade_history2)
events = [self.event_with_txn(event, trade_history[0].dt)
for event in events]
# Extract events with transactions to use for verification.
events_with_txns = [event for event in events if event.TRANSACTION]
perf_messages = \
[msg for date, snapshot in
perf_tracker.transform(
itertools.groupby(events, attrgetter('dt')))
for event in snapshot
for msg in event.perf_messages]
end_perf_messages, risk_message = perf_tracker.handle_simulation_end()
perf_messages.extend(end_perf_messages)
#we skip two trades, to test case of None transaction
self.assertEqual(perf_tracker.txn_count, len(events_with_txns))
cumulative_pos = perf_tracker.cumulative_performance.positions[sid]
expected_size = len(events_with_txns) / 2 * -25
self.assertEqual(cumulative_pos.amount, expected_size)
self.assertEqual(perf_tracker.last_close,
perf_tracker.cumulative_risk_metrics.end_date)
self.assertEqual(len(perf_messages),
trading_environment.days_in_period)