mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-30 01:04:13 +08:00
Richard Frank
095f2dd65b
Issues appeared when we were close to the end of our historical data. Yielding DONE event with both perf and risk messages now
144 lines
5.1 KiB
Python
144 lines
5.1 KiB
Python
#
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# Copyright 2012 Quantopian, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import datetime
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import pytz
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import numpy as np
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import zipline.finance.risk as risk
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from zipline.utils import factory
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from zipline.finance.trading import TradingEnvironment
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from test_risk import RETURNS
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class RiskCompareIterativeToBatch(unittest.TestCase):
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"""
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Assert that RiskMetricsIterative and RiskMetricsBatch
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behave in the same way.
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"""
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def setUp(self):
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self.start_date = datetime.datetime(
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year=2006,
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month=1,
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day=1,
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hour=0,
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minute=0,
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tzinfo=pytz.utc)
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self.end_date = datetime.datetime(
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year=2006, month=12, day=31, tzinfo=pytz.utc)
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self.benchmark_returns, self.treasury_curves = \
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factory.load_market_data()
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self.trading_env = TradingEnvironment(
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self.benchmark_returns,
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self.treasury_curves,
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period_start=self.start_date,
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period_end=self.end_date,
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capital_base=1000.0
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)
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self.oneday = datetime.timedelta(days=1)
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def test_risk_metrics_returns(self):
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risk_metrics_refactor = risk.RiskMetricsIterative(
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self.start_date, self.trading_env)
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todays_date = self.start_date
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cur_returns = []
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for i, ret in enumerate(RETURNS):
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todays_return_obj = risk.DailyReturn(
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todays_date,
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ret
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)
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cur_returns.append(todays_return_obj)
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# Move forward day counter to next trading day
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todays_date += self.oneday
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while not self.trading_env.is_trading_day(todays_date):
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todays_date += self.oneday
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try:
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risk_metrics_original = risk.RiskMetricsBatch(
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start_date=self.start_date,
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end_date=todays_date,
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returns=cur_returns,
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trading_environment=self.trading_env
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)
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except Exception as e:
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#assert that when original raises exception, same
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#exception is raised by risk_metrics_refactor
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np.testing.assert_raises(
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type(e), risk_metrics_refactor.update, todays_date, ret)
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continue
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risk_metrics_refactor.update(todays_date, ret)
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self.assertEqual(
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risk_metrics_original.start_date,
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risk_metrics_refactor.start_date)
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self.assertEqual(
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risk_metrics_original.end_date,
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risk_metrics_refactor.end_date)
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self.assertEqual(
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risk_metrics_original.treasury_duration,
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risk_metrics_refactor.treasury_duration)
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self.assertEqual(
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risk_metrics_original.treasury_curve,
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risk_metrics_refactor.treasury_curve)
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self.assertEqual(
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risk_metrics_original.treasury_period_return,
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risk_metrics_refactor.treasury_period_return)
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self.assertEqual(
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risk_metrics_original.benchmark_returns,
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risk_metrics_refactor.benchmark_returns)
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self.assertEqual(
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risk_metrics_original.algorithm_returns,
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risk_metrics_refactor.algorithm_returns)
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risk_original_dict = risk_metrics_original.to_dict()
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risk_refactor_dict = risk_metrics_refactor.to_dict()
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self.assertEqual(set(risk_original_dict.keys()),
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set(risk_refactor_dict.keys()))
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err_msg_format = """\
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"In update step {iter}: {measure} should be {truth} but is {returned}!"""
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for measure in risk_original_dict.iterkeys():
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if measure == 'max_drawdown':
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np.testing.assert_almost_equal(
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risk_refactor_dict[measure],
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risk_original_dict[measure],
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err_msg=err_msg_format.format(
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iter=i,
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measure=measure,
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truth=risk_original_dict[measure],
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returned=risk_refactor_dict[measure]))
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else:
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np.testing.assert_equal(
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risk_original_dict[measure],
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risk_refactor_dict[measure],
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err_msg_format.format(
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iter=i,
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measure=measure,
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truth=risk_original_dict[measure],
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returned=risk_refactor_dict[measure])
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)
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