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119 lines
4.1 KiB
Python
119 lines
4.1 KiB
Python
#
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# Copyright 2013 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 numpy as np
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import pytz
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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 SimulationParameters
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import answer_key
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ANSWER_KEY = answer_key.ANSWER_KEY
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class TestRisk(unittest.TestCase):
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def setUp(self):
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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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end_date = datetime.datetime(
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year=2006, month=12, day=29, tzinfo=pytz.utc)
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self.sim_params = SimulationParameters(
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period_start=start_date,
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period_end=end_date
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)
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self.algo_returns_06 = factory.create_returns_from_list(
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answer_key.ALGORITHM_RETURNS.values,
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self.sim_params
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)
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self.cumulative_metrics_06 = risk.RiskMetricsCumulative(
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self.sim_params)
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for dt, returns in answer_key.RETURNS_DATA.iterrows():
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self.cumulative_metrics_06.update(dt,
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returns['Algorithm Returns'],
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returns['Benchmark Returns'])
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def test_algorithm_volatility_06(self):
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np.testing.assert_almost_equal(
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ANSWER_KEY.ALGORITHM_CUMULATIVE_VOLATILITY,
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self.cumulative_metrics_06.metrics.algorithm_volatility.values)
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def test_sharpe_06(self):
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for dt, value in answer_key.RISK_CUMULATIVE.sharpe.iterkv():
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np.testing.assert_almost_equal(
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value,
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self.cumulative_metrics_06.metrics.sharpe[dt],
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decimal=2,
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err_msg="Mismatch at %s" % (dt,))
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def test_downside_risk_06(self):
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for dt, value in answer_key.RISK_CUMULATIVE.downside_risk.iterkv():
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np.testing.assert_almost_equal(
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self.cumulative_metrics_06.metrics.downside_risk[dt],
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value,
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decimal=2,
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err_msg="Mismatch at %s" % (dt,))
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def test_sortino_06(self):
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for dt, value in answer_key.RISK_CUMULATIVE.sortino.iterkv():
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np.testing.assert_almost_equal(
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self.cumulative_metrics_06.metrics.sortino[dt],
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value,
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decimal=2,
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err_msg="Mismatch at %s" % (dt,))
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def test_information_06(self):
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for dt, value in answer_key.RISK_CUMULATIVE.information.iterkv():
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np.testing.assert_almost_equal(
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self.cumulative_metrics_06.metrics.information[dt],
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value,
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decimal=2,
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err_msg="Mismatch at %s" % (dt,))
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def test_alpha_06(self):
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for dt, value in answer_key.RISK_CUMULATIVE.alpha.iterkv():
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np.testing.assert_almost_equal(
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self.cumulative_metrics_06.metrics.alpha[dt],
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value,
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decimal=2,
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err_msg="Mismatch at %s" % (dt,))
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def test_beta_06(self):
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for dt, value in answer_key.RISK_CUMULATIVE.beta.iterkv():
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np.testing.assert_almost_equal(
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self.cumulative_metrics_06.metrics.beta[dt],
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value,
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decimal=2,
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err_msg="Mismatch at %s" % (dt,))
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def test_max_drawdown_calculated(self):
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# We don't track max_drawdown by day, so it doesn't make sense to
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# generate a full answer key for it. For now, ensure it's just
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# "not zero"
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self.assertNotEqual(self.cumulative_metrics_06.max_drawdown, 0.0)
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