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# Copyright 2015 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, TradingEnvironment |
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from . 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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@classmethod |
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def setUpClass(cls): |
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cls.env = TradingEnvironment() |
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@classmethod |
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def tearDownClass(cls): |
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del cls.env |
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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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env=self.env, |
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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, env=self.env |
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) |
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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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0.0) |
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def test_algorithm_volatility_06(self): |
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algo_vol_answers = answer_key.RISK_CUMULATIVE.volatility |
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for dt, value in algo_vol_answers.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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self.cumulative_metrics_06.algorithm_volatility[dt_loc], |
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value, |
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err_msg="Mismatch at %s" % (dt,)) |
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def test_sharpe_06(self): |
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for dt, value in answer_key.RISK_CUMULATIVE.sharpe.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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self.cumulative_metrics_06.sharpe[dt_loc], |
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value, |
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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.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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value, |
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self.cumulative_metrics_06.downside_risk[dt_loc], |
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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.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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self.cumulative_metrics_06.sortino[dt_loc], |
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value, |
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decimal=4, |
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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.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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value, |
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self.cumulative_metrics_06.information[dt_loc], |
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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.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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self.cumulative_metrics_06.alpha[dt_loc], |
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value, |
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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.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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value, |
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self.cumulative_metrics_06.beta[dt_loc], |
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err_msg="Mismatch at %s" % (dt,)) |
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def test_max_drawdown_06(self): |
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for dt, value in answer_key.RISK_CUMULATIVE.max_drawdown.iteritems(): |
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dt_loc = self.cumulative_metrics_06.cont_index.get_loc(dt) |
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np.testing.assert_almost_equal( |
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self.cumulative_metrics_06.max_drawdowns[dt_loc], |
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value, |
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err_msg="Mismatch at %s" % (dt,)) |
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quantopian /
zipline
