mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-20 12:20:29 +08:00
Eddie Hebert
2314e8a281
Add reference to updated answer key with benchmark variance cells, and use the new cells as the reference for the benchmark variance test. The values changed from the original hardcoded values, due to the change to close over close benchmarks.
763 lines
29 KiB
Python
763 lines
29 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 calendar
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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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from . answer_key import AnswerKey
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ANSWER_KEY = AnswerKey()
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RETURNS = ANSWER_KEY.get_values(AnswerKey.RETURNS)
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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=31, 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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RETURNS,
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self.sim_params
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)
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self.metrics_06 = risk.RiskReport(
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self.algo_returns_06,
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self.sim_params
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)
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start_08 = datetime.datetime(
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year=2008,
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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_08 = datetime.datetime(
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year=2008,
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month=12,
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day=31,
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tzinfo=pytz.utc
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)
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self.sim_params08 = SimulationParameters(
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period_start=start_08,
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period_end=end_08
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)
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def tearDown(self):
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return
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def test_factory(self):
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returns = [0.1] * 100
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r_objects = factory.create_returns_from_list(returns, self.sim_params)
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self.assertTrue(r_objects[-1].date <=
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datetime.datetime(
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year=2006, month=12, day=31, tzinfo=pytz.utc))
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def test_drawdown(self):
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returns = factory.create_returns_from_list(
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[1.0, -0.5, 0.8, .17, 1.0, -0.1, -0.45], self.sim_params)
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#200, 100, 180, 210.6, 421.2, 379.8, 208.494
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metrics = risk.RiskMetricsBatch(returns[0].date,
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returns[-1].date,
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returns)
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self.assertEqual(metrics.max_drawdown, 0.505)
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def test_benchmark_returns_06(self):
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returns = factory.create_returns_from_range(self.sim_params)
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metrics = risk.RiskReport(returns, self.sim_params)
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answer_key_month_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_RETURNS['Monthly'])
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self.assertEqual([round(x.benchmark_period_returns, 4)
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for x in metrics.month_periods],
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answer_key_month_periods)
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answer_key_three_month_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_RETURNS['3-Month'])
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self.assertEqual([round(x.benchmark_period_returns, 4)
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for x in metrics.three_month_periods],
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answer_key_three_month_periods)
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answer_key_six_month_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_RETURNS['6-month'])
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self.assertEqual([round(x.benchmark_period_returns, 4)
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for x in metrics.six_month_periods],
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answer_key_six_month_periods)
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answer_key_year_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_RETURNS['year'])
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self.assertEqual([round(x.benchmark_period_returns, 4)
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for x in metrics.year_periods],
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answer_key_year_periods)
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def test_trading_days_06(self):
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returns = factory.create_returns_from_range(self.sim_params)
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metrics = risk.RiskReport(returns, self.sim_params)
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self.assertEqual([x.num_trading_days for x in metrics.year_periods],
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[251])
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self.assertEqual([x.num_trading_days for x in metrics.month_periods],
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[20, 19, 23, 19, 22, 22, 20, 23, 20, 22, 21, 20])
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def test_benchmark_volatility_06(self):
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returns = factory.create_returns_from_range(self.sim_params)
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metrics = risk.RiskReport(returns, self.sim_params)
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answer_key_month_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_VOLATILITY['Monthly'],
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decimal=3)
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self.assertEqual([np.round(x.benchmark_volatility, 3)
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for x in metrics.month_periods],
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answer_key_month_periods)
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answer_key_three_month_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_VOLATILITY['3-Month'],
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decimal=3)
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self.assertEqual([np.round(x.benchmark_volatility, 3)
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for x in metrics.three_month_periods],
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answer_key_three_month_periods)
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answer_key_six_month_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_VOLATILITY['6-month'],
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decimal=3)
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self.assertEqual([np.round(x.benchmark_volatility, 3)
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for x in metrics.six_month_periods],
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answer_key_six_month_periods)
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answer_key_year_periods = ANSWER_KEY.get_values(
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AnswerKey.BENCHMARK_PERIOD_VOLATILITY['year'],
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decimal=3)
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self.assertEqual([np.round(x.benchmark_volatility, 3)
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for x in metrics.year_periods],
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answer_key_year_periods)
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def test_algorithm_returns_06(self):
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answer_key_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_RETURNS['Monthly'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_period_returns, 3)
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for x in self.metrics_06.month_periods],
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answer_key_month_periods)
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answer_key_three_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_RETURNS['3-Month'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_period_returns, 3)
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for x in self.metrics_06.three_month_periods],
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answer_key_three_month_periods)
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answer_key_six_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_RETURNS['6-month'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_period_returns, 3)
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for x in self.metrics_06.six_month_periods],
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answer_key_six_month_periods)
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answer_key_year_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_RETURNS['year'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_period_returns, 3)
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for x in self.metrics_06.year_periods],
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answer_key_year_periods)
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def test_algorithm_volatility_06(self):
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answer_key_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_VOLATILITY['Monthly'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_volatility, 3)
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for x in self.metrics_06.month_periods],
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answer_key_month_periods)
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answer_key_three_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_VOLATILITY['3-Month'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_volatility, 3)
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for x in self.metrics_06.three_month_periods],
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answer_key_three_month_periods)
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answer_key_six_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_VOLATILITY['6-month'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_volatility, 3)
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for x in self.metrics_06.six_month_periods],
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answer_key_six_month_periods)
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answer_key_year_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_VOLATILITY['year'],
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decimal=3)
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self.assertEqual([np.round(x.algorithm_volatility, 3)
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for x in self.metrics_06.year_periods],
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answer_key_year_periods)
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def test_algorithm_sharpe_06_monthly(self):
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answer_key_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_SHARPE['Monthly'],
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decimal=3)
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self.assertEqual([np.round(x.sharpe, 3)
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for x in self.metrics_06.month_periods],
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answer_key_month_periods)
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def test_algorithm_sharpe_06_three_month(self):
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answer_key_three_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_SHARPE['3-Month'],
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decimal=3)
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self.assertEqual([np.round(x.sharpe, 3)
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for x in self.metrics_06.three_month_periods],
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answer_key_three_month_periods)
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def test_algorithm_sharpe_06_six_month(self):
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answer_key_six_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_SHARPE['6-month'],
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decimal=3)
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results_six_month_periods = [
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np.round(x.sharpe, 3)
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for x in self.metrics_06.six_month_periods]
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self.assertEqual(results_six_month_periods,
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answer_key_six_month_periods)
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def test_algorithm_sharpe_06_year(self):
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answer_key_year_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_SHARPE['year'],
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decimal=3)
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self.assertEqual([np.round(x.sharpe, 3)
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for x in self.metrics_06.year_periods],
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answer_key_year_periods)
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def test_algorithm_sortino_06(self):
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self.assertEqual([round(x.sortino, 3)
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for x in self.metrics_06.month_periods],
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[4.491,
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-2.842,
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-2.052,
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3.898,
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7.023,
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-8.532,
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3.079,
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-0.354,
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-1.125,
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3.009,
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3.277,
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-3.122])
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self.assertEqual([round(x.sortino, 3)
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for x in self.metrics_06.three_month_periods],
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[-0.769,
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-1.043,
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6.677,
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-2.77,
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-3.209,
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-6.769,
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1.253,
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1.085,
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3.659,
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1.674])
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self.assertEqual([round(x.sortino, 3)
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for x in self.metrics_06.six_month_periods],
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[-2.728,
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-3.258,
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-1.84,
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-1.366,
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-1.845,
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-3.415,
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2.238])
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self.assertEqual([round(x.sortino, 3)
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for x in self.metrics_06.year_periods],
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[-0.524])
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def test_algorithm_information_06(self):
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self.assertEqual([round(x.information, 3)
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for x in self.metrics_06.month_periods],
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[0.131,
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-0.11,
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-0.067,
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0.136,
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0.301,
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-0.387,
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0.107,
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-0.032,
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-0.058,
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0.069,
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0.095,
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-0.123])
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self.assertEqual([round(x.information, 3)
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for x in self.metrics_06.three_month_periods],
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[-0.013,
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-0.009,
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0.111,
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-0.014,
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-0.017,
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-0.108,
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0.011,
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-0.004,
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0.032,
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0.011])
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self.assertEqual([round(x.information, 3)
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for x in self.metrics_06.six_month_periods],
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[-0.013,
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-0.014,
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-0.003,
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-0.002,
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-0.011,
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-0.041,
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0.011])
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self.assertEqual([round(x.information, 3)
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for x in self.metrics_06.year_periods],
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[-0.001])
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def dtest_algorithm_beta_06(self):
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self.assertEqual([round(x.beta, 3)
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for x in self.metrics_06.month_periods],
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[0.553,
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0.583,
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-2.168,
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-0.548,
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1.463,
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-0.322,
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-1.38,
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1.473,
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-1.315,
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-0.7,
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0.352,
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-2.002])
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self.assertEqual([round(x.beta, 3)
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for x in self.metrics_06.three_month_periods],
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[-0.075,
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-0.637,
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0.124,
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0.186,
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-0.204,
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-0.497,
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-0.867,
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-0.173,
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-0.499,
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-0.563])
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self.assertEqual([round(x.beta, 3)
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for x in self.metrics_06.six_month_periods],
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[-0.075,
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-0.637,
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0.124,
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0.186,
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-0.204,
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-0.497,
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-0.867,
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-0.173,
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-0.499,
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-0.563])
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self.assertEqual([round(x.beta, 3)
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for x in self.metrics_06.year_periods], [-0.219])
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def dtest_algorithm_alpha_06(self):
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self.assertEqual([round(x.alpha, 3)
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for x in self.metrics_06.month_periods],
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[0.085,
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-0.063,
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-0.03,
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0.093,
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0.182,
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-0.255,
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0.073,
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-0.032,
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0,
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0.086,
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0.054,
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-0.058])
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self.assertEqual([round(x.alpha, 3)
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for x in self.metrics_06.three_month_periods],
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[-0.051,
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-0.021,
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0.179,
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-0.077,
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-0.106,
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-0.202,
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0.069,
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0.042,
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0.13,
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0.073])
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self.assertEqual([round(x.alpha, 3)
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for x in self.metrics_06.six_month_periods],
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[-0.105,
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-0.135,
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-0.072,
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-0.051,
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-0.066,
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-0.094,
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0.152])
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self.assertEqual([round(x.alpha, 3)
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for x in self.metrics_06.year_periods],
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[-0.011])
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# FIXME: Covariance is not matching excel precisely enough to run the test.
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# Month 4 seems to be the problem. Variance is disabled
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# just to avoid distraction - it is much closer than covariance
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# and can probably pass with 6 significant digits instead of 7.
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#re-enable variance, alpha, and beta tests once this is resolved
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def dtest_algorithm_covariance_06(self):
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metric = self.metrics_06.month_periods[3]
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print repr(metric)
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print "----"
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self.assertEqual([round(x.algorithm_covariance, 7)
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for x in self.metrics_06.month_periods],
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[0.0000289,
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0.0000222,
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-0.0000554,
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-0.0000192,
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0.0000954,
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-0.0000333,
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-0.0001111,
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0.0000322,
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-0.0000349,
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-0.0000143,
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0.0000108,
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-0.0000386])
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self.assertEqual([round(x.algorithm_covariance, 7)
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for x in self.metrics_06.three_month_periods],
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[-0.0000026,
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-0.0000189,
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0.0000049,
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0.0000121,
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-0.0000158,
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-0.000031,
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-0.0000336,
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-0.0000036,
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-0.0000119,
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-0.0000122])
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self.assertEqual([round(x.algorithm_covariance, 7)
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for x in self.metrics_06.six_month_periods],
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[0.000005,
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-0.0000172,
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-0.0000142,
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-0.0000102,
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-0.0000089,
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-0.0000207,
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-0.0000229])
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self.assertEqual([round(x.algorithm_covariance, 7)
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for x in self.metrics_06.year_periods],
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[-8.75273E-06])
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def test_benchmark_variance_06(self):
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answer_key_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_BENCHMARK_VARIANCE['Monthly'],
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decimal=7)
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self.assertEqual([np.round(x.benchmark_variance, 7)
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for x in self.metrics_06.month_periods],
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answer_key_month_periods)
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answer_key_three_month_periods = ANSWER_KEY.get_values(
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AnswerKey.ALGORITHM_PERIOD_BENCHMARK_VARIANCE['3-Month'],
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decimal=7)
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self.assertEqual([np.round(x.benchmark_variance, 7)
|
|
for x in self.metrics_06.three_month_periods],
|
|
answer_key_three_month_periods)
|
|
|
|
answer_key_six_month_periods = ANSWER_KEY.get_values(
|
|
AnswerKey.ALGORITHM_PERIOD_BENCHMARK_VARIANCE['6-month'],
|
|
decimal=7)
|
|
results_six_month_periods = [
|
|
np.round(x.benchmark_variance, 7)
|
|
for x in self.metrics_06.six_month_periods]
|
|
self.assertEqual(results_six_month_periods,
|
|
answer_key_six_month_periods)
|
|
|
|
answer_key_year_periods = ANSWER_KEY.get_values(
|
|
AnswerKey.ALGORITHM_PERIOD_BENCHMARK_VARIANCE['year'],
|
|
decimal=7)
|
|
self.assertEqual([np.round(x.benchmark_variance, 7)
|
|
for x in self.metrics_06.year_periods],
|
|
answer_key_year_periods)
|
|
|
|
def test_benchmark_returns_08(self):
|
|
returns = factory.create_returns_from_range(self.sim_params08)
|
|
metrics = risk.RiskReport(returns, self.sim_params08)
|
|
|
|
self.assertEqual([round(x.benchmark_period_returns, 3)
|
|
for x in metrics.month_periods],
|
|
[-0.061,
|
|
-0.035,
|
|
-0.006,
|
|
0.048,
|
|
0.011,
|
|
-0.086,
|
|
-0.01,
|
|
0.012,
|
|
-0.091,
|
|
-0.169,
|
|
-0.075,
|
|
0.008])
|
|
|
|
self.assertEqual([round(x.benchmark_period_returns, 3)
|
|
for x in metrics.three_month_periods],
|
|
[-0.099,
|
|
0.005,
|
|
0.052,
|
|
-0.032,
|
|
-0.085,
|
|
-0.084,
|
|
-0.089,
|
|
-0.236,
|
|
-0.301,
|
|
-0.226])
|
|
|
|
self.assertEqual([round(x.benchmark_period_returns, 3)
|
|
for x in metrics.six_month_periods],
|
|
[-0.128,
|
|
-0.081,
|
|
-0.036,
|
|
-0.118,
|
|
-0.301,
|
|
-0.36,
|
|
-0.294])
|
|
|
|
self.assertEqual([round(x.benchmark_period_returns, 3)
|
|
for x in metrics.year_periods],
|
|
[-0.385])
|
|
|
|
def test_trading_days_08(self):
|
|
returns = factory.create_returns_from_range(self.sim_params08)
|
|
metrics = risk.RiskReport(returns, self.sim_params08)
|
|
self.assertEqual([x.num_trading_days for x in metrics.year_periods],
|
|
[253])
|
|
|
|
self.assertEqual([x.num_trading_days for x in metrics.month_periods],
|
|
[21, 20, 20, 22, 21, 21, 22, 21, 21, 23, 19, 22])
|
|
|
|
def test_benchmark_volatility_08(self):
|
|
returns = factory.create_returns_from_range(self.sim_params08)
|
|
metrics = risk.RiskReport(returns, self.sim_params08)
|
|
|
|
self.assertEqual([round(x.benchmark_volatility, 3)
|
|
for x in metrics.month_periods],
|
|
[0.07,
|
|
0.058,
|
|
0.082,
|
|
0.054,
|
|
0.041,
|
|
0.057,
|
|
0.068,
|
|
0.06,
|
|
0.157,
|
|
0.244,
|
|
0.195,
|
|
0.145])
|
|
|
|
self.assertEqual([round(x.benchmark_volatility, 3)
|
|
for x in metrics.three_month_periods],
|
|
[0.12,
|
|
0.113,
|
|
0.105,
|
|
0.09,
|
|
0.098,
|
|
0.107,
|
|
0.179,
|
|
0.293,
|
|
0.344,
|
|
0.34])
|
|
|
|
self.assertEqual([round(x.benchmark_volatility, 3)
|
|
for x in metrics.six_month_periods],
|
|
[0.15,
|
|
0.149,
|
|
0.15,
|
|
0.2,
|
|
0.308,
|
|
0.36,
|
|
0.383])
|
|
# TODO: ugly, but I can't get the rounded float to match.
|
|
# maybe we need a different test that checks the
|
|
# difference between the numbers
|
|
self.assertEqual([round(x.benchmark_volatility, 3)
|
|
for x in metrics.year_periods],
|
|
[0.411])
|
|
|
|
def test_treasury_returns_06(self):
|
|
returns = factory.create_returns_from_range(self.sim_params)
|
|
metrics = risk.RiskReport(returns, self.sim_params)
|
|
self.assertEqual([round(x.treasury_period_return, 4)
|
|
for x in metrics.month_periods],
|
|
[0.0037,
|
|
0.0034,
|
|
0.0039,
|
|
0.0038,
|
|
0.0040,
|
|
0.0037,
|
|
0.0043,
|
|
0.0043,
|
|
0.0038,
|
|
0.0044,
|
|
0.0043,
|
|
0.004])
|
|
|
|
self.assertEqual([round(x.treasury_period_return, 4)
|
|
for x in metrics.three_month_periods],
|
|
[0.0114,
|
|
0.0116,
|
|
0.0122,
|
|
0.0125,
|
|
0.0129,
|
|
0.0127,
|
|
0.0123,
|
|
0.0128,
|
|
0.0125,
|
|
0.0127])
|
|
self.assertEqual([round(x.treasury_period_return, 4)
|
|
for x in metrics.six_month_periods],
|
|
[0.0260,
|
|
0.0257,
|
|
0.0258,
|
|
0.0252,
|
|
0.0259,
|
|
0.0256,
|
|
0.0257])
|
|
|
|
self.assertEqual([round(x.treasury_period_return, 4)
|
|
for x in metrics.year_periods],
|
|
[0.0500])
|
|
|
|
def test_benchmarkrange(self):
|
|
self.check_year_range(
|
|
datetime.datetime(
|
|
year=2008, month=1, day=1, tzinfo=pytz.utc),
|
|
2)
|
|
|
|
def test_partial_month(self):
|
|
|
|
start = datetime.datetime(
|
|
year=1991,
|
|
month=1,
|
|
day=1,
|
|
hour=0,
|
|
minute=0,
|
|
tzinfo=pytz.utc)
|
|
|
|
#1992 and 1996 were leap years
|
|
total_days = 365 * 5 + 2
|
|
end = start + datetime.timedelta(days=total_days)
|
|
sim_params90s = SimulationParameters(
|
|
period_start=start,
|
|
period_end=end
|
|
)
|
|
|
|
returns = factory.create_returns_from_range(sim_params90s)
|
|
returns = returns[:-10] # truncate the returns series to end mid-month
|
|
metrics = risk.RiskReport(returns, sim_params90s)
|
|
total_months = 60
|
|
self.check_metrics(metrics, total_months, start)
|
|
|
|
def check_year_range(self, start_date, years):
|
|
sim_params = SimulationParameters(
|
|
period_start=start_date,
|
|
period_end=start_date.replace(year=(start_date.year + years))
|
|
)
|
|
returns = factory.create_returns_from_range(sim_params)
|
|
metrics = risk.RiskReport(returns, self.sim_params)
|
|
total_months = years * 12
|
|
self.check_metrics(metrics, total_months, start_date)
|
|
|
|
def check_metrics(self, metrics, total_months, start_date):
|
|
"""
|
|
confirm that the right number of riskmetrics were calculated for each
|
|
window length.
|
|
"""
|
|
self.assert_range_length(
|
|
metrics.month_periods,
|
|
total_months,
|
|
1,
|
|
start_date
|
|
)
|
|
|
|
self.assert_range_length(
|
|
metrics.three_month_periods,
|
|
total_months,
|
|
3,
|
|
start_date
|
|
)
|
|
|
|
self.assert_range_length(
|
|
metrics.six_month_periods,
|
|
total_months,
|
|
6,
|
|
start_date
|
|
)
|
|
|
|
self.assert_range_length(
|
|
metrics.year_periods,
|
|
total_months,
|
|
12,
|
|
start_date
|
|
)
|
|
|
|
def assert_last_day(self, period_end):
|
|
#30 days has september, april, june and november
|
|
if period_end.month in [9, 4, 6, 11]:
|
|
self.assertEqual(period_end.day, 30)
|
|
#all the rest have 31, except for february
|
|
elif(period_end.month != 2):
|
|
self.assertEqual(period_end.day, 31)
|
|
else:
|
|
if calendar.isleap(period_end.year):
|
|
self.assertEqual(period_end.day, 29)
|
|
else:
|
|
self.assertEqual(period_end.day, 28)
|
|
|
|
def assert_month(self, start_month, actual_end_month):
|
|
if start_month == 1:
|
|
expected_end_month = 12
|
|
else:
|
|
expected_end_month = start_month - 1
|
|
|
|
self.assertEqual(expected_end_month, actual_end_month)
|
|
|
|
def assert_range_length(self, col, total_months,
|
|
period_length, start_date):
|
|
if(period_length > total_months):
|
|
self.assertEqual(len(col), 0)
|
|
else:
|
|
self.assertEqual(
|
|
len(col),
|
|
total_months - (period_length - 1),
|
|
"mismatch for total months - \
|
|
expected:{total_months}/actual:{actual}, \
|
|
period:{period_length}, start:{start_date}, \
|
|
calculated end:{end}".format(total_months=total_months,
|
|
period_length=period_length,
|
|
start_date=start_date,
|
|
end=col[-1].end_date,
|
|
actual=len(col))
|
|
)
|
|
self.assert_month(start_date.month, col[-1].end_date.month)
|
|
self.assert_last_day(col[-1].end_date)
|