mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-29 23:23:34 +08:00
Eddie Hebert
39038131db
The treasury_duration member in RiskMetrics is never used except for in unit tests. Remove the saving of treasury_duration in preparation for the move of the choose_treasury method out of the RiskMetrics classes. Down the line, if we do restore the sanving of treasury_duration, choose_treasury can return a tuple that includes treasury_duration instead of just returning the rate.
144 lines
5.4 KiB
Python
144 lines
5.4 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 numbers
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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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import zipline.finance.trading as trading
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from zipline.protocol import DailyReturn
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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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def test_risk_metrics_returns(self):
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trading.environment = trading.TradingEnvironment()
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# Advance start date to first date in the trading calendar
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if trading.environment.is_trading_day(self.start_date):
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start_date = self.start_date
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else:
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start_date = trading.environment.next_trading_day(self.start_date)
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risk_metrics_refactor = risk.RiskMetricsIterative(start_date)
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todays_date = 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 = 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 = trading.environment.next_trading_day(todays_date)
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try:
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risk_metrics_original = risk.RiskMetricsBatch(
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start_date=start_date,
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end_date=todays_date,
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returns=cur_returns
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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_period_return,
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risk_metrics_refactor.treasury_period_return)
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np.testing.assert_allclose(
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risk_metrics_original.benchmark_returns,
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risk_metrics_refactor.benchmark_returns,
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rtol=0.001
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)
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np.testing.assert_allclose(
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risk_metrics_original.algorithm_returns,
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risk_metrics_refactor.algorithm_returns,
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rtol=0.001
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)
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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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if isinstance(risk_original_dict[measure], numbers.Real):
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np.testing.assert_allclose(
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risk_original_dict[measure],
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risk_refactor_dict[measure],
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rtol=0.001,
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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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)
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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=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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