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https://github.com/wassname/catalyst.git
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TST: Read benchmark returns directly from answer key spreadsheet.
The risk tests originally were based on a spread sheet, with the results of returns etc copy and pasted into the `test_risk` module. Include the spreadsheet and read the values directly using a Python Excel spreadsheet library.
This commit is contained in:
Eddie Hebert
@@ -0,0 +1,88 @@
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#
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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 os
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import numpy as np
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import xlrd
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def col_letter_to_index(col_letter):
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# Only supports single letter,
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# but answer key doesn't need multi-letter, yet.
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return ord(col_letter) - 65
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DIR = os.path.dirname(os.path.realpath(__file__))
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ANSWER_KEY_PATH = os.path.join(DIR, 'risk-answer-key.xls')
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class DataIndex(object):
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"""
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Coordinates for the spreadsheet, using the values as seen in the notebook.
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The python-excel libraries use 0 index, while the spreadsheet in a GUI
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uses a 1 index.
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"""
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def __init__(self, sheet_name, col, row_start, row_end):
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self.sheet_name = sheet_name
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self.col = col
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self.row_start = row_start
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self.row_end = row_end
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@property
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def col_index(self):
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return col_letter_to_index(self.col)
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@property
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def row_start_index(self):
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return self.row_start - 1
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@property
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def row_end_index(self):
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return self.row_end - 1
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class AnswerKey(object):
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RETURNS = DataIndex('Sim', 'D', 4, 255)
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# Below matches the inconsistent capitalization in spreadsheet
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BENCHMARK_PERIOD_RETURNS = {
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'Monthly': DataIndex('s_p', 'P', 8, 19),
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'3-Month': DataIndex('s_p', 'Q', 10, 19),
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'6-month': DataIndex('s_p', 'R', 13, 19),
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'year': DataIndex('s_p', 'S', 19, 19),
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}
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BENCHMARK_PERIOD_VOLATILITY = {
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'Monthly': DataIndex('s_p', 'T', 8, 19),
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'3-Month': DataIndex('s_p', 'U', 10, 19),
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'6-month': DataIndex('s_p', 'V', 13, 19),
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'year': DataIndex('s_p', 'W', 19, 19),
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}
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def __init__(self):
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self.workbook = xlrd.open_workbook(ANSWER_KEY_PATH)
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self.sheets = {}
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self.sheets['Sim'] = self.workbook.sheet_by_name('Sim')
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self.sheets['s_p'] = self.workbook.sheet_by_name('s_p')
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def get_values(self, data_index, decimal=4):
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return [np.round(x, decimal) for x in
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self.sheets[data_index.sheet_name].col_values(
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data_index.col_index,
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data_index.row_start_index,
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data_index.row_end_index + 1)]
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+39
-317
@@ -16,12 +16,19 @@
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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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@@ -93,44 +100,26 @@ class TestRisk(unittest.TestCase):
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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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[0.0255,
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0.0005,
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0.0111,
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0.0122,
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-0.0309,
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0.0001,
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0.0051,
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0.0213,
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0.0246,
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0.0315,
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0.0165,
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0.0126])
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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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[0.0373,
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0.0239,
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-0.0083,
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-0.0191,
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-0.0259,
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0.0266,
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0.0517,
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0.0793,
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0.0743,
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0.0617])
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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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[0.0176,
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-0.0027,
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0.0181,
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0.0316,
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0.0514,
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0.1028,
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0.1166])
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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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[0.1362])
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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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@@ -143,47 +132,33 @@ class TestRisk(unittest.TestCase):
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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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self.assertEqual([round(x.benchmark_volatility, 3)
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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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[0.031,
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0.026,
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0.024,
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0.025,
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0.037,
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0.047,
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0.039,
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0.022,
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0.023,
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0.021,
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0.025,
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0.019])
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answer_key_month_periods)
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self.assertEqual([round(x.benchmark_volatility, 3)
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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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[0.047,
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0.042,
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0.050,
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0.064,
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0.070,
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0.064,
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0.049,
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0.037,
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0.039,
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0.037])
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answer_key_three_month_periods)
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self.assertEqual([round(x.benchmark_volatility, 3)
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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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[0.079,
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0.082,
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0.081,
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0.081,
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0.080,
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0.074,
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0.061])
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answer_key_six_month_periods)
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self.assertEqual([round(x.benchmark_volatility, 3)
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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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[0.100])
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answer_key_year_periods)
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def test_algorithm_returns_06(self):
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self.assertEqual([round(x.algorithm_period_returns, 3)
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@@ -834,256 +809,3 @@ class TestRisk(unittest.TestCase):
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)
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self.assert_month(start_date.month, col[-1].end_date.month)
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self.assert_last_day(col[-1].end_date)
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RETURNS = [
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0.0093,
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-0.0193,
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0.0351,
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0.0396,
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0.0338,
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-0.0211,
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0.0389,
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0.0326,
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-0.0137,
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-0.0411,
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-0.0032,
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0.0149,
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0.0133,
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0.0348,
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0.042,
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-0.0455,
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0.0262,
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-0.0461,
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0.0021,
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-0.0273,
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-0.0429,
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0.0427,
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-0.0104,
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0.0346,
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-0.0311,
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0.0003,
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0.0211,
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0.0248,
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-0.0215,
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0.004,
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0.0267,
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0.0029,
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-0.0369,
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0.0057,
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0.0298,
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-0.0179,
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-0.0361,
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-0.0401,
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-0.0123,
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-0.005,
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0.0203,
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-0.041,
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0.0011,
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0.0118,
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0.0103,
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-0.0184,
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-0.0437,
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0.0411,
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-0.0242,
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-0.0054,
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-0.0039,
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-0.0273,
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-0.0075,
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0.0064,
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-0.0376,
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0.0424,
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0.0399,
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0.019,
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0.0236,
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-0.0284,
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-0.0341,
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0.0266,
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0.05,
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0.0069,
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-0.0442,
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-0.016,
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0.0173,
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0.0348,
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-0.0404,
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-0.0068,
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-0.0376,
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0.0356,
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0.0043,
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-0.0481,
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-0.0134,
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0.0257,
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0.0442,
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0.0234,
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0.0394,
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0.0376,
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-0.0147,
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-0.0098,
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0.0474,
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-0.0102,
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0.0138,
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0.0286,
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0.0347,
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0.0279,
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-0.0067,
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0.0462,
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-0.0432,
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0.0247,
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0.0174,
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-0.0305,
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-0.0317,
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-0.0068,
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0.0264,
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-0.0257,
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-0.0328,
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0.0092,
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0.0288,
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-0.002,
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0.0288,
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0.028,
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-0.0093,
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0.0178,
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-0.0365,
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-0.0086,
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-0.0133,
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-0.0309,
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0.0473,
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-0.0149,
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0.0378,
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-0.0316,
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-0.0292,
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-0.0453,
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-0.0451,
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0.0093,
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0.0397,
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-0.0361,
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-0.0168,
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-0.0494,
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-0.0143,
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-0.0405,
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-0.0349,
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0.0069,
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0.0378,
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-0.0233,
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-0.0492,
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0.018,
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-0.0386,
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0.0339,
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0.0119,
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0.0454,
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0.0118,
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-0.011,
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-0.0254,
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0.0266,
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-0.0366,
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-0.0211,
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0.0399,
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0.0307,
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0.035,
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-0.0402,
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0.0304,
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-0.0031,
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0.0256,
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0.0134,
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-0.0019,
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-0.0235,
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-0.0058,
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-0.0117,
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0.0051,
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-0.0451,
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-0.0466,
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-0.0124,
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0.0283,
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-0.0499,
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0.0318,
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-0.0028,
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0.0203,
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0.005,
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0.0085,
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0.0048,
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0.0277,
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0.0159,
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-0.0149,
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0.035,
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0.0404,
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-0.01,
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0.0377,
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0.0302,
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0.0046,
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-0.0328,
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-0.0469,
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0.0071,
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-0.0382,
|
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-0.0214,
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0.0429,
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0.0145,
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-0.0279,
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-0.0172,
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0.0423,
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0.041,
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-0.0183,
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0.0137,
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-0.0412,
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-0.0348,
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0.0302,
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0.0248,
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0.0051,
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-0.0298,
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-0.0103,
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-0.0333,
|
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-0.0399,
|
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0.0485,
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-0.0166,
|
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0.0384,
|
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0.0259,
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-0.0163,
|
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0.0357,
|
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0.0308,
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-0.0386,
|
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0.0481,
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-0.0446,
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-0.0282,
|
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-0.0037,
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0.0202,
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0.0216,
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0.0113,
|
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0.0194,
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0.0392,
|
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0.0016,
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0.0268,
|
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-0.0155,
|
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-0.027,
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0.02,
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0.0216,
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-0.0009,
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0.022,
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0.0,
|
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0.041,
|
||||
0.0133,
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-0.0382,
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0.0495,
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-0.0221,
|
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-0.0329,
|
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-0.0033,
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-0.0089,
|
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-0.0129,
|
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-0.0252,
|
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0.048,
|
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-0.0307,
|
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-0.0357,
|
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0.0033,
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-0.0412,
|
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-0.0407,
|
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0.0455,
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0.0159,
|
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-0.0051,
|
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-0.0274,
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-0.0213,
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0.0361,
|
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0.0051,
|
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-0.0378,
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0.0084,
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0.0066,
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-0.0103,
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-0.0037,
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0.0478,
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-0.0278]
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