Files
catalyst/zipline/finance/risk/risk.py
T
Ana Ruelas 902865cf71 ENH: Use qrisk to calculate risk metrics in cumulative and period
TST: Remove metric correctness testing from period and cumulative tests

ENH: Removed answer key and related files

ENH: Update qrisk version
2016-08-23 13:49:27 -04:00

186 lines
7.2 KiB
Python

#
# Copyright 2014 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Risk Report
===========
+-----------------+----------------------------------------------------+
| key | value |
+=================+====================================================+
| trading_days | The number of trading days between self.start_date |
| | and self.end_date |
+-----------------+----------------------------------------------------+
| benchmark_volat\| The volatility of the benchmark between |
| ility | self.start_date and self.end_date. |
+-----------------+----------------------------------------------------+
| algo_volatility | The volatility of the algo between self.start_date |
| | and self.end_date. |
+-----------------+----------------------------------------------------+
| treasury_period\| The return of treasuries over the period. Treasury |
| _return | maturity is chosen to match the duration of the |
| | test period. |
+-----------------+----------------------------------------------------+
| sharpe | The sharpe ratio based on the _algorithm_ (rather |
| | than the static portfolio) returns. |
+-----------------+----------------------------------------------------+
| information | The information ratio based on the _algorithm_ |
| | (rather than the static portfolio) returns. |
+-----------------+----------------------------------------------------+
| beta | The _algorithm_ beta to the benchmark. |
+-----------------+----------------------------------------------------+
| alpha | The _algorithm_ alpha to the benchmark. |
+-----------------+----------------------------------------------------+
| excess_return | The excess return of the algorithm over the |
| | treasuries. |
+-----------------+----------------------------------------------------+
| max_drawdown | The largest relative peak to relative trough move |
| | for the portfolio returns between self.start_date |
| | and self.end_date. |
+-----------------+----------------------------------------------------+
| max_leverage | The largest gross leverage between self.start_date |
| | and self.end_date |
+-----------------+----------------------------------------------------+
"""
import logbook
import numpy as np
log = logbook.Logger('Risk')
TREASURY_DURATIONS = [
'1month', '3month', '6month',
'1year', '2year', '3year', '5year',
'7year', '10year', '30year'
]
# check if a field in rval is nan, and replace it with
# None.
def check_entry(key, value):
if key != 'period_label':
return np.isnan(value) or np.isinf(value)
else:
return False
def get_treasury_rate(treasury_curves, treasury_duration, day):
rate = None
curve = treasury_curves.ix[day]
# 1month note data begins in 8/2001,
# so we can use 3month instead.
idx = TREASURY_DURATIONS.index(treasury_duration)
for duration in TREASURY_DURATIONS[idx:]:
rate = curve[duration]
if rate is not None:
break
return rate
def select_treasury_duration(start_date, end_date):
td = end_date - start_date
if td.days <= 31:
treasury_duration = '1month'
elif td.days <= 93:
treasury_duration = '3month'
elif td.days <= 186:
treasury_duration = '6month'
elif td.days <= 366:
treasury_duration = '1year'
elif td.days <= 365 * 2 + 1:
treasury_duration = '2year'
elif td.days <= 365 * 3 + 1:
treasury_duration = '3year'
elif td.days <= 365 * 5 + 2:
treasury_duration = '5year'
elif td.days <= 365 * 7 + 2:
treasury_duration = '7year'
elif td.days <= 365 * 10 + 2:
treasury_duration = '10year'
else:
treasury_duration = '30year'
return treasury_duration
def choose_treasury(select_treasury, treasury_curves, start_session,
end_session, trading_calendar, compound=True):
"""
Find the latest known interest rate for a given duration within a date
range.
If we find one but it's more than a trading day ago from the date we're
looking for, then we log a warning
"""
treasury_duration = select_treasury(start_session, end_session)
search_day = None
if end_session in treasury_curves.index:
rate = get_treasury_rate(treasury_curves,
treasury_duration,
end_session)
if rate is not None:
search_day = end_session
if not search_day:
# in case end date is not a trading day or there is no treasury
# data, search for the previous day with an interest rate.
search_days = treasury_curves.index
# Find rightmost value less than or equal to end_session
i = search_days.searchsorted(end_session)
for prev_day in search_days[i - 1::-1]:
rate = get_treasury_rate(treasury_curves,
treasury_duration,
prev_day)
if rate is not None:
search_day = prev_day
search_dist = trading_calendar.session_distance(
end_session, prev_day
)
break
if search_day:
if (search_dist is None or search_dist > 1) and \
search_days[0] <= end_session <= search_days[-1]:
message = "No rate within 1 trading day of end date = \
{dt} and term = {term}. Using {search_day}. Check that date doesn't exceed \
treasury history range."
message = message.format(dt=end_session,
term=treasury_duration,
search_day=search_day)
log.warn(message)
if search_day:
td = end_session - start_session
if compound:
return rate * (td.days + 1) / 365
else:
return rate
message = "No rate for end date = {dt} and term = {term}. Check \
that date doesn't exceed treasury history range."
message = message.format(
dt=end_session,
term=treasury_duration
)
raise Exception(message)