BUG: Return NaN beta when missing benchmarks

instead of raising LinAlgError
This commit is contained in:
Richard Frank
2015-11-18 10:40:54 -05:00
parent a9c91a7fbf
commit f4cf30dd19
2 changed files with 22 additions and 0 deletions
+18
View File
@@ -18,6 +18,10 @@ import datetime
import calendar
import numpy as np
import pytz
from itertools import chain
from six import itervalues
import zipline.finance.risk as risk
from zipline.utils import factory
@@ -622,3 +626,17 @@ class TestRisk(unittest.TestCase):
)
self.assert_month(start_date.month, col[-1].end_date.month)
self.assert_last_day(col[-1].end_date)
def test_sparse_benchmark(self):
benchmark_returns = self.benchmark_returns_06.copy()
# Set every other day to nan.
benchmark_returns.iloc[::2] = np.nan
report = risk.RiskReport(
self.algo_returns_06,
self.sim_params,
benchmark_returns=benchmark_returns,
env=self.env,
)
for risk_period in chain.from_iterable(itervalues(report.to_dict())):
self.assertIsNone(risk_period['beta'])
+4
View File
@@ -259,6 +259,10 @@ class RiskMetricsPeriod(object):
returns_matrix = np.vstack([self.algorithm_returns,
self.benchmark_returns])
C = np.cov(returns_matrix, ddof=1)
if not np.isfinite(C).all():
return np.nan, np.nan, np.nan, np.nan, []
eigen_values = la.eigvals(C)
condition_number = max(eigen_values) / min(eigen_values)
algorithm_covariance = C[0][1]