def period_returns(self):
# check series is indeed a series
# assert isinstance(returns, pd.Series)
# check that all indices are increasing
# assert returns.index.is_monotonic_increasing
# make sure all entries non-negative
# assert not (prices < 0).any()
return period_returns(returns=self, today=self.index[-1])
def test_periods(self):
y = period_returns(ts.pct_change(), offset=periods(ts.index[-1]))
pdt.assert_series_equal(y, read_series("periods.csv", parse_dates=False), check_names=False)
def period_returns(self):
n = self.__nav.pct_change()
return period_returns(n, periods(today=n.index[-1]))
def test_period_returns(returns):
p = periods(today=pd.Timestamp("2015-05-01"))
x = 100 * period_returns(returns=returns, offset=p)
assert x["Three Years"] == pytest.approx(1.1645579858904798, 1e-10)