def test_annualized_adjusted_rate(): """ Check annual rate of return.""" pa = np.array(dummy_data, dtype=schema) ra = metrics.rate_array(pa) aar = metrics.annualized_adjusted_rate(ra) # This is not a great test ... needs to be independently calculated, # as does the rate array data. np.testing.assert_almost_equal(aar, 2.6020844941637074)
def update_metrics(self): self.dates = self.stock_data['date'] self.stock_prices = self.stock_data['adjclose'] self.bench_prices = self.bench_data['adjclose'] self.ratearray = rate_array(self.stock_data) self.bencharray = rate_array(self.bench_data) # TODO: Not sure if these are the metrics I'm looking for... self.annual_volatility = volatility(self.ratearray) self.beta = beta_bb(self.ratearray, self.bencharray) self.annualized_adjusted_return = annualized_adjusted_rate(self.ratearray, rfr=0.01) self.expected_return = expected_return(self.ratearray, self.bencharray, rfr=self.rfr) return