def test_log_likelihood(self): model = GARCHModel(0.2, 0.3, 0.4, sc=self.sc) n = 10000 ts = np.array(model.sample(n)) logLikelihoodWithRightModel = model.log_likelihood(ts) logLikelihoodWithWrongModel1 = GARCHModel(.3, .4, .5, sc=self.sc).log_likelihood(ts) logLikelihoodWithWrongModel2 = GARCHModel(.25, .35, .45, sc=self.sc).log_likelihood(ts) logLikelihoodWithWrongModel3 = GARCHModel(.1, .2, .3, sc=self.sc).log_likelihood(ts) self.assertTrue(logLikelihoodWithRightModel > logLikelihoodWithWrongModel1) self.assertTrue(logLikelihoodWithRightModel > logLikelihoodWithWrongModel2) self.assertTrue(logLikelihoodWithRightModel > logLikelihoodWithWrongModel3) self.assertTrue(logLikelihoodWithWrongModel2 > logLikelihoodWithWrongModel1)
def test_log_likelihood(self): model = GARCHModel(0.2, 0.3, 0.4, sc=self.sc) n = 10000 ts = np.array(model.sample(n)) logLikelihoodWithRightModel = model.log_likelihood(ts) logLikelihoodWithWrongModel1 = GARCHModel( 0.3, 0.4, 0.5, sc=self.sc).log_likelihood(ts) logLikelihoodWithWrongModel2 = GARCHModel( 0.25, 0.35, 0.45, sc=self.sc).log_likelihood(ts) logLikelihoodWithWrongModel3 = GARCHModel( 0.1, 0.2, 0.3, sc=self.sc).log_likelihood(ts) self.assertTrue( logLikelihoodWithRightModel > logLikelihoodWithWrongModel1) self.assertTrue( logLikelihoodWithRightModel > logLikelihoodWithWrongModel2) self.assertTrue( logLikelihoodWithRightModel > logLikelihoodWithWrongModel3) self.assertTrue( logLikelihoodWithWrongModel2 > logLikelihoodWithWrongModel1)