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)
