def test_calculate_turnover(self):
algorithm = Algorithm()
#simple weights - no change in weights
current_weights = np.array([0.5, 0.5])
last_weights = np.array([0.5, 0.5])
current_individual_returns = np.array([1.1, 1.1])
result = algorithm.calculate_turnover2(current_weights,
last_weights,
current_individual_returns,
iteration=999)
self.assertEqual(result, 0.0)
#simple weights - change with same returns
current_weights = np.array([0.5, 0.5])
last_weights = np.array([0.6, 0.4])
current_individual_returns = np.array([1.0, 1.0])
result = algorithm.calculate_turnover2(current_weights,
last_weights,
current_individual_returns,
iteration=999)
self.assertAlmostEqual(result, 0.2, 3)
#simple weights - change with same returns
current_weights = np.array([0.5, 0.5])
last_weights = np.array([0.6, 0.4])
current_individual_returns = np.array([1.0, 1.0])
result = algorithm.calculate_turnover2(current_weights,
last_weights,
current_individual_returns,
iteration=999)
self.assertAlmostEqual(result, 0.2, 3)
#simple weights - no change but different returns
current_weights = np.array([0.5, 0.5])
last_weights = np.array([0.5, 0.5])
current_individual_returns = np.array([1.2, 1.0])
result = algorithm.calculate_turnover2(current_weights,
last_weights,
current_individual_returns,
iteration=999)
self.assertAlmostEqual(result, 0.1, 3)
def test_calculate_turnover_negative_weights(self):
algorithm = Algorithm()
#simple weights - no change in weights
current_weights = np.array([0.6, -0.3, 0.4])
last_weights = np.array([0.6, -0.3, 0.4])
current_individual_returns = np.array([1.1, 1.1, 1.0])
result = algorithm.calculate_turnover2(current_weights,
last_weights,
current_individual_returns,
iteration=999)
self.assertAlmostEqual(result, 0.06, 3)
