def test_downsideCorrel(self): portfolio = Portfolio(self.stock_db, percent_allocations=[0.5, 0.4, 0.1]) returns = np.array([1.01, 1.02, 1.03, 1.04, 1.05], dtype=np.float64) portfolio.backtested_returns = returns portfolio._stock_db.price_change_array = [[1.00, 1.01, 1.02], [1.01, 1.00, 1.03], [1.02, 0.99, 1.04], [1.03, 0.98, 1.05], [1.04, 0.97, 1.06]] portfolio.getScore(1.05) self.assertAlmostEqual(portfolio.downside_correl, 0.04)
def test_score(self): portfolio = Portfolio(self.stock_db, percent_allocations=[0.5, 0.4, 0.1]) returns = np.array([1.01, 1.02, 1.03, 1.04, 1.05], dtype=np.float64) portfolio.backtested_returns = returns portfolio._stock_db.price_change_array = [[1.00, 1.01, 1.02], [1.01, 1.00, 1.03], [1.02, 0.99, 1.04], [1.03, 0.98, 1.05], [1.04, 0.97, 1.06]] score = portfolio.getScore(1.021) self.assertAlmostEqual(portfolio.score, -5.80858974126046) self.assertAlmostEqual(score, -5.80858974126046)