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)
