def test_ts(self):
universe = make_randomwalk()
strategy = RandomStrategy().run(universe)
trades = strategy.trades
assert_equal(strategy.wealth().values, ts.wealth(trades, universe))
assert_equal(strategy.drawdown().values, ts.drawdown(trades, universe))
def test_handmade(self):
universe = pd.DataFrame({"A": [0.0, 3.0, 1.0, 4.0, 1.0, 5.0, 9.0, 2.0]})
trades = [trade("A").execute(universe)]
result = ts.drawdown(trades, universe)
expected = np.array([0.0, 0.0, -2.0, 0.0, -3.0, 0.0, 0.0, -7.0])
assert_equal(result, expected)
def test(self):
np.random.seed(42)
universe = make_randomwalk()
strategy = RandomStrategy().run(universe)
drawdown = ts.drawdown(strategy.trades, universe)
assert np.min(drawdown) == max_drawdown(strategy.trades, universe)
def test_monotonous(self):
"""
result = 0 if wealth is monotonously increasing
"""
universe = pd.DataFrame({"A": np.linspace(1, 2, 100)})
trades = [trade("A").execute(universe)]
result = ts.drawdown(trades, universe)
expected = np.zeros_like(result)
assert_equal(result, expected)
def test_zero(self):
"""
result = 0 if trade is zero
"""
universe = make_randomwalk()
strategy = RandomStrategy(min_lot=0, max_lot=0).run(universe)
result = ts.drawdown(strategy.trades, universe)
expected = np.zeros_like(result)
assert_equal(result, expected)