def setUp(self):
DefaultHeston = HestonBarrierOption(spot=100,
strike=100,
interest_rate=0.06,
volatility=0.2,
tenor=1.0,
mean_reversion=1,
mean_variance=0.12,
vol_of_variance=0.3,
correlation=0.4,
top=(False, 170.0))
option = DefaultHeston
# option = HestonOption(tenor=1, strike=99.0, volatility=0.2,
# mean_reversion=3, mean_variance=0.04,
# vol_of_variance=0.6, correlation=-0.7)
self.dt = 1.0 / 150.0
self.F = HestonFiniteDifferenceEngine(option,
nspots=150,
nvols=80,
force_bandwidth=None,
flip_idx_var=False)
self.F.init()
self.F.operators[1].diagonalize()
self.FG = FDG.HestonFiniteDifferenceEngine(option,
nspots=self.F.grid.shape[0],
nvols=self.F.grid.shape[1])
self.FG.make_operator_templates()
self.FG.set_zero_derivative()
self.FG.scale_and_combine_operators()
def setUp(self):
DefaultHeston = HestonBarrierOption(spot=100,
strike=100,
interest_rate=0.03125,
volatility=0.2,
tenor=1.0,
mean_reversion=1,
mean_variance=0.12,
vol_of_variance=0.3,
correlation=10.4,
top=(False, 170.0))
option = DefaultHeston
# option = HestonOption(tenor=1, strike=99.0, volatility=0.2,
# mean_reversion=3, mean_variance=0.04,
# vol_of_variance=0.6, correlation=-0.7)
self.dt = 1.0 / 2.0
self.F = HestonFiniteDifferenceEngine(option,
nspots=5,
nvols=5,
force_bandwidth=None,
force_exact=False,
flip_idx_var=False)
# self.F = HestonFiniteDifferenceEngine(H, nspots=100,
# nvols=100, spotdensity=10, varexp=4,
# var_max=12, flip_idx_spot=False,
# flip_idx_var=False, verbose=False,
# force_bandwidth=None,
# force_exact=False)
self.F.init()
self.FGG = FDG.HestonFiniteDifferenceEngine(
option,
force_exact=False,
nspots=self.F.grid.shape[0],
nvols=self.F.grid.shape[1])
self.FGG.set_zero_derivative()
self.FGG.make_operator_templates()
def setUp(self):
self.option = HestonBarrierOption()
self.s = np.array((4.5, 0.2, 5.5, 0, 3, 5.3, 0.001, 24, 1.3, 2.5))
self.state = np.array((1, 1, 1, 1, 1, 1, 1, 1, 1, 1), dtype=bool)
class BarrierOption_test(unittest.TestCase):
def setUp(self):
self.option = HestonBarrierOption()
self.s = np.array((4.5, 0.2, 5.5, 0, 3, 5.3, 0.001, 24, 1.3, 2.5))
self.state = np.array((1, 1, 1, 1, 1, 1, 1, 1, 1, 1), dtype=bool)
def test_knockout_impossible(self):
s = self.s.copy()
state = self.state.copy()
self.option.top = (False, np.infty)
self.option.monte_carlo_callback(s, state)
npt.assert_array_equal(np.ones(state.shape), state)
def test_knockout_inevitable(self):
self.option.top = (False, 0)
self.option.monte_carlo_callback(self.s, self.state)
npt.assert_array_equal(self.state, np.zeros(self.state.shape))
def test_knockout_partial(self):
self.option.top = (False, 3.0)
self.option.monte_carlo_callback(self.s, self.state)
res = np.array((0,1,0,1,0,0,1,0,1,1), dtype=bool)
npt.assert_array_equal(self.state, res)
def test_knockout_permanent(self):
self.option.top = (False, 3.0)
self.option.monte_carlo_callback(self.s, self.state)
res = np.array((0,1,0,1,0,0,1,0,1,1), dtype=bool)
self.s *= 0
self.option.monte_carlo_callback(self.s, self.state)
npt.assert_array_equal(self.state, res)
def test_knockout_double(self):
self.option.top = (False, 3.0)
self.option.bottom = (False, 1.0)
res = np.array((0,0,0,0,0,0,0,0,1,1), dtype=bool)
self.option.monte_carlo_callback(self.s, self.state)
npt.assert_array_equal(self.state, res)
