def test_features(self):
m = BSAmericanBinaryOption()
assert m.features() == [
"log_moneyness",
"max_log_moneyness",
"expiry_time",
"volatility",
]
_ = [get_feature(f) for f in m.features()]
def test_example(self):
from pfhedge import Hedger
from pfhedge.instruments import AmericanBinaryOption
from pfhedge.instruments import BrownianStock
deriv = AmericanBinaryOption(BrownianStock(), strike=1.03)
model = BSAmericanBinaryOption(deriv)
hedger = Hedger(model, model.features())
price = hedger.price(deriv)
assert torch.allclose(price, torch.tensor(0.6219), atol=1e-4)
def test_price(self):
m = BSAmericanBinaryOption()
result = m.price(-0.1, -0.1, 0.1, 0.2) # s, m, t, v
expect = torch.tensor(0.5778)
assert torch.allclose(result, expect, atol=1e-4)
result = m.price(-0.0001, -0.0001, 0.1, 0.2) # s, m, t, v
expect = torch.tensor(0.9995)
assert torch.allclose(result, expect, atol=1e-4)
result = m.price(0.1, 0.1, 0.1, 0.2) # s, m, t, v
expect = torch.tensor(1.0)
assert torch.allclose(result, expect, atol=1e-4)
def test_delta(self):
m = BSAmericanBinaryOption()
result = m.delta(-0.1, -0.1, 0.1, 0.2) # s, m, t, v
expect = torch.tensor(0.7819)
assert torch.allclose(result, expect, atol=1e-4)
result = m.delta(0.1, 0.1, 0.1, 0.2) # s, m, t, v
expect = torch.tensor(0.0)
assert torch.allclose(result, expect, atol=1e-4)
result = m.delta(-0.0001, -0.0001, 0.1, 0.2) # s, m, t, v
expect = torch.tensor(1.1531)
assert torch.allclose(result, expect, atol=1e-4)
def test_repr(self):
m = BSAmericanBinaryOption()
assert repr(m) == "BSAmericanBinaryOption()"
liability = AmericanBinaryOption(BrownianStock(), strike=1.1)
m = BSAmericanBinaryOption(liability)
assert repr(m) == "BSAmericanBinaryOption(strike=1.1)"
with pytest.raises(ValueError):
# not yet supported
liability = AmericanBinaryOption(BrownianStock(),
strike=1.1,
call=False)
m = BSAmericanBinaryOption(liability)
assert repr(m) == "BSAmericanBinaryOption(call=False, strike=1.1)"
def test_implied_volatility(self):
# log_moneyness, max_log_moneyness, expiry_time, price
x = torch.tensor([
[-0.01, -0.01, 0.1, 0.5],
[-0.01, -0.01, 0.1, 0.6],
[-0.01, -0.01, 0.1, 0.7],
])
m = BSAmericanBinaryOption()
iv = m.implied_volatility(x[:, 0], x[:, 1], x[:, 2], x[:, 3])
result = BSAmericanBinaryOption().price(x[:, 0], x[:, 1], x[:, 2], iv)
expect = x[:, -1]
print(result)
print(expect)
assert torch.allclose(result, expect, atol=1e-4)
def test_shape(self):
torch.distributions.Distribution.set_default_validate_args(False)
m = BSAmericanBinaryOption()
self.assert_shape_delta(m)
# self.assert_shape_gamma(m)
self.assert_shape_price(m)
self.assert_shape_forward(m)
def test_gamma(self):
m = BSAmericanBinaryOption()
result = m.gamma(-0.01, -0.01, 1.0, 0.2).item()
assert np.isclose(result, 0.7618406414985657)
with pytest.raises(ValueError):
# not yet supported
m = BSAmericanBinaryOption(call=False)
result = m.gamma(-0.01, -0.01, 1.0, 0.2).item()
def test_forward(self):
m = BSAmericanBinaryOption()
x = torch.tensor([-0.1, -0.1, 0.1, 0.2]).reshape(1, -1)
result = m(x)
expect = torch.tensor(0.7819)
assert torch.allclose(result, expect, atol=1e-4)
x = torch.tensor([0.1, 0.1, 0.1, 0.2]).reshape(1, -1)
result = m(x)
expect = torch.tensor(0.0)
assert torch.allclose(result, expect, atol=1e-4)
x = torch.tensor([-0.0001, -0.0001, 0.1, 0.2]).reshape(1, -1)
result = m(x)
expect = torch.tensor(1.1531)
assert torch.allclose(result, expect, atol=1e-4)
def test_error_put(self):
with pytest.raises(ValueError):
# not yet supported
liability = AmericanBinaryOption(BrownianStock(), call=False)
BSAmericanBinaryOption(liability)