def test_option_prices_pos_carries(self, discount_rates, volatilities,
expiries, expected_prices):
"""Tests the prices for positive cost_of_carries."""
spots = np.array([80.0, 90.0, 100.0, 110.0, 120.0] * 2)
strikes = np.array([100.0] * 10)
is_call_options = [True] * 5 + [False] * 5
cost_of_carries = 0.04
computed_prices, converged, failed = adesi_whaley(
volatilities=volatilities,
strikes=strikes,
expiries=expiries,
discount_rates=discount_rates,
cost_of_carries=cost_of_carries,
spots=spots,
is_call_options=is_call_options,
dtype=tf.float64)
with self.subTest(name='ExpectedPrices'):
self.assertAllClose(expected_prices,
computed_prices,
rtol=5e-3,
atol=5e-3)
with self.subTest(name='AllConverged'):
self.assertAllEqual(converged, tf.ones_like(computed_prices))
with self.subTest(name='NonFailed'):
self.assertAllEqual(failed, tf.zeros_like(computed_prices))
def test_option_prices_no_cost_of_carries(self, dtype, discount_rates,
volatilities, expiries,
expected_prices):
"""Tests the prices when no cost_of_carries is supplied."""
spots = np.array([80.0, 90.0, 100.0, 110.0, 120.0])
strikes = np.array([100.0, 100.0, 100.0, 100.0, 100.0])
is_call_options = False
computed_prices, converged, failed = adesi_whaley(
volatilities=volatilities,
strikes=strikes,
expiries=expiries,
discount_rates=discount_rates,
spots=spots,
is_call_options=is_call_options,
tolerance=1e-5, # float32 does not converge to tolerance 1e-8
dtype=dtype)
with self.subTest(name='ExpectedPrices'):
self.assertAllClose(expected_prices,
computed_prices,
rtol=5e-3,
atol=5e-3)
with self.subTest(name='AllConverged'):
self.assertAllEqual(converged, tf.ones_like(computed_prices))
with self.subTest(name='NonFailed'):
self.assertAllEqual(failed, tf.zeros_like(computed_prices))
def test_option_prices(self, discount_rates, volatilities, expiries,
expected_prices):
"""Tests that the prices are correct."""
spots = np.array([80.0, 90.0, 100.0, 110.0, 120.0] * 2)
strikes = np.array([100.0] * 10)
is_call_options = np.array([True] * 5 + [False] * 5)
cost_of_carries = -0.04
computed_prices, converged, failed = self.evaluate(
adesi_whaley(volatilities=volatilities,
strikes=strikes,
expiries=expiries,
discount_rates=discount_rates,
cost_of_carries=cost_of_carries,
is_call_options=is_call_options,
spots=spots,
dtype=tf.float32))
expected_prices = np.array(expected_prices)
self.assertArrayNear(expected_prices, computed_prices, 5e-3)
def test_option_prices_b_equal_r(self, dtype, discount_rates, volatilities,
expiries, expected_prices):
"""Tests that the prices are correct.
Also tests that single and double precision both work"""
spots = np.array([80.0, 90.0, 100.0, 110.0, 120.0])
strikes = np.array([100.0, 100.0, 100.0, 100.0, 100.0])
cost_of_carries = discount_rates
is_call_options = False
computed_prices, converged, failed = self.evaluate(
adesi_whaley(volatilities=volatilities,
strikes=strikes,
expiries=expiries,
discount_rates=discount_rates,
cost_of_carries=cost_of_carries,
spots=spots,
is_call_options=is_call_options,
dtype=dtype))
expected_prices = np.array(expected_prices)
self.assertArrayNear(expected_prices, computed_prices, 5e-3)
def test_option_prices_all_call_options(self):
"""Tests call prices with zero discount."""
dtype = tf.float64
computed_prices, converged, failed = adesi_whaley(
volatilities=[0.2],
strikes=[104, 90],
expiries=[0.1, 1.0],
spots=[100],
tolerance=1e-08,
discount_rates=[0.0, 0.0],
dtype=dtype)
# Computed using tff.black_scholes.option_price_binomial
expected_prices = [1.05226366, 13.58957787]
with self.subTest(name='ExpectedPrices'):
self.assertAllClose(expected_prices,
computed_prices,
rtol=1e-4,
atol=5e-4)
with self.subTest(name='AllConverged'):
self.assertAllEqual(converged, tf.ones_like(computed_prices))
with self.subTest(name='NonFailed'):
self.assertAllEqual(failed, tf.zeros_like(computed_prices))
