def test_vol_types(self):
"""Test correctness of types."""
moneyness, maturity, premium, call = 0, .3, .05, True
vol = imp_vol(moneyness, maturity, premium, call)
self.assertIsInstance(vol, np.ndarray)
self.assertEqual(vol.shape, (1,))
moneyness, maturity, premium, call = [-.1, .1], .3, .05, True
vol = imp_vol(moneyness, maturity, premium, call)
self.assertIsInstance(vol, np.ndarray)
self.assertEqual(vol.shape, (2,))
def test_vol_types(self):
"""Test correctness of types."""
moneyness, maturity, premium, call = 0, .3, .05, True
vol = imp_vol(moneyness, maturity, premium, call)
self.assertIsInstance(vol, np.ndarray)
self.assertEqual(vol.shape, (1, ))
moneyness, maturity, premium, call = [-.1, .1], .3, .05, True
vol = imp_vol(moneyness, maturity, premium, call)
self.assertIsInstance(vol, np.ndarray)
self.assertEqual(vol.shape, (2, ))
def test_vol_values(self):
"""Test values of implied volatility."""
premium = .024
price = 1
strike = 1
riskfree = .02
maturity = 30/365
call = True
moneyness = lfmoneyness(price, strike, riskfree, maturity)
vol = imp_vol(moneyness, maturity, premium, call)
self.assertAlmostEqual(float(vol), .2, 2)
strike = [1, .95]
premium = [.024, .057]
moneyness = lfmoneyness(price, strike, riskfree, maturity)
vol = imp_vol(moneyness, maturity, premium, call)
np.testing.assert_array_almost_equal(vol, [.2, .2], 2)
def test_vol_values(self):
"""Test values of implied volatility."""
premium = .024
price = 1
strike = 1
riskfree = .02
maturity = 30 / 365
call = True
moneyness = lfmoneyness(price, strike, riskfree, maturity)
vol = imp_vol(moneyness, maturity, premium, call)
self.assertAlmostEqual(float(vol), .2, 2)
strike = [1, .95]
premium = [.024, .057]
moneyness = lfmoneyness(price, strike, riskfree, maturity)
vol = imp_vol(moneyness, maturity, premium, call)
np.testing.assert_array_almost_equal(vol, [.2, .2], 2)
maturity = 30/365
premium = .057
call = True
moneyness = lfmoneyness(price, strike, riskfree, maturity)
vol = impvol_bisection(moneyness, maturity, premium, call)
count = int(1e2)
sigma = np.random.uniform(.05, .8, count)
moneyness = np.random.uniform(-.1, .1, count)
premium = blackscholes_norm(moneyness, maturity, sigma, call)
text = 'Time elapsed: %.2f seconds'
time_start = time.time()
# Based on SciPy root method
vol = imp_vol(moneyness, maturity, premium, call)
print(np.allclose(sigma, vol))
print(text % (time.time() - time_start))
time_start = time.time()
# Based on bisection method
vol = impvol_bisection(moneyness, maturity, premium, call)
print('Relative difference (percent) = ', ((sigma/vol-1).max()*100))
print(np.allclose(vol, sigma, rtol=1e-3))
print(text % (time.time() - time_start))
table = pd.DataFrame({'premium': premium, 'moneyness': moneyness})
table['maturity'] = maturity
table['call'] = call
table['imp_vol'] = impvol_table(table)
maturity = 30 / 365
premium = .057
call = True
moneyness = lfmoneyness(price, strike, riskfree, maturity)
vol = impvol_bisection(moneyness, maturity, premium, call)
count = int(1e2)
sigma = np.random.uniform(.05, .8, count)
moneyness = np.random.uniform(-.1, .1, count)
premium = blackscholes_norm(moneyness, maturity, sigma, call)
text = 'Time elapsed: %.2f seconds'
time_start = time.time()
# Based on SciPy root method
vol = imp_vol(moneyness, maturity, premium, call)
print(np.allclose(sigma, vol))
print(text % (time.time() - time_start))
time_start = time.time()
# Based on bisection method
vol = impvol_bisection(moneyness, maturity, premium, call)
print('Relative difference (percent) = ', ((sigma / vol - 1).max() * 100))
print(np.allclose(vol, sigma, rtol=1e-3))
print(text % (time.time() - time_start))
table = pd.DataFrame({'premium': premium, 'moneyness': moneyness})
table['maturity'] = maturity
table['call'] = call
table['imp_vol'] = impvol_table(table)