def test_stocks_input_unchanged(self):
'''
The stock objects used as inputs should not themselves be walked
'''
stocks = [ConstantVolatilityStock(i, 1) for i in xrange(1, 5)]
create_simple_path(stocks, risk_free=0.01, T=10, n_steps=5)
for spot, stock in enumerate(stocks, start=1):
self.assertEqual(stock.post_walk_price, spot)
def test_all_stocks_walked(self):
'''
The stock objects used as inputs should not themselves be walked
'''
stocks = [ConstantVolatilityStock(i, 1) for i in xrange(1, 5)]
paths = create_simple_path(stocks, risk_free=0.01, T=10, n_steps=5)
self.assertEqual(len(paths), len(stocks))
def run_bottom_level(self, option, steps):
'''
Run the bottom level of E-M paths. Each of the E-M paths
will have only one step
option: Option. What we're looking to price
steps: int. Totally irrelevant, used only because run_upper_levels
requires it as part of the signature.
'''
result = path.create_simple_path(option.assets, option.risk_free,
option.expiry, 1, self.rng_creator)
return option.determine_payoff(*result),
def _simulate_paths(self, option, n_steps, discount):
stat_tracker = StatTracker(discount)
cnt = itertools.count()
while next(cnt) < 10 or stat_tracker.get_interval_length(
self.z_score) > self.max_interval_length:
result = path.create_simple_path(option.assets, option.risk_free,
option.expiry, n_steps,
self.rng_creator)
payoff = option.determine_payoff(*result)
stat_tracker.add_sample(payoff)
return stat_tracker
def test_path_creation_will_walk_all_steps(self):
spots = map(float, xrange(1, 3))
r = 0.01
T = 5
n_steps = 2
stocks = [MockStock(s) for s in spots]
samples = np.array([
np.array([5, 6, 7]),
np.array([1, 2, 3]),
np.array([9, 8, 7]),
np.array([4, 6, 2]),
])
rng_creator = functools.partial(MockSampleCreator, samples)
paths = create_simple_path(stocks, r, T, n_steps, rng_creator)
expecteds = [376.063125, 21610.50125]
for observed, expected in zip(paths, expecteds):
self.assertAlmostEqual(observed, expected)
def run_bottom_level(self, option, steps):
result = path.create_simple_path(option.assets, option.risk_free,
option.expiry, 1, self.rng_creator)
return option.determine_payoff(*result),