def test_constant_vol_uses_constants(self):
spot = 10
vol = 2
sut = ConstantVolatilityStock(spot, vol)
res = sut.find_volatilities(0.01, [0 for _ in xrange(100)])
self.assertEqual(list(res), [vol for _ in xrange(100)])
def test_swaption(self):
spot = 100
strike = 110
risk_free = 0.05
expiry = 1
vol = 0.2
s1 = ConstantVolatilityStock(100, 0.2)
s2 = ConstantVolatilityStock(85, 0.4)
option = EuropeanSwaption([s1, s2], risk_free, expiry, False)
interval = 0.1
solver = HeuristicLayeredMCOptionSolver(interval)
print solver.solve_option_price(option)
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 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 main():
import multiprocessing
from mlmc.stock import ConstantVolatilityStock
pool = multiprocessing.Pool(4)
stock = ConstantVolatilityStock(10, 0.1)
x = pool.map(calculate, [[create_simple_path] + [[stock], 0.01, 1, 100]
for _ in xrange(100)])
import pprint
pprint.pprint(sorted(xx[0] for xx in x))
def test_put_option(self):
spot = 100
strike = 110
risk_free = 0.05
expiry = 1
vol = 0.2
stock = ConstantVolatilityStock(spot, vol)
option = EuropeanStockOption([stock], risk_free, expiry, False, strike)
solver = AnalyticEuropeanStockOptionSolver()
put_value = black_scholes(spot, strike, risk_free, 0, vol, expiry, 'put')
self.assertAlmostEqual(put_value, 10.6753248248)
self.assertAlmostEqual(solver.solve_option_price(option),
10.6753248248)
def test_option_pricing(self):
spot = 100
strike = 110
risk_free = 0.05
expiry = 1
vol = 0.2
stock = ConstantVolatilityStock(spot, vol)
# is_call = True
option = EuropeanStockOption([stock], risk_free, expiry, True, strike)
solver = AnalyticEuropeanStockOptionSolver()
call_value = black_scholes(spot, strike, risk_free, 0, vol, expiry, 'call')
self.assertAlmostEqual(call_value, 6.04008812972)
self.assertAlmostEqual(solver.solve_option_price(option),
6.04008812972)
def test_put_option(self):
spot = 100
strike = 110
risk_free = 0.05
expiry = 1
vol = 0.2
stock = ConstantVolatilityStock(spot, vol)
option = EuropeanStockOption([stock], risk_free, expiry, False, strike)
interval = 0.1
expected = 10.6753248248
lower_bound = expected - interval
upper_bound = expected + interval
solver = NaiveMCOptionSolver(interval)
n_runs = 20
in_bound_count = sum(
1 for _ in xrange(n_runs)
if lower_bound <= solver.solve_option_price(option) <= upper_bound
)
self.assertGreaterEqual(in_bound_count, 0.95*n_runs)
def test_call_option(self):
spot = 100
strike = 110
risk_free = 0.05
expiry = 1
vol = 0.2
stock = ConstantVolatilityStock(spot, vol)
option = EuropeanStockOption([stock], risk_free, expiry, True, strike)
interval = 0.1
expected = 6.04008812972
lower_bound = expected - interval
upper_bound = expected + interval
solver = SimpleLayeredMCOptionSolver(interval)
n_runs = 20
in_bound_count = sum(
1 for _ in xrange(n_runs)
if lower_bound <= solver.solve_option_price(option) <= upper_bound
)
self.assertGreaterEqual(in_bound_count, 0.95*n_runs)
def test_valuation_for_put(self):
stock = ConstantVolatilityStock(10, 1)
sut = EuropeanSwaption([stock, stock], 0.05, 1, False)
self.assertEqual(sut.determine_payoff(10, 4), 0)
self.assertEqual(sut.determine_payoff(4, 10), 6)
def test_valuation_for_call(self):
stock = ConstantVolatilityStock(10, 1)
sut = EuropeanStockOption([stock], 0.05, 1, True, 10)
self.assertEqual(sut.determine_payoff(6), 0)
self.assertEqual(sut.determine_payoff(15), 5)