def UpAndOutCallPrototype(Spot):
#look at times
look_at_times = list(np.linspace(start=0, stop=Expiry, num=12))
#generate a path
market_params = {'spot':Spot, 'rate':rate, 'vol':Vol}
path_generator = GeneratorGBM(market_params)
path_generator.generator.set_seed(seed=0)
path_generator.sim_setup(look_at_times)
sum = 0.
Knockout = 108.
for i in range(0,num_paths):
path = path_generator.do_one_path()
# plt.plot(look_at_times,path)
# plt.show()
#Evaluate the payoff for path
#Check if knocks out above barrier
if any(map(lambda(x): x >= Knockout,path)):
this_payoff = 0
else:
#Calc payoff
po = VanillaCall(Strike=Strike)
this_payoff = po.po(path[-1]) #Get last element of path
sum += this_payoff
def AsianPrototype(Spot):
#look at times
look_at_times = list(np.linspace(start=0, stop=Expiry, num=12))
#generate a path
market_params = {'spot':Spot, 'rate':rate, 'vol':Vol}
path_generator = GeneratorGBM(market_params)
path_generator.sim_setup(look_at_times)
sum = 0.
for i in range(0,num_paths):
path = path_generator.do_one_path()
#plt.plot(look_at_times,path)
#plt.show()
#Evaluate the payoff for path
#Average of price - K
average_price = np.mean(path)
#Calc payoff
po = VanillaCall(Strike=Strike)
this_payoff = po.po(average_price)
sum += this_payoff
#Average and discount
price = math.exp(-rate*Expiry)*sum/num_paths
return price