import scipy
import scipy.stats
from scipy.stats import norm
import math
import random
import statistics
import codecs

def monteCarlo():
    s = 600
    k = 650
    v = 0.25
    T = 1
    t = 1/52
    r = 0.04
    q = 0.04
    N = 1

    stockPrices = []
    callOptionPrices = []
    putOptionPrices = []

    def blackScholesCall():
        d1 = (math.log(s/k)+(r-q+(v*v)/2)*T)/(v*math.sqrt(T))
        d2 = d1 - v*math.sqrt(T)
        c = s*math.exp(-q*T)*norm.cdf(d1) - k*math.exp(-r*T)*norm.cdf(d2)
        return c

    def blackScholesPut():
        d1 = (math.log(s/k)+(r-q+(v*v)/2)*T)/(v*math.sqrt(T))
        d2 = d1 - v*math.sqrt(T)
        p = k*math.exp(-r*T)*norm.cdf(-d2) - s*math.exp(-q*T)*norm.cdf(-d1)
        return p

    def nextPrice(cP):
        p = cP*math.exp((r-q-(v*v)/2)*t+v*math.sqrt(t)* norm.ppf(random.random()))
        return p

    def callOptionPricePV(sP):
        p = math.exp(-r*T)*max(sP-k,0)
        return p

    def putOptionPricePV(sP):
        p = math.exp(-r*T)*max(k-sP,0)
        return p

    for j in range(0,N-1):
        for i in range(0,51):
            s = nextPrice(s)

        stockPrices.append(s)
        callOptionPrices.append(callOptionPricePV(s))
        putOptionPrices.append(putOptionPricePV(s))

    print("------Call option------")
    print("Black Scholes Pricing is: " + str(blackScholesCall()))