--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/fbs/helpers.py	Mon Nov 15 23:14:41 2021 +0100
@@ -0,0 +1,62 @@
+"""
+Helper methods
+"""
+
+import math
+import numpy as np
+from scipy.stats import norm
+
+
+class Option:
+    def __init__(self, spot_price, exercise_price, risk_free_rate, std, expiration):
+        """
+        :param spot_price: spot price of the underlying asset at t0, float, required
+        :param exercise_price: exercise price of the option, float, required
+        :param risk_free_rate: float, required
+        :param std: standard deviation of the return rate of P, float, required
+        :param expiration: time to expiration, float, required
+        :return: None
+        """
+
+        self.s = spot_price
+        self.k = exercise_price
+        self.r = risk_free_rate
+        self.std = std
+        self.t = expiration
+
+    def compute_eu_call_price(self):
+        """
+        Determine the value of an European call option
+        :return:
+        """
+
+        d1 = self.compute_d1()
+        d2 = self.compute_d2()
+
+        price = self.s * norm.cdf(d1) - self.k * math.exp(- self.r * self.t) * norm.cdf(d2)
+
+        return price
+
+    def compute_d1(self):
+        """
+        Determine d1 coefficient
+        :return: float
+        """
+
+        numerator = (np.log(self.s / self.k) + (self.r + (self.std**2 / 2)) * self.t)
+        denominator = self.std * np.sqrt(self.t)
+
+        d1 = numerator / denominator
+
+        return d1
+
+    def compute_d2(self):
+        """
+        Determine d2 coefficient
+        :return: float
+        """
+
+        d1 = self.compute_d1()
+        d2 = d1 - self.std * np.sqrt(self.t)
+
+        return d2