75 lines
2.5 KiB
C#
Executable File
75 lines
2.5 KiB
C#
Executable File
using System;
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using System.Collections.Generic;
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using MarketData.MarketDataModel;
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namespace MarketData.Numerical
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{
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/// <summary>
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/// Black Sholes Option Pricing Model for simplest scenario.
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/// This is an adoption of the Abramowitz Stegun approximation for the cumulative normal distribution
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/// </summary>
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public class BlackScholesOptionPricingModel
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{
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private BlackScholesOptionPricingModel()
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{
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}
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/// <summary>
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/// Get Option price by applying BlackScholesOptionPricingModel
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/// </summary>
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/// <param name="optionType">Enum to indicate whether Call or Put</param>
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/// <param name="S">Price of underlying</param>
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/// <param name="X">Strike price</param>
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/// <param name="T">Time to expiration in years</param>
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/// <param name="r">Risk free interest rate</param>
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/// <param name="v">Volatility</param>
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/// <returns></returns>
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public static double GetPrice(OptionTypeEnum optionType, double S, double X, double T, double r, double v)
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{
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double d1 = 0.0;
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double d2 = 0.0;
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double optionValue = 0.0;
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d1 = (Math.Log(S / X) + (r + v * v / 2.0) * T) / (v * Math.Sqrt(T));
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d2 = d1 - v * Math.Sqrt(T);
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if (optionType == OptionTypeEnum.CallOption)
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{
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optionValue = S * CumulativeNormalDistributionFun(d1) - X * Math.Exp(-r * T) * CumulativeNormalDistributionFun(d2);
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}
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else if (optionType == OptionTypeEnum.PutOption)
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{
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optionValue = X * Math.Exp(-r * T) * CumulativeNormalDistributionFun(-d2) - S * CumulativeNormalDistributionFun(-d1);
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}
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return optionValue;
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}
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/// <summary>
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/// Cumulative normal distribution function
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/// </summary>
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/// <param name="d"></param>
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/// <returns></returns>
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private static double CumulativeNormalDistributionFun(double d)
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{
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double L = 0.0;
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double K = 0.0;
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double dCND = 0.0;
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const double a1 = 0.31938153;
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const double a2 = -0.356563782;
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const double a3 = 1.781477937;
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const double a4 = -1.821255978;
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const double a5 = 1.330274429;
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L = Math.Abs(d);
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K = 1.0 / (1.0 + 0.2316419 * L);
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dCND = 1.0 - 1.0 / Math.Sqrt(2 * Convert.ToDouble(Math.PI)) * Math.Exp(-L * L / 2.0) * (a1 * K + a2 * K * K + a3 * Math.Pow(K, 3.0) + a4 * Math.Pow(K, 4.0) + a5 * Math.Pow(K, 5.0));
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if (d < 0)
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{
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return 1.0 - dCND;
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}
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else
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{
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return dCND;
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}
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}
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}
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}
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