// Objective function is Roger Lee's G*exp(d*Tau) function
// or Lord and Kahl's optimal alpha function
public double f(double[] x, double[] param)
{
LordKahl LK = new LordKahl();
if (GlobalVars.ObjFunChoice == "RogerLee")
{
double kappa = param[0];
double rho = param[1];
double sigma = param[2];
double tau = param[3];
return(LK.RogerLeeGExpD(x[0], kappa, rho, sigma, tau));
}
else if (GlobalVars.ObjFunChoice == "LordKahl")
{
double kappa = param[0];
double theta = param[1];
double lambda = param[2];
double rho = param[3];
double sigma = param[4];
double tau = param[5];
double K = param[6];
double S = param[7];
double r = param[8];
double v0 = param[9];
return(LK.LordKahlFindAlpha(x[0], kappa, theta, lambda, rho, sigma, tau, K, S, r, v0));
}
else
{
return(0.0);
}
}
static void Main(string[] args)
{
double S = 1.0; // Spot Price
double K = 1.2; // Strike Price
double T = 1.0; // Maturity in Years
double rf = 0.0; // Interest Rate
double q = 0.0; // Dividend yield
double rho = -0.7; // Heston Parameter: Correlation
double kappa = 1.0; // Heston Parameter
double theta = 0.1; // Heston Parameter
double lambda = 0.0; // Heston Parameter
double sigma = 1.0; // Heston Parameter: Volatility of Variance
double v0 = 0.1; // Heston Parameter: Current Variance
int trap = 1; // 1="Little Trap" characteristic function
// Verify : kappa - rho*sigma >0
double check = kappa - rho * sigma;
if (check < 0)
{
Console.WriteLine("Warning: kappa - rho*sigma = {0:F3} is < 0", check);
Console.WriteLine("------------------------------------------");
}
// Bounds on alpha and optimal alpha
// Shows multiple solutions to Rogers Lee's formula
// in which we solve for "a" in g(-ia)*exp(d(-ia)*T) = 1
LordKahl LK = new LordKahl();
double start = -15.0;
double increment = 0.01;
Complex g, d, E;
double E1;
Complex i = new Complex(0.0, 1.0);
double[] A = new Double[3001];
double[] y = new Double[3001];
double[] z = new Double[3001];
for (int j = 0; j <= 3000; j++)
{
A[j] = start + j * increment;
g = LK.RogerLeeG(-i * A[j], kappa, rho, sigma);
d = LK.RogerLeeD(-i * A[j], kappa, rho, sigma);
E = g * Complex.Exp(d * T);
E1 = E.Real;
y[j] = (E1 - 1.0);
z[j] = 0.0;
}
// Find yMax and yMin from Roger Lee's closed form
double ymax = (sigma - 2.0 * kappa * rho + Math.Sqrt(sigma * sigma - 4.0 * kappa * rho * sigma + 4.0 * kappa * kappa))
/ (2.0 * sigma * (1.0 - rho * rho));
double ymin = (sigma - 2.0 * kappa * rho - Math.Sqrt(sigma * sigma - 4.0 * kappa * rho * sigma + 4.0 * kappa * kappa))
/ (2.0 * sigma * (1 - rho * rho));
// Settings for the Nelder Mead algorithm
int N = 1; // Number of parameters in f(x) to find
int NumIters = 1; // First Iteration
double MaxIters = 5000; // Maximum number of iterations
double Tolerance = 1e-20; // Tolerance on best and worst function values
// Starting values (vertices) in vector form. Add more as needed
double [,] s1 = new double [N, N + 1];
// Vertice 0 Vertice 1
s1[0, 0] = ymin - 0.09; s1[0, 1] = ymin - 1.01;
// Select the Roger Lee function as the objective function
GlobalVars.ObjFunChoice = "RogerLee";
// Arrange parameters in a vector to pass to Nelder Mead function
double[] paramRL = new double[4];
paramRL[0] = kappa;
paramRL[1] = rho;
paramRL[2] = sigma;
paramRL[3] = T;
// Calculate lower limit of the the range Ax
NelderMeadAlgo NM = new NelderMeadAlgo();
double[] AxLo = NM.NelderMead(NM.f, N, NumIters, MaxIters, Tolerance, s1, paramRL);
double yneg = AxLo[0];
// Calculate upper limit of the the range Ax
double[,] s2 = new double[N, N + 1];
s2[0, 0] = ymax + 4.99; s2[0, 1] = ymax + 5.01;
double[] AxHi = NM.NelderMead(NM.f, N, NumIters, MaxIters, Tolerance, s2, paramRL);
double ypos = AxHi[0];
// Bounds on alpha
double AlphaMax = ypos - 1.0;
double AlphaMin = yneg - 1.0;
// Select the KahlLord function as the objective function
GlobalVars.ObjFunChoice = "LordKahl";
// Starting values for Lord and Kahl
double StartVal = (AlphaMax + AlphaMin) / 2.0;
double[,] s3 = new double[N, N + 1];
s3[0, 0] = StartVal + 0.01; s3[0, 1] = StartVal - 0.01;
// Parameters for Lord and Kahl
double[] paramLK = new double[10];
paramLK[0] = kappa;
paramLK[1] = theta;
paramLK[2] = lambda;
paramLK[3] = rho;
paramLK[4] = sigma;
paramLK[5] = T;
paramLK[6] = K;
paramLK[7] = S;
paramLK[8] = rf;
paramLK[9] = v0;
// Lord and Kahl optimal alpha
double[] AlphaOptimal = NM.NelderMead(NM.f, N, NumIters, MaxIters, Tolerance, s3, paramLK);
// Write the results
Console.WriteLine("Roger Lee bounds on alpha");
Console.WriteLine("--------------------------------------------------------");
Console.WriteLine("Ymin and Ymax are ({0,7:F4}, {1,7:F4})", ymin, ymax);
Console.WriteLine("The range Ax is ({0,7:F4}, {1,7:F4})", yneg, ypos);
Console.WriteLine("(AlphaMin,AlphMax) is ({0,7:F4}, {1,7:F4}) = Ax - 1", AlphaMin, AlphaMax);
Console.WriteLine("--------------------------------------------------------");
Console.WriteLine("Lord and Kahl optimal Alpha {0,7:F4}", AlphaOptimal[0]);
Console.WriteLine("--------------------------------------------------------");
Console.WriteLine("Note that optimal alpha in ({0,7:F4}, {1,7:F4})", AlphaMin, AlphaMax);
Console.WriteLine(" ");
}