public double DHQuadExpSim(DHParam param, double S0, double Strike, double Mat, double r, double q, int T, int N, string PutCall)
{
RandomNumber RN = new RandomNumber();
NormInverse NI = new NormInverse();
double kappa1 = param.kappa1;
double theta1 = param.theta1;
double sigma1 = param.sigma1;
double v01 = param.v01;
double rho1 = param.rho1;
double kappa2 = param.kappa2;
double theta2 = param.theta2;
double sigma2 = param.sigma2;
double v02 = param.v02;
double rho2 = param.rho2;
// Time increment
double dt = Mat / T;
// Required quantities
double K01 = -rho1 * kappa1 * theta1 * dt / sigma1;
double K11 = dt / 2.0 * (kappa1 * rho1 / sigma1 - 0.5) - rho1 / sigma1;
double K21 = dt / 2.0 * (kappa1 * rho1 / sigma1 - 0.5) + rho1 / sigma1;
double K31 = dt / 2.0 * (1.0 - rho1 * rho1);
double K02 = -rho2 * kappa2 * theta2 * dt / sigma2;
double K12 = dt / 2.0 * (kappa2 * rho2 / sigma2 - 0.5) - rho2 / sigma2;
double K22 = dt / 2.0 * (kappa2 * rho2 / sigma2 - 0.5) + rho2 / sigma2;
double K32 = dt / 2.0 * (1.0 - rho2 * rho2);
// Initialize the variance and stock processes
double[,] V1 = new double[T, N];
double[,] V2 = new double[T, N];
double[,] S = new double[T, N];
// Starting values for the variance and stock processes
for (int k = 0; k <= N - 1; k++)
{
S[0, k] = S0; // Spot price
V1[0, k] = v01; // Heston v0 initial variance
V2[0, k] = v02; // Heston v0 initial variance
}
// Generate the stock and volatility paths
double m1, s1, phi1, p1, U1, b1, a1, Zv1;
double m2, s2, phi2, p2, U2, b2, a2, Zv2;
double beta1, beta2, B1, B2, logS;
for (int k = 0; k <= N - 1; k++)
{
for (int t = 1; t <= T - 1; t++)
{
m1 = theta1 + (V1[t - 1, k] - theta1) * Math.Exp(-kappa1 * dt);
s1 = V1[t - 1, k] * sigma1 *sigma1 *Math.Exp(-kappa1 *dt) / kappa1 * (1.0 - Math.Exp(-kappa1 * dt))
+ theta1 * sigma1 * sigma1 / 2.0 / kappa1 * Math.Pow(1.0 - Math.Exp(-kappa1 * dt), 2.0);
phi1 = s1 / (m1 * m1);
p1 = (phi1 - 1.0) / (phi1 + 1.0);
U1 = RN.RandomNum(0.0, 1.0);
if (phi1 < 0.5)
{
b1 = Math.Sqrt(2.0 / phi1 - 1.0 + Math.Sqrt(2.0 / phi1 * (2.0 / phi1 - 1.0)));
a1 = m1 / (1.0 + b1 * b1);
Zv1 = NI.normICDF(U1);
V1[t, k] = a1 * (b1 + Zv1) * (b1 + Zv1);
}
else if (phi1 >= 0.5)
{
if (U1 <= p1)
{
V1[t, k] = 0.0;
}
else if (U1 > p1)
{
beta1 = (1.0 - p1) / m1;
V1[t, k] = Math.Log((1.0 - p1) / (1 - U1)) / beta1;
}
}
m2 = theta2 + (V2[t - 1, k] - theta2) * Math.Exp(-kappa2 * dt);
s2 = V2[t - 1, k] * sigma2 *sigma2 *Math.Exp(-kappa2 *dt) / kappa2 * (1.0 - Math.Exp(-kappa2 * dt))
+ theta2 * sigma2 * sigma2 / 2.0 / kappa2 * Math.Pow(1.0 - Math.Exp(-kappa2 * dt), 2.0);
phi2 = s2 / (m2 * m2);
p2 = (phi2 - 1.0) / (phi2 + 1.0);
U2 = RN.RandomNum(0.0, 1.0);
if (phi2 < 0.5)
{
b2 = Math.Sqrt(2.0 / phi2 - 1.0 + Math.Sqrt(2.0 / phi2 * (2.0 / phi2 - 1.0)));
a2 = m2 / (1.0 + b2 * b2);
Zv2 = NI.normICDF(U2);
V2[t, k] = a2 * (b2 + Zv2) * (b2 + Zv2);
}
else if (phi2 >= 0.5)
{
if (U2 <= p2)
{
V2[t, k] = 0.0;
}
else if (U2 > p2)
{
beta2 = (1.0 - p2) / m2;
V2[t, k] = Math.Log((1.0 - p2) / (1.0 - U2)) / beta2;
}
}
// Predictor-Corrector for the stock price
B1 = RN.RandomNorm();
B2 = RN.RandomNorm();
logS = Math.Log(Math.Exp(-r * Convert.ToDouble(t) * dt) * S[t - 1, k])
+ K01 + K11 * V1[t - 1, k] + K21 * V1[t, k] + Math.Sqrt(K31 * (V1[t, k] + V1[t - 1, k])) * B1
+ K02 + K12 * V2[t - 1, k] + K22 * V2[t, k] + Math.Sqrt(K32 * (V2[t, k] + V2[t - 1, k])) * B2;
S[t, k] = Math.Exp(logS) * Math.Exp(r * Convert.ToDouble(t + 1) * dt);
}
}
// Terminal stock prices
double[] ST = new double[N];
for (int k = 0; k <= N - 1; k++)
{
ST[k] = S[T - 1, k];
}
// Payoff vectors
double[] Payoff = new double[N];
for (int k = 0; k <= N - 1; k++)
{
if (PutCall == "C")
{
Payoff[k] = Math.Max(ST[k] - Strike, 0.0);
}
else if (PutCall == "P")
{
Payoff[k] = Math.Max(Strike - ST[k], 0.0);
}
}
// Simulated price
EulerAlfonsiSimulation EA = new EulerAlfonsiSimulation();
double SimPrice = Math.Exp(-r * Mat) * EA.VMean(Payoff);
return(SimPrice);
}
// Alfonsi function
public double AlfonsiV(HParam param, double vt, double dt)
{
RandomNumber RN = new RandomNumber();
double kappa = param.kappa;
double theta = param.theta;
double sigma = param.sigma;
double v0 = param.v0;
double rho = param.rho;
double phi = (1.0 - Math.Exp(-kappa * dt / 2.0)) / kappa;
double S = (sigma * sigma / 4.0 - theta * kappa);
double E = Math.Exp(kappa * dt / 2.0);
double K2 = 0.0;
double U = 0.0;
double Y = 0.0;
double newV = 0.0;
if (sigma * sigma > 4.0 * kappa * theta)
{
K2 = E * (S * phi + Math.Pow((Math.Sqrt(E * S * phi) + sigma / 2.0 * Math.Sqrt(3.0 * dt)), 2));
}
else
{
K2 = 0;
}
if (vt >= K2)
{
U = RN.RandomNum(0.0, 1.0);
if (U <= 1.0 / 6.0)
{
Y = Math.Sqrt(3.0);
}
else if (U <= 1.0 / 3.0)
{
Y = -Math.Sqrt(3.0);
}
else
{
Y = 0.0;
}
phi = (1.0 - Math.Exp(-kappa * dt / 2.0)) / kappa;
S = (theta * kappa - sigma * sigma / 4.0);
E = Math.Exp(-kappa * dt / 2.0);
newV = E * Math.Pow((Math.Sqrt(S * phi + E * vt) + sigma / 2.0 * Math.Sqrt(dt) * Y), 2) + S * phi;
}
else
{
double[] u = CIRmoments(param, vt, dt);
double u1 = u[0];
double u2 = u[1];
double Pi = 0.5 - 0.5 * Math.Sqrt(1 - u1 * u1 / u2);
U = RN.RandomNum(0.0, 1.0);
if (U <= Pi)
{
newV = u1 / 2.0 / Pi;
}
else if (U > Pi)
{
newV = u1 / 2.0 / (1.0 - Pi);
}
}
return(newV);
}
public double DHEulerAlfonsiSim(string scheme, DHParam param, double S0, double Strike, double Mat, double r, double q, int T, int N, string PutCall)
{
RandomNumber RN = new RandomNumber();
double kappa1 = param.kappa1;
double theta1 = param.theta1;
double sigma1 = param.sigma1;
double v01 = param.v01;
double rho1 = param.rho1;
double kappa2 = param.kappa2;
double theta2 = param.theta2;
double sigma2 = param.sigma2;
double v02 = param.v02;
double rho2 = param.rho2;
HParam param1;
param1.kappa = kappa1;
param1.theta = theta1;
param1.sigma = sigma1;
param1.v0 = v01;
param1.rho = rho1;
HParam param2;
param2.kappa = kappa2;
param2.theta = theta2;
param2.sigma = sigma2;
param2.v0 = v02;
param2.rho = rho2;
// Time increment
double dt = Mat / T;
// Required quantities
double K01 = -rho1 * kappa1 * theta1 * dt / sigma1;
double K11 = dt / 2.0 * (kappa1 * rho1 / sigma1 - 0.5) - rho1 / sigma1;
double K21 = dt / 2.0 * (kappa1 * rho1 / sigma1 - 0.5) + rho1 / sigma1;
double K31 = dt / 2.0 * (1.0 - rho1 * rho1);
double K02 = -rho2 * kappa2 * theta2 * dt / sigma2;
double K12 = dt / 2.0 * (kappa2 * rho2 / sigma2 - 0.5) - rho2 / sigma2;
double K22 = dt / 2.0 * (kappa2 * rho2 / sigma2 - 0.5) + rho2 / sigma2;
double K32 = dt / 2.0 * (1.0 - rho2 * rho2);
// Initialize the variance and stock processes
double[,] V1 = new double[T, N];
double[,] V2 = new double[T, N];
double[,] S = new double[T, N];
// Starting values for the variance and stock processes
for (int k = 0; k <= N - 1; k++)
{
S[0, k] = S0; // Spot price
V1[0, k] = v01; // Heston v0 initial variance
V2[0, k] = v02; // Heston v0 initial variance
}
double G1, G2, B1, B2, logS;
// Generate the stock and volatility paths
for (int k = 0; k <= N - 1; k++)
{
for (int t = 1; t <= T - 1; t++)
{
if (scheme == "Euler")
{
// Generate two in dependent N(0,1) variables
G1 = RN.RandomNorm();
G2 = RN.RandomNorm();
// Euler discretization with full truncation for the variances
V1[t, k] = V1[t - 1, k] + kappa1 * (theta1 - V1[t - 1, k]) * dt + sigma1 * Math.Sqrt(V1[t - 1, k] * dt) * G1;
V2[t, k] = V2[t - 1, k] + kappa2 * (theta2 - V2[t - 1, k]) * dt + sigma2 * Math.Sqrt(V2[t - 1, k] * dt) * G2;
V1[t, k] = Math.Max(0, V1[t, k]);
V2[t, k] = Math.Max(0, V2[t, k]);
}
else if (scheme == "Alfonsi")
{
// Alfonsi discretization
V1[t, k] = AlfonsiV(param1, V1[t - 1, k], dt);
V2[t, k] = AlfonsiV(param2, V2[t - 1, k], dt);
}
// Predictor-Corrector for the stock price
B1 = RN.RandomNorm();
B2 = RN.RandomNorm();
logS = Math.Log(Math.Exp(-r * Convert.ToDouble(t) * dt) * S[t - 1, k])
+ K01 + K11 * V1[t - 1, k] + K21 * V1[t, k] + Math.Sqrt(K31 * (V1[t, k] + V1[t - 1, k])) * B1
+ K02 + K12 * V2[t - 1, k] + K22 * V2[t, k] + Math.Sqrt(K32 * (V2[t, k] + V2[t - 1, k])) * B2;
S[t, k] = Math.Exp(logS) * Math.Exp(r * Convert.ToDouble(t + 1) * dt);
}
}
// Terminal stock prices
double[] ST = new double[N];
for (int k = 0; k <= N - 1; k++)
{
ST[k] = S[T - 1, k];
}
// Payoff vectors
double[] Payoff = new double[N];
for (int k = 0; k <= N - 1; k++)
{
if (PutCall == "C")
{
Payoff[k] = Math.Max(ST[k] - Strike, 0.0);
}
else if (PutCall == "P")
{
Payoff[k] = Math.Max(Strike - ST[k], 0.0);
}
}
// Simulated price
double SimPrice = Math.Exp(-r * Mat) * VMean(Payoff);
return(SimPrice);
}
public double DHTransVolSim(string scheme, DHParam param, double S0, double Strike, double Mat, double r, double q, int T, int N, string PutCall)
{
RandomNumber RN = new RandomNumber();
// Heston parameters
double kappa1 = param.kappa1;
double theta1 = param.theta1;
double sigma1 = param.sigma1;
double v01 = param.v01;
double rho1 = param.rho1;
double kappa2 = param.kappa2;
double theta2 = param.theta2;
double sigma2 = param.sigma2;
double v02 = param.v02;
double rho2 = param.rho2;
// Time increment
double dt = Mat / T;
// Required quantities
double K01 = -rho1 * kappa1 * theta1 * dt / sigma1;
double K11 = dt / 2.0 * (kappa1 * rho1 / sigma1 - 0.5) - rho1 / sigma1;
double K21 = dt / 2.0 * (kappa1 * rho1 / sigma1 - 0.5) + rho1 / sigma1;
double K31 = dt / 2.0 * (1.0 - rho1 * rho1);
double K02 = -rho2 * kappa2 * theta2 * dt / sigma2;
double K12 = dt / 2.0 * (kappa2 * rho2 / sigma2 - 0.5) - rho2 / sigma2;
double K22 = dt / 2.0 * (kappa2 * rho2 / sigma2 - 0.5) + rho2 / sigma2;
double K32 = dt / 2.0 * (1.0 - rho2 * rho2);
// Initialize the volatility and stock processes
double[,] w1 = new double[T, N];
double[,] w2 = new double[T, N];
double[,] S = new double[T, N];
// Starting values for the variance and stock processes
for (int k = 0; k <= N - 1; k++)
{
S[0, k] = S0; // Spot price
w1[0, k] = Math.Sqrt(v01); // Heston initial volatility
w2[0, k] = Math.Sqrt(v02);
}
// Generate the stock and volatility paths
double Zv1, m11, m12, beta1, thetav1;
double Zv2, m21, m22, beta2, thetav2;
double B1, B2, logS;
for (int k = 0; k <= N - 1; k++)
{
for (int t = 1; t <= T - 1; t++)
{
Zv1 = RN.RandomNorm();
Zv2 = RN.RandomNorm();
if (scheme == "ZhuEuler")
{
// Transformed variance scheme
w1[t, k] = w1[t - 1, k] + 0.5 * kappa1 * ((theta1 - sigma1 * sigma1 / 4.0 / kappa1) / w1[t - 1, k] - w1[t - 1, k]) * dt + 0.5 * sigma1 * Math.Sqrt(dt) * Zv1;
w2[t, k] = w2[t - 1, k] + 0.5 * kappa2 * ((theta2 - sigma2 * sigma2 / 4.0 / kappa2) / w2[t - 1, k] - w2[t - 1, k]) * dt + 0.5 * sigma2 * Math.Sqrt(dt) * Zv2;
}
else if (scheme == "ZhuTV")
{
// Zhu (2010) process for the transformed volatility
m11 = theta1 + (w1[t - 1, k] * w1[t - 1, k] - theta1) * Math.Exp(-kappa1 * dt);
m21 = theta2 + (w2[t - 1, k] * w2[t - 1, k] - theta2) * Math.Exp(-kappa2 * dt);
m12 = sigma1 * sigma1 / 4.0 / kappa1 * (1.0 - Math.Exp(-kappa1 * dt));
m22 = sigma2 * sigma2 / 4.0 / kappa2 * (1.0 - Math.Exp(-kappa2 * dt));
beta1 = Math.Sqrt(Math.Max(0, m11 - m12));
beta2 = Math.Sqrt(Math.Max(0, m21 - m22));
thetav1 = (beta1 - w1[t - 1, k] * Math.Exp(-kappa1 * dt / 2.0)) / (1.0 - Math.Exp(-kappa1 * dt / 2.0));
thetav2 = (beta2 - w2[t - 1, k] * Math.Exp(-kappa2 * dt / 2.0)) / (1.0 - Math.Exp(-kappa2 * dt / 2.0));
w1[t, k] = w1[t - 1, k] + 0.5 * kappa1 * (thetav1 - w1[t - 1, k]) * dt + 0.5 * sigma1 * Math.Sqrt(dt) * Zv1;
w2[t, k] = w2[t - 1, k] + 0.5 * kappa2 * (thetav2 - w2[t - 1, k]) * dt + 0.5 * sigma2 * Math.Sqrt(dt) * Zv2;
}
// Predictor-Corrector for the stock price
B1 = RN.RandomNorm();
B2 = RN.RandomNorm();
logS = Math.Log(Math.Exp(-r * Convert.ToDouble(t) * dt) * S[t - 1, k])
+ K01 + K11 * w1[t - 1, k] * w1[t - 1, k] + K21 * w1[t, k] * w1[t, k] + Math.Sqrt(K31 * (w1[t, k] * w1[t, k] + w1[t - 1, k] * w1[t - 1, k])) * B1
+ K02 + K12 * w2[t - 1, k] * w2[t - 1, k] + K22 * w2[t, k] * w2[t, k] + Math.Sqrt(K32 * (w2[t, k] * w2[t, k] + w2[t - 1, k] * w2[t - 1, k])) * B2;
S[t, k] = Math.Exp(logS) * Math.Exp(r * Convert.ToDouble(t + 1) * dt);
}
}
// Terminal stock prices
double[] ST = new double[N];
for (int k = 0; k <= N - 1; k++)
{
ST[k] = S[T - 1, k];
}
// Payoff vectors
double[] Payoff = new double[N];
for (int k = 0; k <= N - 1; k++)
{
if (PutCall == "C")
{
Payoff[k] = Math.Max(ST[k] - Strike, 0.0);
}
else if (PutCall == "P")
{
Payoff[k] = Math.Max(Strike - ST[k], 0.0);
}
}
// Simulated price
EulerAlfonsiSimulation EA = new EulerAlfonsiSimulation();
double SimPrice = Math.Exp(-r * Mat) * EA.VMean(Payoff);
return(SimPrice);
}