public ColumnVector VIXfuture_HybridMethod(double T, Func <double, double> epsilon)
{
//Result
ColumnVector VIXFutures;
//For Exécution Time
DateTime start = DateTime.Now;
//Input:
int kappa = 2;
// the Gri t_0 ..... t_{100} = T
int n = 500;
Grid grid = new Grid(0, T, (int)Math.Abs(T * n));
int n_T = grid.get_timeNmbrStep();
n_tH = Math.Pow(n_T, H - 0.5); //optimizeMC
//The second Grid t_0=T, t_1 ..... t_N = T + Delta
int Nbstep = 20;
//Correlation :
SymmetricMatrix correl = MakeCorrel(n, grid);
SquareMatrix choleskyCorrel = correl.CholeskyDecomposition().SquareRootMatrix();
int period = 100;
VIXFutures = new ColumnVector(grid.get_timeNmbrStep() / period);
//--------------------------------------------------------------------------------------------------------------------------------------------------------------
//-----------------------------------MC----------------------------------------------------------------------------------------------------------------------
//-----------------------------------------------------------------------------------------------------------------------------------------------------------
var MCnbofSimulation = 3.0E4;
HybridScheme hybridscheme = new HybridScheme(choleskyCorrel, grid, kappa, H);
for (int mc = 1; mc <= MCnbofSimulation; mc++)
{
// 1-simulation of volterra Hybrid Scheme
ColumnVector Z;
ColumnVector volterra;
ColumnVector Z_Brownian;
hybridscheme.simulateFFT(out Z, out volterra);
//2 - extract the path of the Brownian motion Z driving the Volterra process
Z_Brownian = ExtractBrownian(kappa, n_T, Z, volterra);
//Grid secondGrid2 = new Grid(grid.t(n_T), grid.t(n_T) + Delta, 20);
//ColumnVector volterraT2 = EulerMEthode(grid, secondGrid2, n_T, volterra, Z_Brownian);
//double VIX_future_i2 = VIX_Calculate(epsilon, secondGrid2, volterraT2);
//VIXFutures[0] += VIX_future_i2;
//DateTime starttestM = DateTime.Now;
//for (int zz = 1; zz <= 1.0E4; zz++)
//{
// hybridscheme.simulateFFT(out Z, out volterra);
//}
//TimeSpan timeExecutiontestM = DateTime.Now - starttestM;
//DateTime starttest = DateTime.Now;
//for (int zz = 1; zz <= 1.0E4; zz++)
//{
// for (int i = 1; i <= volterra.Count() / period; i++)
// {
// int N_i2 = i * period;
// //3- approximate the continuous-time process V^T by the discrete-time version V^T~ defined via the forward Euler scheme
// double[] volterraT2 = EulerMEthode(grid, secondGrid, N_i2, volterra, Z_Brownian);
// //double VIX_future_i2 = VIX_Calculate(epsilon, secondGrid, volterraT2);
// //VIXFutures[i - 1] += VIX_future_i2;
// }
//}
//TimeSpan timeExecutiontest = DateTime.Now - starttest;
for (int i = 1; i <= volterra.Count() / period; i++)
{
int N_i = i * period;
Grid secondGrid = new Grid(grid.t(N_i), grid.t(N_i) + Delta, Nbstep);
//3- approximate the continuous-time process V^T by the discrete-time version V^T~ defined via the forward Euler scheme
double[] volterraT = EulerMEthode(grid, secondGrid, N_i, volterra, Z_Brownian);
double VIX_future_i = VIX_Calculate(epsilon, secondGrid, volterraT);
VIXFutures[i - 1] += VIX_future_i;
}
}// ENd of MC
//MC Mean
for (int i = 0; i < VIXFutures.Count(); i++)
{
VIXFutures[i] /= MCnbofSimulation;
}
TimeSpan timeExecution = DateTime.Now - start;
return(VIXFutures);
}
public double PriceVIXOption(VIXOption Option, Func <double, double> epsilon, double stock_0)
{
int n = 500;
double T = Option.maturity;
Grid grid = new Grid(0, T, (int)Math.Abs(T * n));
int n_T = grid.get_timeNmbrStep();
int kappa = 2;
//Correlation :
SymmetricMatrix correl = MakeCorrel(n, grid);
SquareMatrix choleskyCorrel = correl.CholeskyDecomposition().SquareRootMatrix();
double rho = 0.1;//correlation between the two Brownian
Func <double, double> payoff;
switch (Option.type)
{
case VIXOption.OptionType.Call:
payoff = S => Math.Max(S - Option.strike, 0);
break;
case VIXOption.OptionType.Put:
payoff = S => Math.Max(Option.strike - S, 0);
break;
default:
payoff = S => Math.Max(S - Option.strike, 0);
break;
}
double price = 0.0;
double McNbSimulation = 1E5;
for (int mc = 1; mc <= McNbSimulation; mc++)
{
// 1-simulation of volterra Hybrid Scheme
ColumnVector Z;
ColumnVector volterra;
//ColumnVector Z_Brownian;
HybridScheme hybridscheme = new HybridScheme(choleskyCorrel, grid, kappa, H);
hybridscheme.simulate(out Z, out volterra);
GaussianSimulator simulator = new GaussianSimulator();
//Z_Brownian = ExtractBrownian(kappa, n_T, Z, volterra);
ColumnVector Variance = new ColumnVector(n_T + 1);
Variance[0] = epsilon(grid.t(0));
for (int i = 1; i <= grid.get_timeNmbrStep(); i++)
{
Variance[i] = epsilon(grid.t(i)) * Math.Exp(2 * vi * Ch * volterra[i - 1] - Math.Pow(vi * Ch, 2) * Math.Pow(grid.t(i), 2 * H));
}
double X = Math.Log(stock_0);
for (int i = 0; i < n_T; i++)
{
double dW = (rho * Z[i] + Math.Sqrt(1 - Math.Pow(rho, 2)) * Math.Sqrt(grid.get_Step()) * simulator.Next());
X = X - 0.5 * Variance[i] * grid.get_Step() + Math.Sqrt(Variance[i]) * dW;
}
double S = Math.Exp(X);
price += payoff(S);
}
price /= McNbSimulation;
return(price);
}
