/// <summary>
/// override the <method>DipathByAntitheticMethod</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point
/// </summary>
public double[][] DipathByAntitheticMethod(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps, bool visualizationFlag = false, Form1 form = null)
{
double[][] pricePath = new double[2][];
pricePath[0] = new double[timeSteps + 1];
pricePath[1] = new double[timeSteps + 1];
StochasticAssetPrice S2 = new StochasticAssetPrice(S);
double dt = totalTime / (double)timeSteps;
pricePath[0][0] = S.CurrentPrice;
pricePath[1][0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
double z2 = -z;
pricePath[0][i] = GetNextPrice(S, dt, z);
pricePath[1][i] = GetNextPrice(S2, dt, z2);
}
if (visualizationFlag & form != null)
{
double[] X = new double[timeSteps + 1];
for (int i = 0; i <= timeSteps; i++)
{
X[i] = i;
}
form.add(X, pricePath[0], "");
form.add(X, pricePath[1], "");
}
return(pricePath);
}
/// <summary>
/// override the <method>GeneratingRandomPricePath</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point.
/// </summary>
public double[] GeneratingRandomPricePath(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps)
{
double[] pricePath = new double[timeSteps + 1];
double dt = totalTime / (double)timeSteps;
pricePath[0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
pricePath[i] = GetNextPrice(S, dt, z);
}
return(pricePath);
}
/// <summary>
/// override the <method>DipathByAntitheticMethod</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point
/// </summary>
public double[][] DipathByAntitheticMethod(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps)
{
double[][] pricePath = new double[2][];
pricePath[0] = new double[timeSteps + 1];
pricePath[1] = new double[timeSteps + 1];
StochasticAssetPrice S2 = new StochasticAssetPrice(S);
double dt = totalTime / (double)timeSteps;
pricePath[0][0] = S.CurrentPrice;
pricePath[1][0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
double z2 = -z;
pricePath[0][i] = GetNextPrice(S, dt, z);
pricePath[1][i] = GetNextPrice(S2, dt, z2);
}
return pricePath;
}
/// <summary>
/// override the <method>DipathByAntitheticMethod</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point
/// </summary>
public double[][] DipathByAntitheticMethod(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps)
{
double[][] pricePath = new double[2][];
pricePath[0] = new double[timeSteps + 1];
pricePath[1] = new double[timeSteps + 1];
StochasticAssetPrice S2 = new StochasticAssetPrice(S);
double dt = totalTime / (double)timeSteps;
pricePath[0][0] = S.CurrentPrice;
pricePath[1][0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
double z2 = -z;
pricePath[0][i] = GetNextPrice(S, dt, z);
pricePath[1][i] = GetNextPrice(S2, dt, z2);
}
return(pricePath);
}
/// <summary>
/// override the <method>GeneratingRandomPricePath</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point.
/// </summary>
public double[] GeneratingRandomPricePath(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps, bool visualizationFlag = false, Form1 form = null)
{
double[] pricePath = new double[timeSteps + 1];
double dt = totalTime / (double)timeSteps;
pricePath[0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
pricePath[i] = GetNextPrice(S, dt, z);
}
if (visualizationFlag & form != null)
{
double[] X = new double[timeSteps + 1];
for (int i = 0; i <= timeSteps; i++)
{
X[i] = i;
}
form.add(X, pricePath, "");
}
return(pricePath);
}
/// <summary>
/// override the <method>DipathByAntitheticMethod</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point
/// </summary>
public double[][] DipathByAntitheticMethod(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps, bool visualizationFlag = false, Form1 form = null)
{
double[][] pricePath = new double[2][];
pricePath[0] = new double[timeSteps + 1];
pricePath[1] = new double[timeSteps + 1];
StochasticAssetPrice S2 = new StochasticAssetPrice(S);
double dt = totalTime / (double)timeSteps;
pricePath[0][0] = S.CurrentPrice;
pricePath[1][0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
double z2 = -z;
pricePath[0][i] = GetNextPrice(S, dt, z);
pricePath[1][i] = GetNextPrice(S2, dt, z2);
}
if (visualizationFlag & form != null)
{
double[] X = new double[timeSteps + 1];
for (int i = 0; i <= timeSteps; i++)
{
X[i] = i;
}
form.add(X, pricePath[0], "");
form.add(X, pricePath[1], "");
}
return pricePath;
}
/// <summary>
/// override the <method>GeneratingRandomPricePath</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point.
/// </summary>
public double[] GeneratingRandomPricePath(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps, bool visualizationFlag = false, Form1 form = null)
{
double[] pricePath = new double[timeSteps + 1];
double dt = totalTime / (double)timeSteps;
pricePath[0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
pricePath[i] = GetNextPrice(S, dt, z);
}
if (visualizationFlag & form != null)
{
double[] X = new double[timeSteps + 1];
for (int i = 0; i <= timeSteps; i++)
{
X[i] = i;
}
form.add(X, pricePath, "");
}
return pricePath;
}
/// <summary>
/// override the <method>GeneratingRandomPricePath</method>.
/// For Black Scholes model, mu and sigma is constant, and only one random
/// variate is needed to generate the state for next point.
/// </summary>
public double[] GeneratingRandomPricePath(StochasticAssetPrice S, GaussianGenerator nrandom,
double totalTime, int timeSteps)
{
double[] pricePath = new double[timeSteps + 1];
double dt = totalTime / (double)timeSteps;
pricePath[0] = S.CurrentPrice;
for (int i = 1; i <= timeSteps; i++)
{
double z = nrandom.NextGaussian();
pricePath[i] = GetNextPrice(S, dt, z);
}
return pricePath;
}
