| public Estimate ( List | ||
| data | List | /// The data to be used in order to perform the optimization. /// |
| settings | IEstimationSettings | The parameter is not used. |
| controller | IController | |
| properties | object>.Dictionary | |
| return | EstimationResult | |
private static Vector Test(int nm, int nk, double q, double s0, double r, double t, double theta, double sigma, double nu)
{
// Simulate synthetic data.
Vector m = new Vector(nm);
Vector k = new Vector(nk);
Matrix cp = new Matrix(nm, nk);
Random rand = new Random();
for (int i = 0; i < nm; i++)
{
m[i] = 0.01 + rand.NextDouble() * 0.99;
}
for (int i = 0; i < nk; i++)
{
k[i] = 60 + rand.NextDouble() * 90;
}
for (int i = 0; i < nm; i++)
{
for (int j = 0; j < nk; j++)
{
cp[i, j] = VarianceGammaOptionsCalibration.VGCall(theta, sigma, nu, m[i], k[j], q, s0, r);
}
}
Console.WriteLine("Benchmark value");
Console.WriteLine(new Vector()
{
theta, sigma, nu
});
Console.WriteLine("Call prices");
Console.WriteLine(cp);
// VGDiff at optimum.
double fopt = VarianceGammaOptimizationProblem.VGDiff(new Vector()
{
theta, sigma, nu
}, q, s0, k, r, cp, m);
Console.WriteLine("fopt");
Console.WriteLine(fopt);
VarianceGammaOptionsCalibration c = new VarianceGammaOptionsCalibration();
List <object> marketData = new List <object>();
var espmd = new EquitySpotMarketData();
espmd.Price = s0;
espmd.RiskFreeRate = r;
espmd.DividendYield = q;
var cpmd = new CallPriceMarketData();
cpmd.Strike = k;
cpmd.Maturity = m;
cpmd.CallPrice = cp;
var dc = new DiscountingCurveMarketData();
dc.Durations = new Vector()
{
0
};
dc.Values = new Vector()
{
r
};
marketData.Add(espmd);
marketData.Add(cpmd);
marketData.Add(dc);
EstimationResult res = c.Estimate(marketData, null);
return((Vector)res.Values);
}
private static Vector Test(int nm, int nk, double q, double s0, double r, double t, double theta, double sigma, double nu)
{
// Simulate synthetic data.
Vector m = new Vector(nm);
Vector k = new Vector(nk);
Matrix cp = new Matrix(nm, nk);
Random rand = new Random();
for (int i = 0; i < nm; i++)
{
m[i] = 0.01 + rand.NextDouble() * 0.99;
}
for (int i = 0; i < nk; i++)
{
k[i] = 60 + rand.NextDouble() * 90;
}
for (int i = 0; i < nm; i++)
{
for (int j = 0; j < nk; j++)
{
cp[i, j] = VarianceGammaOptionsCalibration.VGCall(theta, sigma, nu, m[i], k[j], q, s0, r);
}
}
Console.WriteLine("Benchmark value");
Console.WriteLine(new Vector() { theta, sigma, nu });
Console.WriteLine("Call prices");
Console.WriteLine(cp);
// VGDiff at optimum.
double fopt = VarianceGammaOptimizationProblem.VGDiff(new Vector() { theta, sigma, nu }, q, s0, k, r, cp, m);
Console.WriteLine("fopt");
Console.WriteLine(fopt);
VarianceGammaOptionsCalibration c = new VarianceGammaOptionsCalibration();
List<object> marketData = new List<object>();
EquitySpotMarketData espmd = new EquitySpotMarketData();
CallPriceMarketData cpmd = new CallPriceMarketData();
espmd.Price = s0;
espmd.RiskFreeRate = r;
espmd.DividendYield = q;
cpmd.Strike = k;
cpmd.Maturity = m;
cpmd.CallPrice = cp;
marketData.Add(espmd);
marketData.Add(cpmd);
EstimationResult res = c.Estimate(marketData, null);
return (Vector)res.Values;
}
