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; }