/// <summary>
/// Attempts a calibration through <see cref="SwaptionHW1OptimizationProblem"/>
/// using swaption matrices.
/// </summary>
/// <param name="data">The data to be used in order to perform the calibration.</param>
/// <param name="settings">The parameter is not used.</param>
/// <param name="controller">The controller which may be used to cancel the process.</param>
/// <returns>The results of the calibration.</returns>
public EstimationResult Estimate(List <object> data, IEstimationSettings settings = null, IController controller = null, Dictionary <string, object> properties = null)
{
LambdaCalibrationSettings lsettings = (LambdaCalibrationSettings)settings;
if (lsettings.Years > lsettings.BondMaturity)
{
throw new Exception("Bond maturity has to be greater of the historical series time span.");
}
InterestRateMarketData irmd = data[0] as InterestRateMarketData;
List <object> IrmdData = new List <object>();
IrmdData.Add(irmd);
CapletEstimator CapEst = new CapletEstimator();
EstimationResult er1 = CapEst.Estimate(IrmdData);
DiscountingCurveMarketData[] dcmd = Array.ConvertAll <IMarketData, DiscountingCurveMarketData>
((IMarketData[])data[1], el => (DiscountingCurveMarketData)el);
MarketPriceOfRiskCalculator mporc = new MarketPriceOfRiskCalculator();
double lambda = mporc.Calculate(dcmd, lsettings);
string[] names = new string[er1.Names.Length + 1];
for (int i = 0; i < er1.Names.Length; i++)
{
names[i] = er1.Names[i];
}
names[er1.Names.Length] = "lambda0";
Vector values = new Vector(er1.Values.Length + 1);
values[new Range(0, values.Length - 2)] = (Vector)er1.Values;
values[Range.End] = lambda;
EstimationResult result = new EstimationResult(names, values);
return(result);
}
/// <summary>
/// Constructor for the Cox-Ingersoll-Ross Calibration Problem based on caps matrices,
/// using an <see cref="InterestRateMarketData"/> to derive the required data.
/// </summary>
/// <param name="irmd">
/// An <see cref="InterestRateMarketData"/> containing the
/// required information for the optimization problem.
/// </param>
public CapCIROptimizationProblem(InterestRateMarketData irmd)
{
this.capMaturity = irmd.CapMaturity;
this.capRate = irmd.CapRate;
this.tau = irmd.CapTenor;
PFunction zr = new PFunction(null);
zr.m_Function.iType = DVPLUtils.EInterpolationType.LINEAR;
double[,] zrval = (double[, ])ArrayHelper.Concat(irmd.ZRMarketDates.ToArray(),
irmd.ZRMarket.ToArray());
zr.Expr = zrval;
this.r0 = zr.Evaluate(0.0);
BlackModel bm = new BlackModel(zr);
this.blackCaps = new Matrix(this.capMaturity.Length, this.capRate.Length);
for (int i = 0; i < this.capMaturity.Length; i++)
{
for (int j = 0; j < this.capRate.Length; j++)
{
if (irmd.CapVolatility[i, j] == 0)
{
this.blackCaps[i, j] = 0;
}
else
{
this.blackCaps[i, j] = bm.Cap(this.capRate[j], irmd.CapVolatility[i, j],
this.tau, this.capMaturity[i]);
}
if (double.IsNaN(this.blackCaps[i, j]))
{
throw new Exception("Error on cap market price calculation");
}
}
}
}
public void TestCalibration()
{
InterestRateMarketData IData = InterestRateMarketData.FromFile("../../TestData/IRMD-sample.xml");
CallPriceMarketData HData = CallPriceMarketData.FromFile("../../TestData/CallData-sample.xml");
//InterestRateMarketData IData = InterestRateMarketData.FromFile("../../../EquityModels.Tests/TestData/IRMD-EU-30102012-close.xml");
//CallPriceMarketData HData = CallPriceMarketData.FromFile("../../../EquityModels.Tests/TestData/30102012-SX5E_Index-HestonData.xml");
//CallPriceMarketData HData = ObjectSerialization.ReadFromXMLFile("../../../EquityModels.Tests/TestData/FTSE.xml") as CallPriceMarketData;
List <object> l = new List <object>();
l.Add(IData.DiscountingCurve);
l.Add(HData);
DupireEstimator DE = new DupireEstimator();
DupireCalibrationSettings settings = new DupireCalibrationSettings();
settings.LocalVolatilityCalculation = LocalVolatilityCalculation.Method1;
//settings.LocalVolatilityCalculation = LocalVolatilityCalculation.QuantLib;
EstimationResult res = DE.Estimate(l, settings);
//int nmat = HData.Maturity.Length;
//int nstrike = HData.Strike.Length;
int i = 5; // Maturity.
int j = 4; // Strike.
Engine.MultiThread = true;
Document doc = new Document();
ProjectROV rov = new ProjectROV(doc);
doc.Part.Add(rov);
doc.DefaultProject.NMethods.m_UseAntiteticPaths = true;
int n_sim = 10000;
int n_steps = 500;
double strike = HData.Strike[j];
//double volatility = HData.Volatility[i, j];
/*
* PFunction2D.PFunction2D impvolfunc = new PFunction2D.PFunction2D(rov);
* impvolfunc = res.Objects[3] as PFunction2D.PFunction2D;
* impvolfunc.VarName = "impvol";
* rov.Symbols.Add(impvolfunc);
* double volatility = impvolfunc.Evaluate(HData.Maturity[i], HData.Strike[j]);
*/
double volatility = 0.2;
double maturity = HData.Maturity[i];
ModelParameter Pstrike = new ModelParameter(strike, string.Empty, "strike");
rov.Symbols.Add(Pstrike);
AFunction payoff = new AFunction(rov);
payoff.VarName = "payoff";
payoff.m_IndependentVariables = 1;
payoff.m_Value = (RightValue)("max(x1 - strike ; 0)");
rov.Symbols.Add(payoff);
bool found;
double S0 = PopulateHelper.GetValue("S0", res.Names, res.Values, out found);
ModelParameter PS0 = new ModelParameter(S0, string.Empty, "S0");
rov.Symbols.Add(PS0);
PFunction rfunc = new PFunction(rov);
rfunc = res.Objects[0] as PFunction;
rfunc.VarName = "r";
rov.Symbols.Add(rfunc);
PFunction qfunc = new PFunction(rov);
qfunc = res.Objects[1] as PFunction;
qfunc.VarName = "q";
rov.Symbols.Add(qfunc);
PFunction2D.PFunction2D volfunc = new PFunction2D.PFunction2D(rov);
volfunc = res.Objects[2] as PFunction2D.PFunction2D;
volfunc.VarName = "localvol";
rov.Symbols.Add(volfunc);
DupireProcess process = new DupireProcess();
process.s0 = (ModelParameter)"S0";
process.r = (ModelParameter)"@r";
process.q = (ModelParameter)"@q";
process.localVol = (ModelParameter)"@localvol";
double rate = rfunc.Evaluate(maturity);
double dy = qfunc.Evaluate(maturity);
StochasticProcessExtendible s = new StochasticProcessExtendible(rov, process);
rov.Processes.AddProcess(s);
// Set the discounting.
RiskFreeInfo rfi = rov.GetDiscountingModel() as RiskFreeInfo;
rfi.ActualizationType = EActualizationType.RiskFree;
rfi.m_deterministicRF = rate;
OptionTree op = new OptionTree(rov);
op.PayoffInfo.PayoffExpression = "payoff(v1)";
op.PayoffInfo.Timing.EndingTime.m_Value = (RightValue)maturity;
op.PayoffInfo.European = true;
rov.Map.Root = op;
rov.NMethods.Technology = ETechType.T_SIMULATION;
rov.NMethods.PathsNumber = n_sim;
rov.NMethods.SimulationSteps = n_steps;
ROVSolver solver = new ROVSolver();
solver.BindToProject(rov);
solver.DoValuation(-1);
if (rov.HasErrors)
{
rov.DisplayErrors();
}
Assert.IsFalse(rov.HasErrors);
ResultItem price = rov.m_ResultList[0] as ResultItem;
double samplePrice = price.value;
double sampleDevSt = price.stdDev / Math.Sqrt((double)n_sim);
Console.WriteLine("Surf = " + volfunc.Expr);
// Calculation of the theoretical value of the call.
double theoreticalPrice = BlackScholes.Call(rate, S0, strike, volatility, maturity, dy);
Console.WriteLine("Theoretical Price = " + theoreticalPrice.ToString());
Console.WriteLine("Monte Carlo Price = " + samplePrice);
Console.WriteLine("Standard Deviation = " + sampleDevSt.ToString());
double tol = 4.0 * sampleDevSt;
doc.WriteToXMLFile("Dupire.fair");
Assert.LessOrEqual(Math.Abs(theoreticalPrice - samplePrice), tol);
}
/// <summary>
/// Attempts a calibration through <see cref="PelsserCappletOptimizationProblem"/>
/// using caps matrices.
/// </summary>
/// <param name="data">The data to be used in order to perform the calibration.</param>
/// <param name="settings">The parameter is not used.</param>
/// <param name="controller">The controller which may be used to cancel the process.</param>
/// <returns>The results of the calibration.</returns>
public EstimationResult Estimate(List <object> data, IEstimationSettings settings = null, IController controller = null, Dictionary <string, object> properties = null)
{
InterestRateMarketData dataset = data[0] as InterestRateMarketData;
MatrixMarketData normalVol = null;
if (data.Count > 1)
{
normalVol = (MatrixMarketData)data[1];
}
EstimationResult result;
if ((dataset.ZRMarket == null) || (dataset.CapVolatility == null))
{
result = new EstimationResult();
result.ErrorMessage = "Not enough data to calibrate.\n" +
"The estimator needs a ZRMarket and a CapVolatility " +
"defined inside InterestRateMarketData";
return(result);
}
// Backup the dates
DateTime effectiveDate = DateTime.Now.Date;
DateTime valuationDate = DateTime.Now.Date;
if (Document.ActiveDocument != null)
{
effectiveDate = Document.ActiveDocument.ContractDate;
valuationDate = Document.ActiveDocument.SimulationStartDate;
}
// Creates the Context.
Document doc = new Document();
ProjectROV prj = new ProjectROV(doc);
doc.Part.Add(prj);
Function zr = new PFunction(null);
zr.VarName = "zr";
// Load the zr.
double[,] zrvalue = (double[, ])ArrayHelper.Concat(dataset.ZRMarketDates.ToArray(), dataset.ZRMarket.ToArray());
zr.Expr = zrvalue;
prj.Symbols.Add(zr);
var bm = BlackModelFactory(zr);
if (bm is BachelierNormalModel)
{
(bm as BachelierNormalModel).Tenor = dataset.CapTenor;
}
double deltak = dataset.CapTenor;
Matrix capVol = normalVol != null ? normalVol.Values:dataset.CapVolatility;
Vector capMat = normalVol != null ? normalVol.RowValues: dataset.CapMaturity;
Vector capK = normalVol != null ? normalVol.ColumnValues: dataset.CapRate;
var preferences = settings as Fairmat.Calibration.CapVolatilityFiltering;
// Matrix calculated with black.
var blackCaps = new Matrix(capMat.Length, capK.Length);
for (int m = 0; m < capMat.Length; m++)
{
for (int s = 0; s < capK.Length; s++)
{
bool skip = false;
if (preferences != null)
{
if (capK[s] < preferences.MinCapRate || capK[s] > preferences.MaxCapRate ||
capMat[m] < preferences.MinCapMaturity || capMat[m] > preferences.MaxCapMaturity)
{
skip = true;
}
}
if (capVol[m, s] == 0 || skip)
{
blackCaps[m, s] = 0;
}
else
{
blackCaps[m, s] = bm.Cap(capK[s], capVol[m, s], deltak, capMat[m]);
}
}
}
if (blackCaps.IsNaN())
{
Console.WriteLine("Black caps matrix has non real values:");
Console.WriteLine(blackCaps);
throw new Exception("Cannot calculate Black caps");
}
// Maturity goes from 0 to the last item with step deltaK.
Vector maturity = new Vector((int)(1.0 + capMat[capMat.Length - 1] / deltak));
for (int l = 0; l < maturity.Length; l++)
{
maturity[l] = deltak * l;
}
Vector fwd = new Vector(maturity.Length - 1);
for (int i = 0; i < fwd.Length; i++)
{
fwd[i] = bm.Fk(maturity[i + 1], deltak);
}
// Creates a default Pelsser model.
Pelsser.SquaredGaussianModel model = new Pelsser.SquaredGaussianModel();
model.a1 = (ModelParameter)0.014;
model.sigma1 = (ModelParameter)0.001;
model.zr = (ModelParameter)"@zr";
StochasticProcessExtendible iex = new StochasticProcessExtendible(prj, model);
prj.Processes.AddProcess(iex);
prj.Parse();
DateTime t0 = DateTime.Now;
Caplet cp = new Caplet();
PelsserCappletOptimizationProblem problem = new PelsserCappletOptimizationProblem(prj, cp, maturity, fwd, capK, deltak, capMat, blackCaps);
IOptimizationAlgorithm solver = new QADE();
IOptimizationAlgorithm solver2 = new SteepestDescent();
DESettings o = new DESettings();
o.NP = 35;
o.TargetCost = 0.0025;
o.MaxIter = 10;
o.Verbosity = Math.Max(1, Engine.Verbose);
o.controller = controller;
// Parallel evaluation is not supported for this calibration.
o.Parallel = false;
o.Debug = true;
SolutionInfo solution = null;
Vector x0 = (Vector) new double[] { 0.1, 0.1 };
solution = solver.Minimize(problem, o, x0);
if (solution.errors)
{
return(new EstimationResult(solution.message));
}
o.epsilon = 10e-7;
o.h = 10e-7;
o.MaxIter = 1000;
o.Debug = true;
o.Verbosity = Math.Max(1, Engine.Verbose);
if (solution != null)
{
solution = solver2.Minimize(problem, o, solution.x);
}
else
{
solution = solver2.Minimize(problem, o, x0);
}
if (solution.errors)
{
return(new EstimationResult(solution.message));
}
Console.WriteLine(solution);
string[] names = new string[] { "alpha1", "sigma1" };
result = new EstimationResult(names, solution.x);
result.ZRX = (double[])dataset.ZRMarketDates.ToArray();
result.ZRY = (double[])dataset.ZRMarket.ToArray();
result.Objects = new object[1];
result.Objects[0] = solution.obj;
//result.Fit = solution.obj;//Uncomment in 1.6
// Restore the dates
if (Document.ActiveDocument != null)
{
Document.ActiveDocument.ContractDate = effectiveDate;
Document.ActiveDocument.SimulationStartDate = valuationDate;
}
return(result);
}
/// <summary>
/// Attempts a calibration through <see cref="SwaptionHW1OptimizationProblem"/>
/// using swaption matrices.
/// </summary>
/// <param name="data">The data to be used in order to perform the calibration.</param>
/// <param name="settings">The parameter is not used.</param>
/// <param name="controller">The controller which may be used to cancel the process.</param>
/// <returns>The results of the calibration.</returns>
public EstimationResult Estimate(List <object> data, IEstimationSettings settings = null, IController controller = null, Dictionary <string, object> properties = null)
{
InterestRateMarketData dataset = data[0] as InterestRateMarketData;
MatrixMarketData normalVol = null;
if (data.Count > 1)
{
normalVol = (MatrixMarketData)data[1];
}
PFunction zr = new PFunction(null);
// Loads the zero rate.
double[,] zrvalue = (double[, ])ArrayHelper.Concat(dataset.ZRMarketDates.ToArray(), dataset.ZRMarket.ToArray());
zr.Expr = zrvalue;
double deltak = dataset.SwaptionTenor;
Console.WriteLine("Swaption Tenor\t" + dataset.SwaptionTenor);
var swaptionsFiltering = settings as SwaptionsFiltering;
if (swaptionsFiltering == null)
{
swaptionsFiltering = new SwaptionsFiltering();//creates a default
}
//F stands for Full matrix
var optionMaturityF = normalVol != null ? normalVol.RowValues: dataset.OptionMaturity;
var swapDurationF = normalVol != null ? normalVol.ColumnValues: dataset.SwapDuration;
var swaptionsVolatilityF = normalVol != null ? normalVol.Values: dataset.SwaptionsVolatility;
int maturitiesCount = optionMaturityF.Count(x => x >= swaptionsFiltering.MinSwaptionMaturity && x <= swaptionsFiltering.MaxSwaptionMaturity);
int durationsCount = swapDurationF.Count(x => x >= swaptionsFiltering.MinSwapDuration && x <= swaptionsFiltering.MaxSwapDuration);
Console.WriteLine(string.Format("Calibrating on {0} swaptions prices [#maturiries x #durations]=[{1} x {2}]", maturitiesCount * durationsCount, maturitiesCount, durationsCount));
if (maturitiesCount * durationsCount == 0)
{
return(new EstimationResult("No swaptions satisfying criteria found, please relax filters"));
}
//reduced version
var swaptionsVolatility = new Matrix(maturitiesCount, durationsCount); // dataset.SwaptionsVolatility;
var optionMaturity = new Vector(maturitiesCount); // dataset.OptionMaturity;
var swapDuration = new Vector(durationsCount); // dataset.SwapDuration;
//Build filtered matrix and vectors
int fm = 0;
for (int m = 0; m < optionMaturityF.Length; m++)
{
int fd = 0;
if (optionMaturityF[m] >= swaptionsFiltering.MinSwaptionMaturity && optionMaturityF[m] <= swaptionsFiltering.MaxSwaptionMaturity)
{
for (int d = 0; d < swapDurationF.Length; d++)
{
if (swapDurationF[d] >= swaptionsFiltering.MinSwapDuration && swapDurationF[d] <= swaptionsFiltering.MaxSwapDuration)
{
swaptionsVolatility[fm, fd] = swaptionsVolatilityF[m, d];
swapDuration[fd] = swapDurationF[d];
fd++;
}
}
optionMaturity[fm] = optionMaturityF[m];
fm++;
}
}
var swbm = new SwaptionsBlackModel(zr, BlackModelFactory(zr));
Matrix fsr;
var blackSwaptionPrice = 1000.0 * swbm.SwaptionsSurfBM(optionMaturity, swapDuration, swaptionsVolatility, deltak, out fsr);
Console.WriteLine("Maturities\t" + optionMaturity);
Console.WriteLine("swapDuration\t" + swapDuration);
Console.WriteLine("SwaptionHWEstimator: Black model prices");
Console.WriteLine(blackSwaptionPrice);
SwaptionHW1 swhw1 = new SwaptionHW1(zr);
SwaptionHW1OptimizationProblem problem = new SwaptionHW1OptimizationProblem(swhw1, blackSwaptionPrice, optionMaturity, swapDuration, deltak);
IOptimizationAlgorithm solver = new QADE();
IOptimizationAlgorithm solver2 = new SteepestDescent();
DESettings o = new DESettings();
o.NP = 20;
o.MaxIter = 5;
o.Verbosity = 1;
o.controller = controller;
SolutionInfo solution = null;
Vector x0 = new Vector(new double[] { 0.1, 0.1 });
solution = solver.Minimize(problem, o, x0);
if (solution.errors)
{
return(new EstimationResult(solution.message));
}
o.epsilon = 10e-8;
o.h = 10e-8;
o.MaxIter = 1000;
// We can permit this, given it is fast.
o.accourate_numerical_derivatives = true;
if (solution != null)
{
solution = solver2.Minimize(problem, o, solution.x);
}
else
{
solution = solver2.Minimize(problem, o, x0);
}
if (solution.errors)
{
return(new EstimationResult(solution.message));
}
Console.WriteLine("Solution:");
Console.WriteLine(solution);
string[] names = new string[] { "Alpha", "Sigma" };
Console.WriteLine("SwaptionHWEstimator: hw model prices and error");
problem.Obj(solution.x, true);
EstimationResult result = new EstimationResult(names, solution.x);
result.ZRX = (double[])dataset.ZRMarketDates.ToArray();
result.ZRY = (double[])dataset.ZRMarket.ToArray();
double obj = problem.Obj(solution.x);
return(result);
}
/// <summary>
/// Attempts a calibration through <see cref="CapsHW1OptimizationProblem"/>
/// using caps matrices.
/// </summary>
/// <param name="data">The data to be used in order to perform the calibration.</param>
/// <param name="settings">The parameter is not used.</param>
/// <param name="controller">The controller which may be used to cancel the process.</param>
/// <returns>The results of the calibration.</returns>
public EstimationResult Estimate(List <object> data, IEstimationSettings settings = null, IController controller = null, Dictionary <string, object> properties = null)
{
InterestRateMarketData dataset = data[0] as InterestRateMarketData;
PFunction zr = new PFunction(null);
zr.VarName = "zr";
var preferences = settings as Fairmat.Calibration.CapVolatilityFiltering;
// Loads ZR
double[,] zrvalue = (double[, ])ArrayHelper.Concat(dataset.ZRMarketDates.ToArray(), dataset.ZRMarket.ToArray());
zr.Expr = zrvalue;
BlackModel bm = new BlackModel(zr);
double deltak = dataset.CapTenor;
if (dataset.CapVolatility == null)
{
return(new EstimationResult("Cap not available at requested date"));
}
Matrix capVolatility = dataset.CapVolatility;
Vector capMaturity = dataset.CapMaturity;
Vector capRate = dataset.CapRate;
double a = 0.1;
double sigma = 0.1;
// Matrix calculated with Black.
Matrix blackCaps = new Matrix(capMaturity.Length, capRate.Length);
Matrix logic = new Matrix(capMaturity.Length, capRate.Length);
for (int m = 0; m < capMaturity.Length; m++)
{
for (int s = 0; s < capRate.Length; s++)
{
blackCaps[m, s] = bm.Cap(capRate[s], capVolatility[m, s], deltak, capMaturity[m]);
if (double.IsNaN(blackCaps[m, s]))
{
bm.Cap(capRate[s], capVolatility[m, s], deltak, capMaturity[m]);
throw new Exception("Malformed black caps");
}
if (blackCaps[m, s] == 0.0)
{
logic[m, s] = 0.0;
}
else
{
logic[m, s] = 1.0;
}
//filter
if (preferences != null)
{
if (capRate[s] < preferences.MinCapRate || capRate[s] > preferences.MaxCapRate ||
capMaturity[m] < preferences.MinCapMaturity || capMaturity[m] > preferences.MaxCapMaturity)
{
logic[m, s] = 0; blackCaps[m, s] = 0;
}
}
}
}
DateTime t0 = DateTime.Now;
CapHW1 hw1Caps = new CapHW1(zr);
Matrix caps = hw1Caps.HWMatrixCaps(capMaturity, capRate, a, sigma, deltak);
for (int m = 0; m < capMaturity.Length; m++)
{
for (int s = 0; s < capRate.Length; s++)
{
caps[m, s] = logic[m, s] * caps[m, s];
}
}
CapsHW1OptimizationProblem problem = new CapsHW1OptimizationProblem(hw1Caps, blackCaps, capMaturity, capRate, deltak);
Vector provaparam = new Vector(2);
var solver = new QADE();
IOptimizationAlgorithm solver2 = new SteepestDescent();
DESettings o = new DESettings();
o.NP = 20;
o.MaxIter = 10;
o.Verbosity = 1;
o.Parallel = false;
SolutionInfo solution = null;
Vector x0 = new Vector(new double[] { 0.05, 0.01 });
o.controller = controller;
solution = solver.Minimize(problem, o, x0);
o.epsilon = 10e-8;
o.h = 10e-8;
o.MaxIter = 100;
solution = solver2.Minimize(problem, o, solution.x);
if (solution.errors)
{
return(new EstimationResult(solution.message));
}
Console.WriteLine("Solution:");
Console.WriteLine(solution);
string[] names = new string[] { "Alpha", "Sigma" };
//solution.x[0] *= 3;
EstimationResult result = new EstimationResult(names, solution.x);
result.ZRX = (double[])dataset.ZRMarketDates.ToArray();
result.ZRY = (double[])dataset.ZRMarket.ToArray();
return(result);
}
public static void Main(string[] args)
{
int Caso = 1;
if (Caso == 0)
{
InterestRateMarketData MData = InterestRateMarketData.FromFile("../../../TestData/InterestRatesModels/05052009-EU.xml");
CallPriceMarketData test = CallPriceMarketData.FromFile("../../../TestData/Heston/05052009-SX5E-HestonData.xml");
EquityCalibrationData CalData = new EquityCalibrationData(test, MData);
Matrix CallMarketPrice = (Matrix)test.CallPrice;
Vector Maturity = (Vector)test.Maturity;
Vector Strike = (Vector)test.Strike;
Vector DividendYield = (Vector)test.DividendYield;
Vector Drift = CalData.Rate - CalData.DividendYield;
Vector Rate = CalData.Rate;
double u, kappa, theta, sigma, rho, v0, s0, r, q, T, K, val;
u = 1.0;
kappa = 19.4;
theta = 0.235;
sigma = 0.00500999;
rho = -0.96;
v0 = 0.664;
s0 = 3872.15;
r = -0.0867303549580581;
q = 0;
T = 0.50;
K = 6000;
Vector MatBound = new Vector(2);
Vector StrikeBound = new Vector(2);
MatBound[0] = 0.0;
MatBound[1] = 2.0;
StrikeBound[0] = 0.7;
StrikeBound[1] = 1.3;
Matrix Volatility = new Matrix(test.CallPrice.R, test.CallPrice.C);
HestonCallOptimizationProblem HP = new HestonCallOptimizationProblem(CallMarketPrice, Maturity, Strike, Rate, DividendYield, test.S0, MatBound, StrikeBound, Volatility);
Complex Cval, Cu;
Cu = u - Complex.I;
HestonCall hc = new HestonCall(HP);
Cval = hc.phi(u, kappa, theta, sigma, rho, s0, v0, r, T);
Console.WriteLine("phi1 = {0}", Cval);
Cval = hc.phi(Cu, kappa, theta, sigma, rho, s0, v0, r, T);
Console.WriteLine("phi2 = {0}", Cval);
val = hc.IntegrandFunc(u, kappa, theta, sigma, rho, s0, v0, r, q, T, K);
Console.WriteLine("IntFunc = {0}", val);
Vector x = new Vector(5);
x[0] = kappa;
x[1] = theta;
x[2] = sigma;
x[3] = rho;
x[4] = v0;
DateTime T1, T2;
TimeSpan ElapsedTime;
double Time, Time2, Time3;
T1 = DateTime.Now;
val = hc.HestonCallPrice(x, s0, T, K, r, q);
T2 = DateTime.Now;
ElapsedTime = T2 - T1;
Time = (double)ElapsedTime.Milliseconds;
Time2 = (double)ElapsedTime.Seconds;
Console.WriteLine("Price = {0}", val);
Console.WriteLine("Elapsed Time = {0}", Time2 + Time / 1000);
int NProve = 10;
int NPassi = 1000;
double val2;
Random CasNum = new Random();
for (int i = 0; i < NProve; i++)
{
for (int j = 0; j < 5; j++)
{
val2 = ((double)CasNum.Next(0, NPassi)) / ((double)NPassi);
x[j] = HP.Bounds.Lb[j] + (HP.Bounds.Ub[j] - HP.Bounds.Lb[j]) * val2;
}
Console.Write("Trial {0} x = " + x.ToString(), i + 1);
T1 = DateTime.Now;
val = HP.Obj(x);
T2 = DateTime.Now;
ElapsedTime = T2 - T1;
Time = (double)ElapsedTime.Milliseconds;
Time2 = (double)ElapsedTime.Seconds;
Time3 = (double)ElapsedTime.Minutes;
Console.WriteLine(" Time = {0}' {1}'' Val = {2}", Time3, Time2 + Time / 1000, val);
}
}
if (Caso == 1)
{
TestHestonCallEstimation NewTest = new TestHestonCallEstimation();
bool Result = NewTest.Run();
}
}
/// <summary>
/// Attempts a calibration through <see cref="CapsCIROptimizationProblem"/>
/// using caps matrices.
/// </summary>
/// <param name="data">The data to be used in order to perform the calibration.</param>
/// <param name="settings">The parameter is not used.</param>
/// <param name="controller">A controller used for the optimization process.</param>
/// <returns>The results of the calibration.</returns>
public EstimationResult Estimate(List <object> data, IEstimationSettings settings = null, IController controller = null, Dictionary <string, object> properties = null)
{
InterestRateMarketData dataset = data[0] as InterestRateMarketData;
// Creates the context.
Document doc = new Document();
ProjectROV prj = new ProjectROV(doc);
doc.Part.Add(prj);
CapCIROptimizationProblem problem = new CapCIROptimizationProblem(dataset);
IOptimizationAlgorithm solver = new QADE();
IOptimizationAlgorithm solver2 = new SteepestDescent();
DESettings o = new DESettings();
o.NP = 50;
o.MaxIter = 50;
o.Verbosity = 1;
o.Parallel = false;
o.controller = controller;
SolutionInfo solution = null;
Vector x0 = new Vector(new double[] { 1, 0.01, 0.05 });
solution = solver.Minimize(problem, o, x0);
if (solution.errors)
{
return(new EstimationResult(solution.message));
}
o.epsilon = 10e-10;
o.h = 10e-10;
o.MaxIter = 1000;
if (solution != null)
{
solution = solver2.Minimize(problem, o, solution.x);
}
else
{
solution = solver2.Minimize(problem, o, x0);
}
if (solution.errors)
{
return(new EstimationResult(solution.message));
}
Console.WriteLine("Solution:");
Console.WriteLine(solution);
string[] names = CIR.parameterNames;
Vector values = new Vector(4);
values[Range.New(0, 2)] = solution.x;
values[3] = problem.r0;
EstimationResult result = new EstimationResult(names, values);
return(result);
}
/// <summary>
/// Constructor for the Cox-Ingersoll-Ross Calibration Problem based on caps matrices,
/// using an <see cref="InterestRateMarketData"/> to derive the required data.
/// </summary>
/// <param name="irmd">
/// An <see cref="InterestRateMarketData"/> containing the
/// required information for the optimization problem.
/// </param>
public CapCIROptimizationProblem(InterestRateMarketData irmd)
{
this.capMaturity = irmd.CapMaturity;
this.capRate = irmd.CapRate;
this.tau = irmd.CapTenor;
PFunction zr = new PFunction(null);
zr.m_Function.iType = DVPLUtils.EInterpolationType.LINEAR;
double[,] zrval = (double[,])ArrayHelper.Concat(irmd.ZRMarketDates.ToArray(),
irmd.ZRMarket.ToArray());
zr.Expr = zrval;
this.r0 = zr.Evaluate(0.0);
BlackModel bm = new BlackModel(zr);
this.blackCaps = new Matrix(this.capMaturity.Length, this.capRate.Length);
for (int i = 0; i < this.capMaturity.Length; i++)
{
for (int j = 0; j < this.capRate.Length; j++)
{
if (irmd.CapVolatility[i, j] == 0)
this.blackCaps[i, j] = 0;
else
this.blackCaps[i, j] = bm.Cap(this.capRate[j], irmd.CapVolatility[i, j],
this.tau, this.capMaturity[i]);
if (double.IsNaN(this.blackCaps[i, j]))
throw new Exception("Error on cap market price calculation");
}
}
}
