/// <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");
}
}
}
}
/// <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;
}
/// <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);
}
/// <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;
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);
BlackModel bm = new BlackModel(zr);
double deltak = dataset.CapTenor;
Matrix capVol = dataset.CapVolatility;
Vector capMat = dataset.CapMaturity;
Vector capK = dataset.CapRate;
var preferences = settings as Fairmat.Calibration.CapVolatilityFiltering;
// Matrix calculated with black.
Matrix 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>
/// 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");
}
}
}