/// <summary>
/// Returns the Strike vector embedded in the volatility matrix.
/// The method manage the convention that if rates/strikes [defined in .ColumnValues fields] are equal to -1,
/// the strike vector is ATM and must be derived from the term structure.
/// </summary>
/// <param name="normalVol">The matrix</param>
/// <param name="zr">The term structure.</param>
/// <returns>The strike vector.</returns>
static Vector GetStrikes(MatrixMarketData normalVol, IFunction zr)
{
if (IsAtmMatrix(normalVol))
{
// builds the vector of ATM strikes
var s = new Vector(normalVol.RowValues.Length);
for (int j = 0; j < s.Length; j++)
{
s[j] = zr.Evaluate(normalVol.RowValues[j]);
}
return(s);
}
else
{
return(normalVol.ColumnValues);
}
}
/// <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);
}
private static bool IsAtmMatrix(MatrixMarketData normalVol)
{
return(normalVol != null &&
normalVol.ColumnValues.Length == 1 &&
normalVol.ColumnValues[0] == -1);
}
