public LfmHullWhiteParameterization(
LiborForwardModelProcess process,
OptionletVolatilityStructure capletVol,
Matrix correlation, int factors)
: base(process.size(), factors)
{
diffusion_ = new Matrix(size_ - 1, factors_);
fixingTimes_ = process.fixingTimes();
Matrix sqrtCorr = new Matrix(size_ - 1, factors_, 1.0);
if (correlation.empty())
{
Utils.QL_REQUIRE(factors_ == 1, () => "correlation matrix must be given for multi factor models");
}
else
{
Utils.QL_REQUIRE(correlation.rows() == size_ - 1 &&
correlation.rows() == correlation.columns(), () => "wrong dimesion of the correlation matrix");
Utils.QL_REQUIRE(factors_ <= size_ - 1, () => "too many factors for given LFM process");
Matrix tmpSqrtCorr = MatrixUtilitites.pseudoSqrt(correlation,
MatrixUtilitites.SalvagingAlgorithm.Spectral);
// reduce to n factor model
// "Reconstructing a valid correlation matrix from invalid data"
// (<http://www.quarchome.org/correlationmatrix.pdf>)
for (int i = 0; i < size_ - 1; ++i)
{
double d = 0;
tmpSqrtCorr.row(i).GetRange(0, factors_).ForEach((ii, vv) => d += vv * tmpSqrtCorr.row(i)[ii]);
for (int k = 0; k < factors_; ++k)
{
sqrtCorr[i, k] = tmpSqrtCorr.row(i).GetRange(0, factors_)[k] / Math.Sqrt(d);
}
}
}
List <double> lambda = new List <double>();
DayCounter dayCounter = process.index().dayCounter();
List <double> fixingTimes = process.fixingTimes();
List <Date> fixingDates = process.fixingDates();
for (int i = 1; i < size_; ++i)
{
double cumVar = 0.0;
for (int j = 1; j < i; ++j)
{
cumVar += lambda[i - j - 1] * lambda[i - j - 1]
* (fixingTimes[j + 1] - fixingTimes[j]);
}
double vol = capletVol.volatility(fixingDates[i], 0.0, false);
double var = vol * vol
* capletVol.dayCounter().yearFraction(fixingDates[0],
fixingDates[i]);
lambda.Add(Math.Sqrt((var - cumVar)
/ (fixingTimes[1] - fixingTimes[0])));
for (int q = 0; q < factors_; ++q)
{
diffusion_[i - 1, q] = sqrtCorr[i - 1, q] * lambda.Last();
}
}
covariance_ = diffusion_ * Matrix.transpose(diffusion_);
}
// calculating swaption volatility matrix using
// Rebonatos approx. formula. Be aware that this
// matrix is valid only for regular fixings and
// assumes that the fix and floating leg have the
// same frequency
public SwaptionVolatilityMatrix getSwaptionVolatilityMatrix()
{
if (swaptionVola != null)
{
return(swaptionVola);
}
IborIndex index = process_.index();
Date today = process_.fixingDates()[0];
int size = process_.size() / 2;
Matrix volatilities = new Matrix(size, size);
List <Date> exercises = new InitializedList <Date>(size);
for (int i = 0; i < size; ++i)
{
exercises[i] = process_.fixingDates()[i + 1];
}
List <Period> lengths = new InitializedList <Period>(size);
for (int i = 0; i < size; ++i)
{
lengths[i] = (i + 1) * index.tenor();
}
Vector f = process_.initialValues();
for (int k = 0; k < size; ++k)
{
int alpha = k;
double t_alpha = process_.fixingTimes()[alpha + 1];
Matrix var = new Matrix(size, size);
for (int i = alpha + 1; i <= k + size; ++i)
{
for (int j = i; j <= k + size; ++j)
{
var[i - alpha - 1, j - alpha - 1] = var[j - alpha - 1, i - alpha - 1] =
covarProxy_.integratedCovariance(i, j, t_alpha, null);
}
}
for (int l = 1; l <= size; ++l)
{
int beta = l + k;
Vector w = w_0(alpha, beta);
double sum = 0.0;
for (int i = alpha + 1; i <= beta; ++i)
{
for (int j = alpha + 1; j <= beta; ++j)
{
sum += w[i] * w[j] * f[i] * f[j] * var[i - alpha - 1, j - alpha - 1];
}
}
volatilities[k, l - 1] =
Math.Sqrt(sum / t_alpha) / S_0(alpha, beta);
}
}
return(swaptionVola = new SwaptionVolatilityMatrix(today, exercises, lengths,
volatilities, index.dayCounter()));
}