public override void setParams(Vector parameters)
{
base.setParams(parameters);
int k = covarProxy_.volatilityModel().parameters().Count;
covarProxy_.volatilityModel().setParams(new List <Parameter>(arguments_.GetRange(0, k)));
covarProxy_.correlationModel().setParams(new List <Parameter>(arguments_.GetRange(k, arguments_.Count - k)));
swaptionVola = null;
}
public override void calculate()
{
Utils.QL_REQUIRE(arguments_.settlementMethod != Settlement.Method.ParYieldCurve, () =>
"cash-settled (ParYieldCurve) swaptions not priced with Lfm engine");
VanillaSwap swap = arguments_.swap;
IPricingEngine pe = new DiscountingSwapEngine(discountCurve_);
swap.setPricingEngine(pe);
double correction = swap.spread *
Math.Abs(swap.floatingLegBPS() / swap.fixedLegBPS());
double fixedRate = swap.fixedRate - correction;
double fairRate = swap.fairRate() - correction;
SwaptionVolatilityMatrix volatility =
model_.link.getSwaptionVolatilityMatrix();
Date referenceDate = volatility.referenceDate();
DayCounter dayCounter = volatility.dayCounter();
double exercise = dayCounter.yearFraction(referenceDate,
arguments_.exercise.date(0));
double swapLength =
dayCounter.yearFraction(referenceDate,
arguments_.fixedPayDates.Last())
- dayCounter.yearFraction(referenceDate,
arguments_.fixedResetDates[0]);
Option.Type w = arguments_.type == VanillaSwap.Type.Payer ?
Option.Type.Call : Option.Type.Put;
double vol = volatility.volatility(exercise, swapLength,
fairRate, true);
results_.value = (swap.fixedLegBPS() / Const.BASIS_POINT) *
Utils.blackFormula(w, fixedRate, fairRate, vol * Math.Sqrt(exercise));
}
// 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()));
}
