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())); }