public void recalibration(List <Period> swapLengths, List <double> beta, Period swapTenor)
{
Utils.QL_REQUIRE(beta.Count == swapLengths.Count, () =>
"beta size (" + beta.Count + ") must be equal to number of swap lenghts ("
+ swapLengths.Count + ")");
List <double> betaTimes = new List <double>();
for (int i = 0; i < beta.Count; i++)
{
betaTimes.Add(timeFromReference(optionDateFromTenor(swapLengths[i])));
}
LinearInterpolation betaInterpolation = new LinearInterpolation(betaTimes, betaTimes.Count, beta);
List <double> cubeBeta = new List <double>();
for (int i = 0; i < optionTimes().Count; i++)
{
double t = optionTimes()[i];
// flat extrapolation ensures admissable values
if (t < betaTimes.First())
{
t = betaTimes.First();
}
if (t > betaTimes.Last())
{
t = betaTimes.Last();
}
cubeBeta.Add(betaInterpolation.value(t));
}
recalibration(cubeBeta, swapTenor);
}
public void applyTo(object o, double t)
{
Vector a = (Vector)o;
Vector aCopy = new Vector(a);
int iterIndex = dividendTimes_.BinarySearch(t);
if (iterIndex >= 0)
{
double dividend = dividends_[iterIndex];
if (mesher_.layout().dim().Count == 1)
{
LinearInterpolation interp = new LinearInterpolation(x_, x_.Count, aCopy);
for (int k = 0; k < x_.size(); ++k)
{
a[k] = interp.value(Math.Max(x_[0], x_[k] - dividend), true);
}
}
else
{
Vector tmp = new Vector(x_.size());
int xSpacing = mesher_.layout().spacing()[equityDirection_];
for (int i = 0; i < mesher_.layout().dim().Count; ++i)
{
if (i != equityDirection_)
{
int ySpacing = mesher_.layout().spacing()[i];
for (int j = 0; j < mesher_.layout().dim()[i]; ++j)
{
for (int k = 0; k < x_.size(); ++k)
{
int index = j * ySpacing + k * xSpacing;
tmp[k] = aCopy[index];
}
LinearInterpolation interp = new LinearInterpolation(x_, x_.Count, tmp);
for (int k = 0; k < x_.size(); ++k)
{
int index = j * ySpacing + k * xSpacing;
a[index] = interp.value(
Math.Max(x_[0], x_[k] - dividend), true);
}
}
}
}
}
}
}
protected override double volatilityImpl(double length, double strike)
{
calculate();
List <double> vol = new InitializedList <double>(nInterpolations_);
for (int i = 0; i < nInterpolations_; ++i)
{
vol[i] = strikeInterpolations_[i].value(strike, true);
}
List <double> optionletTimes = new List <double>(optionletStripper_.optionletFixingTimes());
LinearInterpolation timeInterpolator = new LinearInterpolation(optionletTimes, optionletTimes.Count, vol);
return(timeInterpolator.value(length, true));
}
public double k(double t, List <double> xBegin, int size)
{
LinearInterpolation li = new LinearInterpolation(xBegin, size, coeffs_.k_);
return(li.value(t));
}
public double k(double t)
{
LinearInterpolation li = new LinearInterpolation(this.xBegin_, this.size_, this.yBegin_);
return(li.value(t));
}
public Concentrating1dMesher(double start, double end, int size,
List <Tuple <double?, double?, bool> > cPoints,
double tol = 1e-8)
: base(size)
{
Utils.QL_REQUIRE(end > start, () => "end must be larger than start");
List <double?> points = new List <double?>(), betas = new List <double?>();
foreach (Tuple <double?, double?, bool> iter in cPoints)
{
points.Add(iter.Item1);
betas.Add((iter.Item2 * (end - start)) * (iter.Item2 * (end - start)));
}
// get scaling factor a so that y(1) = end
double aInit = 0.0;
for (int i = 0; i < points.Count; ++i)
{
double c1 = Utils.Asinh((start - points[i].GetValueOrDefault()) / betas[i].GetValueOrDefault());
double c2 = Utils.Asinh((end - points[i].GetValueOrDefault()) / betas[i].GetValueOrDefault());
aInit += (c2 - c1) / points.Count;
}
OdeIntegrationFct fct = new OdeIntegrationFct(points, betas, tol);
double a = new Brent().solve(
new OdeSolver(fct, start, 0.0, 1.0, end),
tol, aInit, 0.1 * aInit);
// solve ODE for all grid points
Vector x = new Vector(size), y = new Vector(size);
x[0] = 0.0;
y[0] = start;
double dx = 1.0 / (size - 1);
for (int i = 1; i < size; ++i)
{
x[i] = i * dx;
y[i] = fct.solve(a, y[i - 1], x[i - 1], x[i]);
}
// eliminate numerical noise and ensure y(1) = end
double dy = y[y.Count - 1] - end;
for (int i = 1; i < size; ++i)
{
y[i] -= i * dx * dy;
}
LinearInterpolation odeSolution = new LinearInterpolation(x, x.Count, y);
// ensure required points are part of the grid
List <Pair <double?, double?> > w =
new InitializedList <Pair <double?, double?> > (1, new Pair <double?, double?>(0.0, 0.0));
for (int i = 0; i < points.Count; ++i)
{
if (cPoints[i].Item3 && points[i] > start && points[i] < end)
{
int j = y.distance(y[0], y.BinarySearch(points[i].Value));
double e = new Brent().solve(
new OdeSolver2(odeSolution.value, points[i].Value),
Const.QL_EPSILON, x[j], 0.5 / size);
w.Add(new Pair <double?, double?>(Math.Min(x[size - 2], x[j]), e));
}
}
w.Add(new Pair <double?, double?>(1.0, 1.0));
w = w.OrderBy(xx => xx.first).Distinct(new equal_on_first()).ToList();
List <double> u = new List <double>(w.Count), z = new List <double>(w.Count);
for (int i = 0; i < w.Count; ++i)
{
u[i] = w[i].first.GetValueOrDefault();
z[i] = w[i].second.GetValueOrDefault();
}
LinearInterpolation transform = new LinearInterpolation(u, u.Count, z);
for (int i = 0; i < size; ++i)
{
locations_[i] = odeSolution.value(transform.value(i * dx));
}
for (int i = 0; i < size - 1; ++i)
{
dplus_[i] = dminus_[i + 1] = locations_[i + 1] - locations_[i];
}
dplus_[dplus_.Count] = null;
dminus_[0] = null;
}