public void calculate()
{
validCurve_ = false;
int nInsts = ts_.instruments_.Count, i;
// ensure rate helpers are sorted
ts_.instruments_.Sort((x, y) => x.latestDate().CompareTo(y.latestDate()));
// check that there is no instruments with the same maturity
for (i = 1; i < nInsts; ++i)
{
Date m1 = ts_.instruments_[i - 1].latestDate(),
m2 = ts_.instruments_[i].latestDate();
if (m1 == m2)
{
throw new ArgumentException("two instruments have the same maturity (" + m1 + ")");
}
}
// check that there is no instruments with invalid quote
if ((i = ts_.instruments_.FindIndex(x => !x.quoteIsValid())) != -1)
{
throw new ArgumentException("instrument " + i + " (maturity: " + ts_.instruments_[i].latestDate() +
") has an invalid quote");
}
// setup instruments and register with them
ts_.instruments_.ForEach(j => j.setTermStructure(ts_));
// set initial guess only if the current curve cannot be used as guess
if (validCurve_)
{
if (ts_.data_.Count != nInsts + 1)
{
throw new ArgumentException("dimension mismatch: expected " + nInsts + 1 + ", actual " + ts_.data_.Count);
}
}
else
{
ts_.data_ = new InitializedList <double>(nInsts + 1);
ts_.data_[0] = ts_.initialValue(ts_);
}
// calculate dates and times
ts_.dates_ = new InitializedList <Date>(nInsts + 1);
ts_.times_ = new InitializedList <double>(nInsts + 1);
ts_.dates_[0] = ts_.initialDate(ts_);
ts_.times_[0] = ts_.timeFromReference(ts_.dates_[0]);
for (i = 0; i < nInsts; ++i)
{
ts_.dates_[i + 1] = ts_.instruments_[i].latestDate();
ts_.times_[i + 1] = ts_.timeFromReference(ts_.dates_[i + 1]);
if (!validCurve_)
{
ts_.data_[i + 1] = ts_.data_[i];
}
}
LevenbergMarquardt solver = new LevenbergMarquardt(ts_.accuracy_, ts_.accuracy_, ts_.accuracy_);
EndCriteria endCriteria = new EndCriteria(100, 10, 0.00, ts_.accuracy_, 0.00);
PositiveConstraint posConstraint = new PositiveConstraint();
NoConstraint noConstraint = new NoConstraint();
Constraint solverConstraint = forcePositive_ ? (Constraint)posConstraint : (Constraint)noConstraint;
// now start the bootstrapping.
int iInst = localisation_ - 1;
int dataAdjust = (ts_.interpolator_ as ConvexMonotone).dataSizeAdjustment;
do
{
int initialDataPt = iInst + 1 - localisation_ + dataAdjust;
Vector startArray = new Vector(localisation_ + 1 - dataAdjust);
for (int j = 0; j < startArray.size() - 1; ++j)
{
startArray[j] = ts_.data_[initialDataPt + j];
}
// here we are extending the interpolation a point at a
// time... but the local interpolator can make an
// approximation for the final localisation period.
// e.g. if the localisation is 2, then the first section
// of the curve will be solved using the first 2
// instruments... with the local interpolator making
// suitable boundary conditions.
ts_.interpolation_ = (ts_.interpolator_ as ConvexMonotone).localInterpolate(ts_.times_, iInst + 2, ts_.data_,
localisation_, ts_.interpolation_ as ConvexMonotoneInterpolation, nInsts + 1);
if (iInst >= localisation_)
{
startArray[localisation_ - dataAdjust] = ts_.guess(ts_, ts_.dates_[iInst]);
}
else
{
startArray[localisation_ - dataAdjust] = ts_.data_[0];
}
var currentCost = new PenaltyFunction <PiecewiseYieldCurve>(ts_, initialDataPt, ts_.instruments_,
iInst - localisation_ + 1, iInst + 1);
Problem toSolve = new Problem(currentCost, solverConstraint, startArray);
EndCriteria.Type endType = solver.minimize(toSolve, endCriteria);
// check the end criteria
if (!(endType == EndCriteria.Type.StationaryFunctionAccuracy ||
endType == EndCriteria.Type.StationaryFunctionValue))
{
throw new ApplicationException("Unable to strip yieldcurve to required accuracy ");
}
++iInst;
} while (iInst < nInsts);
validCurve_ = true;
}
public void calculate()
{
//prepare instruments
int n = ts_.instruments_.Count, i;
// ensure rate helpers are sorted
ts_.instruments_.Sort((x, y) => x.latestDate().CompareTo(y.latestDate()));
// check that there is no instruments with the same maturity
for (i = 1; i < n; ++i)
{
Date m1 = ts_.instruments_[i - 1].latestDate(),
m2 = ts_.instruments_[i].latestDate();
if (m1 == m2)
{
throw new ArgumentException("two instruments have the same maturity (" + m1 + ")");
}
}
// check that there is no instruments with invalid quote
if ((i = ts_.instruments_.FindIndex(x => !x.quoteIsValid())) != -1)
{
throw new ArgumentException("instrument " + i + " (maturity: " + ts_.instruments_[i].latestDate() +
") has an invalid quote");
}
// setup instruments and register with them
ts_.instruments_.ForEach(x => x.setTermStructure(ts_));
// calculate dates and times
ts_.dates_ = new InitializedList <Date>(n + 1);
ts_.times_ = new InitializedList <double>(n + 1);
ts_.dates_[0] = ts_.initialDate(ts_);
ts_.times_[0] = ts_.timeFromReference(ts_.dates_[0]);
for (i = 0; i < n; ++i)
{
ts_.dates_[i + 1] = ts_.instruments_[i].latestDate();
ts_.times_[i + 1] = ts_.timeFromReference(ts_.dates_[i + 1]);
}
// set initial guess only if the current curve cannot be used as guess
if (validCurve_)
{
if (ts_.data_.Count != n + 1)
{
throw new ArgumentException("dimension mismatch: expected " + n + 1 + ", actual " + ts_.data_.Count);
}
}
else
{
ts_.data_ = new InitializedList <double>(n + 1);
ts_.data_[0] = ts_.initialValue(ts_);
for (i = 0; i < n; ++i)
{
ts_.data_[i + 1] = ts_.initialGuess();
}
}
Brent solver = new Brent();
int maxIterations = ts_.maxIterations();
for (int iteration = 0; ; ++iteration)
{
List <double> previousData = ts_.data();
// restart from the previous interpolation
if (validCurve_)
{
ts_.interpolation_ = ts_.interpolator_.interpolate(ts_.times_, ts_.times_.Count, ts_.data_);
}
for (i = 1; i < n + 1; ++i)
{
// calculate guess before extending interpolation to ensure that any extrapolation is performed
// using the curve bootstrapped so far and no more
RateHelper instrument = ts_.instruments_[i - 1];
double guess = 0;
if (validCurve_ || iteration > 0)
{
guess = ts_.data_[i];
}
else if (i == 1)
{
guess = ts_.initialGuess();
}
else
{
// most traits extrapolate
guess = ts_.guess(ts_, ts_.dates_[i]);
}
// bracket
double min = ts_.minValueAfter(i, ts_.data_);
double max = ts_.maxValueAfter(i, ts_.data_);
if (guess <= min || guess >= max)
{
guess = (min + max) / 2.0;
}
if (!validCurve_ && iteration == 0)
{
// extend interpolation a point at a time
try {
ts_.interpolation_ = ts_.interpolator_.interpolate(ts_.times_, i + 1, ts_.data_);
} catch {
if (!ts_.interpolator_.global)
{
throw; // no chance to fix it in a later iteration
}
// otherwise, if the target interpolation is not usable yet
ts_.interpolation_ = new Linear().interpolate(ts_.times_, i + 1, ts_.data_);
}
}
// required because we just changed the data
// is it really required?
ts_.interpolation_.update();
try {
var error = new BootstrapError(ts_, instrument, i);
double r = solver.solve(error, ts_.accuracy_, guess, min, max);
// redundant assignment (as it has been already performed by BootstrapError in solve procedure), but safe
ts_.data_[i] = r;
} catch (Exception e) {
validCurve_ = false;
throw new ArgumentException(" iteration: " + iteration + 1 +
"could not bootstrap the " + i + " instrument, maturity " + ts_.dates_[i] +
": " + e.Message);
}
}
if (!ts_.interpolator_.global)
{
break; // no need for convergence loop
}
else if (!validCurve_ && iteration == 0)
{
// ensure the target interpolation is used
ts_.interpolation_ = ts_.interpolator_.interpolate(ts_.times_, ts_.times_.Count, ts_.data_);
// at least one more iteration is needed to check convergence
continue;
}
// exit conditions
double improvement = 0.0;
for (i = 1; i < n + 1; ++i)
{
improvement = Math.Max(improvement, Math.Abs(ts_.data_[i] - previousData[i]));
}
if (improvement <= ts_.accuracy_) // convergence reached
{
break;
}
if (!(iteration + 1 < maxIterations))
{
throw new ArgumentException("convergence not reached after " + iteration + 1 + " iterations; last improvement " +
improvement + ", required accuracy " + ts_.accuracy_);
}
}
validCurve_ = true;
}
