Skip to content

Commit

Permalink
Merge pull request #797.
Browse files Browse the repository at this point in the history 
Iterative bootstrap - widen min, max in search and fall back
  • Loading branch information
@lballabio
lballabio committed Apr 30, 2020
2 parents bcb87bc + 4b1f17b commit 1dbc772
Show file tree
Hide file tree
Showing 5 changed files with 432 additions and 23 deletions.
154 changes: 131 additions & 23 deletions ql/termstructures/iterativebootstrap.hpp
View file
Expand Up @@ -36,21 +36,81 @@

namespace QuantLib {

namespace detail {

/*! If \c dontThrow is \c true in IterativeBootstrap and on a given pillar the bootstrap fails when
searching for a helper root between \c xMin and \c xMax, we use this function to return the value that
gives the minimum absolute helper error in the interval between \c xMin and \c xMax inclusive.
*/
template <class Curve>
Real dontThrowFallback(const BootstrapError<Curve>& error,
Real xMin, Real xMax, Size steps) {

QL_REQUIRE(xMin < xMax, "Expected xMin to be less than xMax");

// Set the initial value of the result to xMin and store the absolute bootstrap error at xMin
Real result = xMin;
Real absError = std::abs(error(xMin));
Real minError = absError;

// Step out to xMax
Real stepSize = (xMax - xMin) / steps;
for (Size i = 0; i < steps; i++) {

// Get absolute bootstrap error at updated x value
xMin += stepSize;
absError = std::abs(error(xMin));

// If this absolute bootstrap error is less than the minimum, update result and minError
if (absError < minError) {
result = xMin;
minError = absError;
}
}

return result;
}

}

//! Universal piecewise-term-structure boostrapper.
template <class Curve>
class IterativeBootstrap {
typedef typename Curve::traits_type Traits;
typedef typename Curve::interpolator_type Interpolator;
public:
/*! Constructor
\param accuracy Accuracy for the bootstrap stopping criterion. If it is set to
\c Null<Real>(), its value is taken from the termstructure's accuracy.
\param minValue Allow to override the initial minimum value coming from traits.
\param maxValue Allow to override the initial maximum value coming from traits.
\param maxAttempts Number of attempts on each iteration. A number greater than 1 implies retries.
\param maxFactor Factor for max value retry on each iteration if there is a failure.
\param minFactor Factor for min value retry on each iteration if there is a failure.
\param dontThrow If set to \c true, the bootstrap doesn't throw and returns a <em>fall back</em>
result.
\param dontThrowSteps If \p dontThrow is \c true, this gives the number of steps to use when searching
for a fallback curve pillar value that gives the minimum bootstrap helper error.
*/
IterativeBootstrap(Real accuracy = Null<Real>(),
Real minValue = Null<Real>(),
Real maxValue = Null<Real>());
Real maxValue = Null<Real>(),
Size maxAttempts = 1,
Real maxFactor = 2.0,
Real minFactor = 2.0,
bool dontThrow = false,
Size dontThrowSteps = 10);
void setup(Curve* ts);
void calculate() const;
private:
void initialize() const;
Real accuracy_;
Real minValue_, maxValue_;
Size maxAttempts_;
Real maxFactor_;
Real minFactor_;
bool dontThrow_;
Size dontThrowSteps_;
Curve* ts_;
Size n_;
Brent firstSolver_;
Expand All @@ -65,10 +125,15 @@ namespace QuantLib {
// template definitions

template <class Curve>
IterativeBootstrap<Curve>::IterativeBootstrap(Real accuracy, Real minValue, Real maxValue)
IterativeBootstrap<Curve>::IterativeBootstrap(Real accuracy, Real minValue, Real maxValue,
Size maxAttempts, Real maxFactor, Real minFactor, bool dontThrow, Size dontThrowSteps)
: accuracy_(accuracy), minValue_(minValue), maxValue_(maxValue),
ts_(0), initialized_(false), validCurve_(false),
loopRequired_(Interpolator::global) {}
maxAttempts_(maxAttempts), maxFactor_(maxFactor), minFactor_(minFactor), dontThrow_(dontThrow),
dontThrowSteps_(dontThrowSteps), ts_(0), initialized_(false), validCurve_(false),
loopRequired_(Interpolator::global) {
QL_REQUIRE(maxFactor_ >= 1.0, "Expected that maxFactor would be at least 1.0 but got " << maxFactor_);
QL_REQUIRE(minFactor_ >= 1.0, "Expected that minFactor would be at least 1.0 but got " << minFactor_);
}

template <class Curve>
void IterativeBootstrap<Curve>::setup(Curve* ts) {
Expand Down Expand Up @@ -192,20 +257,39 @@ namespace QuantLib {
for (Size iteration=0; ; ++iteration) {
previousData_ = ts_->data_;

// Store min value and max value at each pillar so that we can expand search if necessary.
std::vector<Real> minValues(alive_+1, Null<Real>());
std::vector<Real> maxValues(alive_+1, Null<Real>());
std::vector<Size> attempts(alive_+1, 1);

for (Size i=1; i<=alive_; ++i) { // pillar loop

// bracket root and calculate guess
Real min = minValue_ != Null<Real>() ? minValue_ :
Traits::minValueAfter(i, ts_, validData, firstAliveHelper_);
Real max = maxValue_ != Null<Real>() ? maxValue_ :
Traits::maxValueAfter(i, ts_, validData, firstAliveHelper_);
// shorter aliases for readability and to avoid duplication
Real& min = minValues[i];
Real& max = maxValues[i];

// bracket root and calculate guess
if (min == Null<Real>()) {
// First attempt; we take min and max either from
// explicit constructor parameter or from traits
min = (minValue_ != Null<Real>() ? minValue_ :
Traits::minValueAfter(i, ts_, validData, firstAliveHelper_));
max = (maxValue_ != Null<Real>() ? maxValue_ :
Traits::maxValueAfter(i, ts_, validData, firstAliveHelper_));
} else {
// Extending a previous attempt. A negative min
// is enlarged; a positive one is shrunk towards 0.
min = (min < 0.0 ? min * minFactor_ : min / minFactor_);
// The opposite holds for the max.
max = (max > 0.0 ? max * maxFactor_ : max / maxFactor_);
}
Real guess = Traits::guess(i, ts_, validData, firstAliveHelper_);

// adjust guess if needed
if (guess>=max)
guess = max - (max-min)/5.0;
else if (guess<=min)
guess = min + (max-min)/5.0;
if (guess >= max)
guess = max - (max - min) / 5.0;
else if (guess <= min)
guess = min + (max - min) / 5.0;

// extend interpolation if needed
if (!validData) {
Expand Down Expand Up @@ -242,12 +326,30 @@ namespace QuantLib {
calculate();
return;
}
QL_FAIL(io::ordinal(iteration+1) << " iteration: failed "
"at " << io::ordinal(i) << " alive instrument, "
"pillar " << errors_[i]->helper()->pillarDate() <<
", maturity " << errors_[i]->helper()->maturityDate() <<
", reference date " << ts_->dates_[0] <<
": " << e.what());

// If we have more attempts left on this iteration, try again. Note that the max and min
// bounds will be widened on the retry.
if (attempts[i] < maxAttempts_) {
attempts[i]++;
i--;
continue;
}

if (dontThrow_) {
// Use the fallback value
ts_->data_[i] = detail::dontThrowFallback(*errors_[i], min, max, dontThrowSteps_);

// Remember to update the interpolation. If we don't and we are on the last "i", we will still
// have the last attempted value in the solver being used in ts_->interpolation_.
ts_->interpolation_.update();
} else {
QL_FAIL(io::ordinal(iteration + 1) << " iteration: failed "
"at " << io::ordinal(i) << " alive instrument, "
"pillar " << errors_[i]->helper()->pillarDate() <<
", maturity " << errors_[i]->helper()->maturityDate() <<
", reference date " << ts_->dates_[0] <<
": " << e.what());
}
}
}

Expand All @@ -261,10 +363,16 @@ namespace QuantLib {
if (change<=accuracy) // convergence reached
break;

QL_REQUIRE(iteration<maxIterations,
"convergence not reached after " << iteration <<
" iterations; last improvement " << change <<
", required accuracy " << accuracy);
// If we hit the max number of iterations and dontThrow is true, just use what we have
if (iteration == maxIterations) {
if (dontThrow_) {
break;
} else {
QL_FAIL("convergence not reached after " << iteration <<
" iterations; last improvement " << change <<
", required accuracy " << accuracy);
}
}

validData = true;
}
Expand Down

0 comments on commit 1dbc772

Please sign in to comment.