/usr/include/ql/termstructures/credit/probabilitytraits.hpp is in libquantlib0-dev 1.4-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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/*
Copyright (C) 2008 Jose Aparicio
Copyright (C) 2008 Chris Kenyon
Copyright (C) 2008 Roland Lichters
Copyright (C) 2008 StatPro Italia srl
Copyright (C) 2009, 2011 Ferdinando Ametrano
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it and/or modify it
under the terms of the QuantLib license. You should have received a
copy of the license along with this program; if not, please email
<quantlib-dev@lists.sf.net>. The license is also available online at
<http://quantlib.org/license.shtml>.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the license for more details.
*/
/*! \file probabilitytraits.hpp
\brief default-probability bootstrap traits
*/
#ifndef ql_probability_traits_hpp
#define ql_probability_traits_hpp
#include <ql/termstructures/credit/interpolatedsurvivalprobabilitycurve.hpp>
#include <ql/termstructures/credit/interpolatedhazardratecurve.hpp>
#include <ql/termstructures/credit/interpolateddefaultdensitycurve.hpp>
#include <ql/termstructures/bootstraphelper.hpp>
namespace QuantLib {
namespace detail {
const Real avgHazardRate = 0.01;
const Real maxHazardRate = 1.0;
}
//! Survival-Probability-curve traits
struct SurvivalProbability {
// interpolated curve type
template <class Interpolator>
struct curve {
typedef InterpolatedSurvivalProbabilityCurve<Interpolator> type;
};
// helper class
typedef BootstrapHelper<DefaultProbabilityTermStructure> helper;
// start of curve data
static Date initialDate(const DefaultProbabilityTermStructure* c) {
return c->referenceDate();
}
// value at reference date
static Real initialValue(const DefaultProbabilityTermStructure*) {
return 1.0;
}
// guesses
template <class C>
static Real guess(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) // previous iteration value
return c->data()[i];
if (i==1) // first pillar
return 1.0/(1.0+detail::avgHazardRate*0.25);
// extrapolate
Date d = c->dates()[i];
return c->survivalProbability(d,true);
}
// constraints
template <class C>
static Real minValueAfter(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) {
return c->data().back()/2.0;
}
Time dt = c->times()[i] - c->times()[i-1];
return c->data()[i-1] * std::exp(- detail::maxHazardRate * dt);
}
template <class C>
static Real maxValueAfter(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
// survival probability cannot increase
return c->data()[i-1];
}
// root-finding update
static void updateGuess(std::vector<Real>& data,
Probability p,
Size i) {
data[i] = p;
}
// upper bound for convergence loop
static Size maxIterations() { return 50; }
};
//! Hazard-rate-curve traits
struct HazardRate {
// interpolated curve type
template <class Interpolator>
struct curve {
typedef InterpolatedHazardRateCurve<Interpolator> type;
};
// helper class
typedef BootstrapHelper<DefaultProbabilityTermStructure> helper;
// start of curve data
static Date initialDate(const DefaultProbabilityTermStructure* c) {
return c->referenceDate();
}
// dummy value at reference date
static Real initialValue(const DefaultProbabilityTermStructure*) {
return detail::avgHazardRate;
}
// guesses
template <class C>
static Real guess(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) // previous iteration value
return c->data()[i];
if (i==1) // first pillar
return detail::avgHazardRate;
// extrapolate
Date d = c->dates()[i];
return c->hazardRate(d, true);
}
// constraints
template <class C>
static Real minValueAfter(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) {
Real r = *(std::min_element(c->data().begin(), c->data().end()));
return r/2.0;
}
return QL_EPSILON;
}
template <class C>
static Real maxValueAfter(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) {
Real r = *(std::max_element(c->data().begin(), c->data().end()));
return r*2.0;
}
// no constraints.
// We choose as max a value very unlikely to be exceeded.
return detail::maxHazardRate;
}
// update with new guess
static void updateGuess(std::vector<Real>& data,
Real rate,
Size i) {
data[i] = rate;
if (i==1)
data[0] = rate; // first point is updated as well
}
// upper bound for convergence loop
static Size maxIterations() { return 30; }
};
//! Default-density-curve traits
struct DefaultDensity {
// interpolated curve type
template <class Interpolator>
struct curve {
typedef InterpolatedDefaultDensityCurve<Interpolator> type;
};
// helper class
typedef BootstrapHelper<DefaultProbabilityTermStructure> helper;
// start of curve data
static Date initialDate(const DefaultProbabilityTermStructure* c) {
return c->referenceDate();
}
// value at reference date
static Real initialValue(const DefaultProbabilityTermStructure*) {
return detail::avgHazardRate;
}
// guesses
template <class C>
static Real guess(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) // previous iteration value
return c->data()[i];
if (i==1) // first pillar
return detail::avgHazardRate;
// extrapolate
Date d = c->dates()[i];
return c->defaultDensity(d, true);
}
// constraints
template <class C>
static Real minValueAfter(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) {
Real r = *(std::min_element(c->data().begin(), c->data().end()));
return r/2.0;
}
return QL_EPSILON;
}
template <class C>
static Real maxValueAfter(Size i,
const C* c,
bool validData,
Size) // firstAliveHelper
{
if (validData) {
Real r = *(std::max_element(c->data().begin(), c->data().end()));
return r*2.0;
}
// no constraints.
// We choose as max a value very unlikely to be exceeded.
return detail::maxHazardRate;
}
// update with new guess
static void updateGuess(std::vector<Real>& data,
Real density,
Size i) {
data[i] = density;
if (i==1)
data[0] = density; // first point is updated as well
}
// upper bound for convergence loop
static Size maxIterations() { return 30; }
};
}
#endif
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