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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2012, 2013 Klaus Spanderen
Copyright (C) 2014 Johannes Göttker-Schnetmann
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
<https://www.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 fdmsquarerootfwdop.cpp
\brief Fokker-Planck forward operator for an square root process
*/
#include <ql/methods/finitedifferences/meshers/fdmmesher.hpp>
#include <ql/methods/finitedifferences/operators/fdmlinearoplayout.hpp>
#include <ql/methods/finitedifferences/operators/firstderivativeop.hpp>
#include <ql/methods/finitedifferences/operators/secondderivativeop.hpp>
#include <ql/methods/finitedifferences/operators/fdmsquarerootfwdop.hpp>
#include <ql/methods/finitedifferences/operators/modtriplebandlinearop.hpp>
namespace QuantLib {
FdmSquareRootFwdOp::FdmSquareRootFwdOp(
const ext::shared_ptr<FdmMesher>& mesher,
Real kappa, Real theta, Real sigma,
Size direction, TransformationType transform)
: direction_(direction),
kappa_(kappa),
theta_(theta),
sigma_(sigma),
transform_(transform),
mapX_(transform == Plain ?
new ModTripleBandLinearOp(FirstDerivativeOp(direction_, mesher)
.mult(kappa*(mesher->locations(direction_)-theta) + sigma*sigma)
.add(SecondDerivativeOp(direction_, mesher)
.mult(0.5*sigma*sigma*mesher->locations(direction_)))
.add(Array(mesher->layout()->size(), kappa)))
: transform == Power ? new ModTripleBandLinearOp(
SecondDerivativeOp(direction_, mesher)
.mult(0.5*sigma*sigma*mesher->locations(direction_))
.add(FirstDerivativeOp(direction_, mesher)
.mult(kappa*(mesher->locations(direction_)+theta)))
.add(Array(mesher->layout()->size(),
2*kappa*kappa*theta/(sigma*sigma))))
: new ModTripleBandLinearOp(FirstDerivativeOp(direction_, mesher)
.mult(Exp(-mesher->locations(direction))
*( -0.5*sigma*sigma - kappa*theta) + kappa)
.add(SecondDerivativeOp(direction_, mesher)
.mult(0.5*sigma*sigma*Exp(-mesher->locations(direction))))
.add(kappa*theta*Exp(-mesher->locations(direction))))
),
v_ (mesher->layout()->dim()[direction_]) {
for (const auto& iter : *mesher->layout()) {
const Real v = mesher->location(iter, direction_);
v_[iter.coordinates()[direction_]] = v;
}
// zero flux boundary condition
setLowerBC(mesher);
setUpperBC(mesher);
}
void FdmSquareRootFwdOp::setLowerBC(
const ext::shared_ptr<FdmMesher>& mesher) {
const Size n = 1;
Real alpha, beta, gamma;
getCoeff(alpha, beta, gamma, n);
const Real f = lowerBoundaryFactor(transform_);
const Real b = -(h(n-1)+h(n))/zeta(n);
const Real c = h(n-1)/zetap(n);
for (const auto& iter : *mesher->layout()) {
if (iter.coordinates()[direction_] == 0) {
const Size idx = iter.index();
mapX_->diag(idx) = beta + f*b; //*v(n-1);
mapX_->upper(idx) = gamma + f*c; //*v(n-1);
}
}
}
void FdmSquareRootFwdOp::setUpperBC(
const ext::shared_ptr<FdmMesher>& mesher) {
const Size n = v_.size();
Real alpha, beta, gamma;
getCoeff(alpha, beta, gamma, n);
const Real f = upperBoundaryFactor(transform_);
const Real b = (h(n)+h(n-1))/zeta(n);
const Real c = -h(n)/zetam(n);
for (const auto& iter : *mesher->layout()) {
if (iter.coordinates()[direction_] == n-1) {
const Size idx = iter.index();
mapX_->diag(idx) = beta + f*b; //*v(n+1);
mapX_->lower(idx) = alpha + f*c; //*v(n+1);
}
}
}
Real FdmSquareRootFwdOp::lowerBoundaryFactor(TransformationType transform) const {
if (transform == Plain) {
return f0Plain();
}
else if (transform == Power) {
return f0Power();
}
else if (transform == Log) {
return f0Log();
}
else
QL_FAIL("unknown transform");
}
Real FdmSquareRootFwdOp::upperBoundaryFactor(TransformationType transform) const {
if (transform == Plain) {
return f1Plain();
}
else if (transform == Power) {
return f1Power();
}
else if (transform == Log) {
return f1Log();
}
else
QL_FAIL("unknown transform");
}
Real FdmSquareRootFwdOp::f0Plain() const {
const Size n = 1;
const Real a = -(2*h(n-1)+h(n))/zetam(n);
const Real alpha = sigma_*sigma_*v(n)/zetam(n) - mu(n)*h(n)/zetam(n);
const Real nu = a*v(n-1) + (2*kappa_*(v(n-1)-theta_) + sigma_*sigma_)
/(sigma_*sigma_);
return alpha/nu*v(n-1);
}
Real FdmSquareRootFwdOp::f1Plain() const {
const Size n = v_.size();
const Real a = (2*h(n)+h(n-1))/zetap(n);
const Real gamma = sigma_*sigma_*v(n)/zetap(n) + mu(n)*h(n-1)/zetap(n);
const Real nu = a*v(n+1) + (2*kappa_*(v(n+1)-theta_) + sigma_*sigma_)
/(sigma_*sigma_);
return gamma/nu*v(n+1);
}
Real FdmSquareRootFwdOp::f0Power() const {
const Size n = 1;
const Real mu = kappa_*(v(n)+theta_);
const Real a = -(2*h(n-1)+h(n))/zetam(n);
const Real alpha = sigma_*sigma_*v(n)/zetam(n) - mu*h(n)/zetam(n);
const Real nu = a*v(n-1) +2*(kappa_*v(n-1)/(sigma_*sigma_));
return alpha/nu*v(n-1);
}
Real FdmSquareRootFwdOp::f1Power() const {
const Size n = v_.size();
const Real mu = kappa_*(v(n)+theta_);
const Real a = (2*h(n)+h(n-1))/zetap(n);
const Real gamma = sigma_*sigma_*v(n)/zetap(n) + mu*h(n-1)/zetap(n);
const Real nu = a*v(n+1) +2*(kappa_*v(n+1)/(sigma_*sigma_));
return gamma/nu*v(n+1);
}
Real FdmSquareRootFwdOp::f0Log() const {
const Size n = 1;
const Real mu = ((-kappa_*theta_-sigma_*sigma_/2.0)*exp(-v(1))+kappa_);
const Real a = -(2*h(n-1)+h(n))/zetam(n);
const Real alpha = sigma_*sigma_*exp(-v(n))/zetam(n) - mu*h(n)/zetam(n);
const Real nu = a*exp(-v(n-1)) + 2*kappa_*(1-theta_*exp(-v(n-1)))
/(sigma_*sigma_);
return alpha/nu*exp(-v(n-1));
}
Real FdmSquareRootFwdOp::f1Log() const {
const Size n = v_.size();
const Real mu = ((-kappa_*theta_-sigma_*sigma_/2.0)*exp(-v(n))+kappa_);
const Real a = (2*h(n)+h(n-1))/zetap(n);
const Real gamma = sigma_*sigma_*exp(-v(n))/zetap(n) + mu*h(n-1)/zetap(n);
const Real nu = a*exp(-v(n+1)) + 2*kappa_*(1-theta_*exp(-v(n+1)))
/(sigma_*sigma_);
return gamma/nu*exp(-v(n+1));
}
Real FdmSquareRootFwdOp::v(Size i) const {
if (i > 0 && i <= v_.size()) {
return v_[i-1];
}
else if (i == 0) {
if (transform_ == Log) {
return 2*v_[0] - v_[1];
// log(std::max(0.5*exp(v_[0]), exp(v_[0] - 0.01 * (v_[1] - v_[0]))));
} else {
return std::max(0.5*v_[0], v_[0] - 0.01 * (v_[1] - v_[0]));
}
}
else if (i == v_.size()+1) {
return v_.back() + (v_.back() - *(v_.end()-2));
}
else {
QL_FAIL("unknown index");
}
}
Real FdmSquareRootFwdOp::h(Size i) const {
return v(i+1) - v(i);
}
Real FdmSquareRootFwdOp::mu(Size i) const {
return kappa_*(v(i) - theta_) + sigma_*sigma_;
}
Real FdmSquareRootFwdOp::zetam(Size i) const {
return h(i-1)*(h(i-1)+h(i));
}
Real FdmSquareRootFwdOp::zeta(Size i) const {
return h(i-1)*h(i);
}
Real FdmSquareRootFwdOp::zetap(Size i) const {
return h(i)*(h(i-1)+h(i));
}
Size FdmSquareRootFwdOp::size() const {
return 1;
}
void FdmSquareRootFwdOp::setTime(Time, Time) {
}
void FdmSquareRootFwdOp::getCoeff(Real& alpha, Real& beta,
Real& gamma, Size n) const {
if (transform_ == Plain) {
getCoeffPlain(alpha, beta, gamma, n);
}
else if (transform_ == Power) {
getCoeffPower(alpha, beta, gamma, n);
}
else if (transform_ == Log) {
getCoeffLog(alpha, beta, gamma, n);
}
}
void FdmSquareRootFwdOp::getCoeffPlain(Real& alpha, Real& beta,
Real& gamma, Size n) const {
alpha = sigma_*sigma_*v(n)/zetam(n) - mu(n)*h(n)/zetam(n);
beta = - sigma_*sigma_*v(n)/zeta(n)
+ mu(n)*(h(n)-h(n-1))/zeta(n) + kappa_;
gamma = sigma_*sigma_*v(n)/zetap(n) + mu(n)*h(n-1)/zetap(n);
}
void FdmSquareRootFwdOp::getCoeffLog(Real& alpha, Real& beta,
Real& gamma, Size n) const {
const Real mu = ((-kappa_*theta_-sigma_*sigma_/2.0)*exp(-v(n))+kappa_);
alpha = sigma_*sigma_*exp(-v(n))/zetam(n) - mu*h(n)/zetam(n);
beta = - sigma_*sigma_*exp(-v(n))/zeta(n)
+ mu*(h(n)-h(n-1))/zeta(n) + kappa_*theta_*exp(-v(n));
gamma = sigma_*sigma_*exp(-v(n))/zetap(n) + mu*h(n-1)/zetap(n);
}
void FdmSquareRootFwdOp::getCoeffPower(Real& alpha, Real& beta,
Real& gamma, Size n) const {
const Real mu = kappa_*(theta_+v(n));
alpha = (sigma_*sigma_*v(n) - mu*h(n))/zetam(n);
beta = (-sigma_*sigma_*v(n) + mu*(h(n)-h(n-1)))/zeta(n)
+ 2*kappa_*kappa_*theta_/(sigma_*sigma_);
gamma= (sigma_*sigma_*v(n) + mu*h(n-1))/zetap(n);
}
Array FdmSquareRootFwdOp::apply(const Array& p) const {
return mapX_->apply(p);
}
Array FdmSquareRootFwdOp::apply_mixed(const Array& r) const {
return Array(r.size(), 0.0);
}
Array FdmSquareRootFwdOp::apply_direction(
Size direction, const Array& r) const {
if (direction == direction_) {
return mapX_->apply(r);
}
else {
return Array(r.size(), 0.0);
}
}
Array FdmSquareRootFwdOp::solve_splitting(
Size direction, const Array& r, Real dt) const {
if (direction == direction_) {
return mapX_->solve_splitting(r, dt, 1.0);
}
else {
return r;
}
}
Array FdmSquareRootFwdOp::preconditioner(
const Array& r, Real dt) const {
return solve_splitting(direction_, r, dt);
}
std::vector<SparseMatrix> FdmSquareRootFwdOp::toMatrixDecomp() const {
return std::vector<SparseMatrix>(1, mapX_->toMatrix());
}
}
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