/usr/include/ql/methods/lattices/trinomialtree.hpp is in libquantlib0-dev 1.7.1-1.
This file is owned by root:root, with mode 0o644.
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/*
Copyright (C) 2001, 2002, 2003 Sadruddin Rejeb
Copyright (C) 2005 StatPro Italia srl
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 trinomialtree.hpp
\brief Trinomial tree class
*/
#ifndef quantlib_trinomial_tree_hpp
#define quantlib_trinomial_tree_hpp
#include <ql/methods/lattices/tree.hpp>
#include <ql/timegrid.hpp>
namespace QuantLib {
class StochasticProcess1D;
//! Recombining trinomial tree class
/*! This class defines a recombining trinomial tree approximating a
1-D stochastic process.
\warning The diffusion term of the SDE must be independent of the
underlying process.
\ingroup lattices
*/
class TrinomialTree : public Tree<TrinomialTree> {
class Branching;
public:
enum Branches { branches = 3 };
TrinomialTree(const boost::shared_ptr<StochasticProcess1D>& process,
const TimeGrid& timeGrid,
bool isPositive = false);
Real dx(Size i) const { return dx_[i]; }
const TimeGrid& timeGrid() const { return timeGrid_; }
Size size(Size i) const;
Real underlying(Size i, Size index) const;
Size descendant(Size i, Size index, Size branch) const;
Real probability(Size i, Size index, Size branch) const;
protected:
std::vector<Branching> branchings_;
Real x0_;
std::vector<Real> dx_;
TimeGrid timeGrid_;
private:
/* Branching scheme for a trinomial node. Each node has three
descendants, with the middle branch linked to the node
which is closest to the expectation of the variable. */
class Branching {
public:
Branching();
Size descendant(Size index, Size branch) const;
Real probability(Size index, Size branch) const;
Size size() const;
Integer jMin() const;
Integer jMax() const;
void add(Integer k, Real p1, Real p2, Real p3);
private:
std::vector<Integer> k_;
std::vector<std::vector<Real> > probs_;
Integer kMin_, jMin_, kMax_, jMax_;
};
};
// inline definitions
inline Size TrinomialTree::size(Size i) const {
return i==0 ? 1 : branchings_[i-1].size();
}
inline Real TrinomialTree::underlying(Size i, Size index) const {
if (i==0)
return x0_;
else
return x0_ + (branchings_[i-1].jMin() +
static_cast<Real>(index))*dx(i);
}
inline Size TrinomialTree::descendant(Size i, Size index,
Size branch) const {
return branchings_[i].descendant(index, branch);
}
inline Real TrinomialTree::probability(Size i, Size j, Size b) const {
return branchings_[i].probability(j, b);
}
inline TrinomialTree::Branching::Branching()
: probs_(3), kMin_(QL_MAX_INTEGER), jMin_(QL_MAX_INTEGER),
kMax_(QL_MIN_INTEGER), jMax_(QL_MIN_INTEGER) {}
inline Size TrinomialTree::Branching::descendant(Size index,
Size branch) const {
return k_[index] - jMin_ - 1 + branch;
}
inline Real TrinomialTree::Branching::probability(Size index,
Size branch) const {
return probs_[branch][index];
}
inline Size TrinomialTree::Branching::size() const {
return jMax_ - jMin_ + 1;
}
inline Integer TrinomialTree::Branching::jMin() const {
return jMin_;
}
inline Integer TrinomialTree::Branching::jMax() const {
return jMax_;
}
inline void TrinomialTree::Branching::add(Integer k,
Real p1, Real p2, Real p3) {
// store
k_.push_back(k);
probs_[0].push_back(p1);
probs_[1].push_back(p2);
probs_[2].push_back(p3);
// maintain invariants
kMin_ = std::min(kMin_, k);
jMin_ = kMin_ - 1;
kMax_ = std::max(kMax_, k);
jMax_ = kMax_ + 1;
}
}
#endif
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