endeulerdiscretization.cpp

/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
 
/*
 Copyright (C) 2008 Frank Hövermann
 
 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.
*/
 
#include <ql/processes/endeulerdiscretization.hpp>
 
namespace QuantLib {
 
    Array EndEulerDiscretization::drift(const StochasticProcess& process,
                                        Time t0, const Array& x0,
                                        Time dt) const {
        return process.drift(t0+dt, x0)*dt;
    }
 
    Real EndEulerDiscretization::drift(const StochasticProcess1D& process,
                                       Time t0, Real x0, Time dt) const {
        return process.drift(t0+dt, x0)*dt;
    }
 
    Matrix EndEulerDiscretization::diffusion(const StochasticProcess& process,
                                             Time t0,
                                             const Array& x0,
                                             Time dt) const {
        return process.diffusion(t0+dt, x0) * std::sqrt(dt);
    }
 
    Real EndEulerDiscretization::diffusion(const StochasticProcess1D& process,
                                           Time t0, Real x0, Time dt) const {
        return process.diffusion(t0+dt, x0) * std::sqrt(dt);
    }
 
    Matrix EndEulerDiscretization::covariance(const StochasticProcess& process,
                                              Time t0,
                                              const Array& x0,
                                              Time dt) const {
        Matrix sigma = process.diffusion(t0+dt, x0);
        Matrix result = sigma*transpose(sigma)*dt;
        return result;
    }
 
    Real EndEulerDiscretization::variance(const StochasticProcess1D& process,
                                          Time t0, Real x0, Time dt) const {
        Real sigma = process.diffusion(t0+dt, x0);
        return sigma*sigma*dt;
    }
 
}