| 1 | /* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */ |
| 2 | |
| 3 | /* |
| 4 | Copyright (C) 2004, 2005 StatPro Italia srl |
| 5 | |
| 6 | This file is part of QuantLib, a free-software/open-source library |
| 7 | for financial quantitative analysts and developers - http://quantlib.org/ |
| 8 | |
| 9 | QuantLib is free software: you can redistribute it and/or modify it |
| 10 | under the terms of the QuantLib license. You should have received a |
| 11 | copy of the license along with this program; if not, please email |
| 12 | <quantlib-dev@lists.sf.net>. The license is also available online at |
| 13 | <http://quantlib.org/license.shtml>. |
| 14 | |
| 15 | This program is distributed in the hope that it will be useful, but WITHOUT |
| 16 | ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
| 17 | FOR A PARTICULAR PURPOSE. See the license for more details. |
| 18 | */ |
| 19 | |
| 20 | /*! \file eulerdiscretization.hpp |
| 21 | \brief Euler discretization for stochastic processes |
| 22 | */ |
| 23 | |
| 24 | #ifndef quantlib_euler_discretization_hpp |
| 25 | #define quantlib_euler_discretization_hpp |
| 26 | |
| 27 | #include <ql/stochasticprocess.hpp> |
| 28 | |
| 29 | namespace QuantLib { |
| 30 | |
| 31 | //! Euler discretization for stochastic processes |
| 32 | /*! \ingroup processes */ |
| 33 | class EulerDiscretization |
| 34 | : public StochasticProcess::discretization, |
| 35 | public StochasticProcess1D::discretization { |
| 36 | public: |
| 37 | |
| 38 | /*! Returns an approximation of the drift defined as |
| 39 | \f$ \mu(t_0, \mathbf{x}_0) \Delta t \f$. |
| 40 | */ |
| 41 | Array drift(const StochasticProcess&, Time t0, const Array& x0, Time dt) const override; |
| 42 | /*! Returns an approximation of the drift defined as |
| 43 | \f$ \mu(t_0, x_0) \Delta t \f$. |
| 44 | */ |
| 45 | Real drift(const StochasticProcess1D&, Time t0, Real x0, Time dt) const override; |
| 46 | |
| 47 | /*! Returns an approximation of the diffusion defined as |
| 48 | \f$ \sigma(t_0, \mathbf{x}_0) \sqrt{\Delta t} \f$. |
| 49 | */ |
| 50 | Matrix diffusion(const StochasticProcess&, Time t0, const Array& x0, Time dt) const override; |
| 51 | /*! Returns an approximation of the diffusion defined as |
| 52 | \f$ \sigma(t_0, x_0) \sqrt{\Delta t} \f$. |
| 53 | */ |
| 54 | Real diffusion(const StochasticProcess1D&, Time t0, Real x0, Time dt) const override; |
| 55 | |
| 56 | /*! Returns an approximation of the covariance defined as |
| 57 | \f$ \sigma(t_0, \mathbf{x}_0)^2 \Delta t \f$. |
| 58 | */ |
| 59 | Matrix covariance(const StochasticProcess&, Time t0, const Array& x0, Time dt) const override; |
| 60 | /*! Returns an approximation of the variance defined as |
| 61 | \f$ \sigma(t_0, x_0)^2 \Delta t \f$. |
| 62 | */ |
| 63 | Real variance(const StochasticProcess1D&, Time t0, Real x0, Time dt) const override; |
| 64 | }; |
| 65 | |
| 66 | } |
| 67 | |
| 68 | |
| 69 | #endif |
| 70 | |
| 71 | |