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