/usr/include/ql/processes/batesprocess.hpp is in libquantlib0-dev 1.4-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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/*
Copyright (C) 2008 Klaus Spanderen
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 batesprocess.hpp
\brief Bates stochastic process, Heston process plus compound Poisson
process plus log-normal jump diffusion size
*/
#ifndef quantlib_bates_process_hpp
#define quantlib_bates_process_hpp
#include <ql/processes/hestonprocess.hpp>
#include <ql/math/distributions/normaldistribution.hpp>
namespace QuantLib {
//! Square-root stochastic-volatility Bates process
/*! This class describes the square root stochastic volatility
process incl jumps governed by
\f[
\begin{array}{rcl}
dS(t, S) &=& (r-d-\lambda m) S dt +\sqrt{v} S dW_1 + (e^J - 1) S dN \\
dv(t, S) &=& \kappa (\theta - v) dt + \sigma \sqrt{v} dW_2 \\
dW_1 dW_2 &=& \rho dt \\
\omega(J) &=& \frac{1}{\sqrt{2\pi \delta^2}}
\exp\left[-\frac{(J-\nu)^2}{2\delta^2}\right]
\end{array}
\f]
\ingroup processes
*/
class BatesProcess : public HestonProcess {
public:
BatesProcess(const Handle<YieldTermStructure>& riskFreeRate,
const Handle<YieldTermStructure>& dividendYield,
const Handle<Quote>& s0,
Real v0, Real kappa,
Real theta, Real sigma, Real rho,
Real lambda, Real nu, Real delta,
HestonProcess::Discretization d
= HestonProcess::FullTruncation);
Size factors() const;
Disposable<Array> drift(Time t, const Array& x) const;
Disposable<Array> evolve(Time t0, const Array& x0,
Time dt, const Array& dw) const;
Real lambda() const;
Real nu() const;
Real delta() const;
private:
const Real lambda_, delta_, nu_, m_;
const CumulativeNormalDistribution cumNormalDist_;
};
}
#endif
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