Quantitative Finance Collector is a blog on Quantitative finance analysis, methods in mathematical finance focusing on derivative pricing, quantitative trading and quantitative risk management.
Jan
15
Attended a training of NAG Toolbox for MATLAB today (NAG is short for Numerical Algorithms Group), nice presentation and persuasive performance against Matlab toolbox. I will soon get a licence and start to experience myself.
Anyway, I got to know two sites after the training, first one is deal.II, which is a finite element differential equations analysis library aiming to enable rapid development of modern finite element codes, using among other aspects adaptive meshes and a wide array of tools classes often used in finite element program. As stated on its webpage: "deal.II is a C++ program library targeted at the computational solution of partial differential equations using adaptive finite elements. It uses state-of-the-art programming techniques to offer you a modern interface to the complex data structures and algorithms required." It should be very useful for those people playing often with PDE numerical solution.
The other site is Walking randomly, a blog where the author randomly collects things including mathematics, physics, vintage computing, Linux, pocket PCs, Android, music and programming. I am especially interested in its Matlab, R, NAG, and statistics categories.
Have a nice weekend.
Anyway, I got to know two sites after the training, first one is deal.II, which is a finite element differential equations analysis library aiming to enable rapid development of modern finite element codes, using among other aspects adaptive meshes and a wide array of tools classes often used in finite element program. As stated on its webpage: "deal.II is a C++ program library targeted at the computational solution of partial differential equations using adaptive finite elements. It uses state-of-the-art programming techniques to offer you a modern interface to the complex data structures and algorithms required." It should be very useful for those people playing often with PDE numerical solution.
The other site is Walking randomly, a blog where the author randomly collects things including mathematics, physics, vintage computing, Linux, pocket PCs, Android, music and programming. I am especially interested in its Matlab, R, NAG, and statistics categories.
Have a nice weekend.
Sep
3
Recently I have been working on pricing a high dimensional (4 dimension, actually) derivative via partial differencial equation (PDE), which can be solved numerically by Finite Element or Finite Difference method. Indeed Matlab has a PDE toolbox to use, however, as I know, this PDE toolbox can only calculate two dimensional problem, for instance, stock and time dimension as Black Scholes model does.
For your attention, I found an excellent Finite Element package named Getfem++ written in C++, as its webpage says, "The Getfem++ project focuses on the development of a generic and efficient C++ library for finite element methods. The goal is to provide a library allowing the computation of any elementary matrix (even for mixed finite element methods) on the largest class of methods and elements, and for arbitrary dimension (i.e. not only 2D and 3D problems). " what's more interesting is this library can be linked easily to Matlab.
We know Finite Element method is an alternative to Finite Difference discretization of the BS and other equations in the price resp. the log-price space variable. The advantage of FE is that it gives convergent deterministic approximations of the option price under realistic, low smoothness assumptions on the payoff function, as e.g. for binary contracts and in particular allow a higher rate of convergence that that achievable with Monte Carlo simulations.
For your attention, I found an excellent Finite Element package named Getfem++ written in C++, as its webpage says, "The Getfem++ project focuses on the development of a generic and efficient C++ library for finite element methods. The goal is to provide a library allowing the computation of any elementary matrix (even for mixed finite element methods) on the largest class of methods and elements, and for arbitrary dimension (i.e. not only 2D and 3D problems). " what's more interesting is this library can be linked easily to Matlab.
We know Finite Element method is an alternative to Finite Difference discretization of the BS and other equations in the price resp. the log-price space variable. The advantage of FE is that it gives convergent deterministic approximations of the option price under realistic, low smoothness assumptions on the payoff function, as e.g. for binary contracts and in particular allow a higher rate of convergence that that achievable with Monte Carlo simulations.
