Numerical Algorithms Group
ثبت نشده
چکیده
The newly emerging science of studying complex systems is being applied to global finance markets by a new joint academic/commercial venture, the Oxford Centre for Computational Finance. Multi-agent-based models are used to create artificial markets and to perform dynamic tests of new methods for option pricing and the like. At the same time, this laboratory for analysis of live-market data is gearing to provide sponsoring organizations with more immediate commercial benefits, such as new types of derivatives and stress-tested algorithms that fine-tune Black-Scholes and other traditional optionpricing methods.
منابع مشابه
On the numerical solution of generalized Sylvester matrix equations
The global FOM and GMRES algorithms are among the effective methods to solve Sylvester matrix equations. In this paper, we study these algorithms in the case that the coefficient matrices are real symmetric (real symmetric positive definite) and extract two CG-type algorithms for solving generalized Sylvester matrix equations. The proposed methods are iterative projection metho...
متن کاملNumerical solution of a system of fuzzy polynomial equations by modified Adomian decomposition method
In this paper, we present some efficient numerical algorithm for solving system of fuzzy polynomial equations based on Newton's method. The modified Adomian decomposition method is applied to construct the numerical algorithms. Some numerical illustrations are given to show the efficiency of algorithms.
متن کاملA New Paradigm for Assessing the Effectiveness of Up-Peak Group Control Algorithms
Elevator group control is critical to the optimal operation of elevator traffic systems under general traffic conditions. In the last 20 years, new elevator group control algorithms have become available for use under up-peak traffic conditions. These up-peak algorithms can be generally classified into three categories: static sectoring, dynamic sectoring and destination group control. It is cu...
متن کاملSolving random inverse heat conduction problems using PSO and genetic algorithms
The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...
متن کاملUsing Neural Networks and Genetic Algorithms for Modelling and Multi-objective Optimal Heat Exchange through a Tube Bank
In this study, by using a multi-objective optimization technique, the optimal design points of forced convective heat transfer in tubular arrangements were predicted upon the size, pitch and geometric configurations of a tube bank. In this way, the main concern of the study is focused on calculating the most favorable geometric characters which may gain to a maximum heat exchange as well as a m...
متن کاملApproximate Pareto Optimal Solutions of Multi objective Optimal Control Problems by Evolutionary Algorithms
In this paper an approach based on evolutionary algorithms to find Pareto optimal pair of state and control for multi-objective optimal control problems (MOOCP)'s is introduced. In this approach, first a discretized form of the time-control space is considered and then, a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002