scholarly journals A class of new modulus-based matrix splitting methods for linear complementarity problem

2021 ◽  
Author(s):  
Shiliang Wu ◽  
Cuixia Li
Keyword(s):  
Linear Complementarity Problem ◽  
Complementarity Problem ◽  
Linear Complementarity ◽  
Splitting Methods ◽  
Matrix Splitting

scholarly journals Relaxed Modulus-Based Matrix Splitting Methods for the Linear Complementarity Problem

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 503
Author(s):  
Shiliang Wu ◽  
Cuixia Li ◽  
Praveen Agarwal
Keyword(s):  
Fixed Point ◽  
Linear Complementarity Problem ◽  
Complementarity Problem ◽  
Sufficient Conditions ◽  
Linear Complementarity ◽  
Splitting Methods ◽  
Matrix Splitting ◽  
Numerical Examples ◽  
Iteration Methods ◽  
Point Form

In this paper, we obtain a new equivalent fixed-point form of the linear complementarity problem by introducing a relaxed matrix and establish a class of relaxed modulus-based matrix splitting iteration methods for solving the linear complementarity problem. Some sufficient conditions for guaranteeing the convergence of relaxed modulus-based matrix splitting iteration methods are presented. Numerical examples are offered to show the efficacy of the proposed methods.

scholarly journals COMPONENTWISE SPLITTING METHODS FOR PRICING AMERICAN OPTIONS UNDER STOCHASTIC VOLATILITY

2007 ◽  
Vol 10 (02) ◽  
pp. 331-361 ◽  
Author(s):  
SAMULI IKONEN ◽  
JARI TOIVANEN
Keyword(s):  
Stochastic Volatility ◽  
Linear Complementarity Problem ◽  
Complementarity Problem ◽  
American Options ◽  
Splitting Method ◽  
Linear Complementarity ◽  
Splitting Methods ◽  
Time Step ◽  
Operator Splitting Methods ◽  
Volatility Model

Efficient numerical methods for pricing American options using Heston's stochastic volatility model are proposed. Based on this model the price of a European option can be obtained by solving a two-dimensional parabolic partial differential equation. For an American option the early exercise possibility leads to a lower bound for the price of the option. This price can be computed by solving a linear complementarity problem. The idea of operator splitting methods is to divide each time step into fractional time steps with simpler operators. This paper proposes componentwise splitting methods for solving the linear complementarity problem. The basic componentwise splitting decomposes the discretized problem into three linear complementarity problems with tridiagonal matrices. These problems can be efficiently solved using the Brennan and Schwartz algorithm, which was originally introduced for American options under the Black and Scholes model. The accuracy of the componentwise splitting method is increased by applying the Strang symmetrization. The good accuracy and the computational efficiency of the proposed symmetrized splitting method are demonstrated by numerical experiments.

scholarly journals Two-step modulus-based matrix splitting iteration method for horizontal linear complementarity problems

Filomat ◽  
2020 ◽  
Vol 34 (7) ◽  
pp. 2171-2184
Author(s):  
Lu Jia ◽  
Xiang Wang ◽  
Xuan-Sheng Wang
Keyword(s):  
Theoretical Analysis ◽  
Linear Complementarity Problem ◽  
Iteration Method ◽  
Complementarity Problem ◽  
Numerical Experiments ◽  
Complementarity Problems ◽  
Linear Complementarity Problems ◽  
Linear Complementarity ◽  
Matrix Splitting ◽  
Splitting Iteration Method

The modulus-based matrix splitting iteration has received substantial attention as a momentous tool for complementarity problems. For the purpose of solving the horizontal linear complementarity problem, we introduce the two-step modulus-based matrix splitting iteration method. We also show the theoretical analysis of the convergence. Numerical experiments illustrate the effectiveness of the proposed approach.

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