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has been cited by the following article:

• TITLE: Non-Negativity Preserving Numerical Algorithms for Problems in Mathematical Finance

  AUTHORS: Yuan Yuan

  KEYWORDS: Stochastic Differential Equations, Numerical Methods, Splitting-Step Algorithm, Non-Negativity, Convergence, Simulation

  JOURNAL NAME: Applied Mathematics, Vol.9 No.3, March 30, 2018

  ABSTRACT: We give a study result to analyze a rather different, semi-analytical numerical algorithms based on splitting-step methods with their applications to mathematical finance. As certain subsistent numerical schemes may fail due to producing negative values for financial variables which require non-negativity preserving. These algorithms which we are analyzing preserve not only the non-negativity, but also the character of boundaries (natural, reflecting, absorbing, etc.). The derivatives of the CIR process and the Heston model are being extensively studied. Beyond plain vanilla European options, we creatively apply our splitting-step methods to a path-dependent option valuation. We compare our algorithms to a class of numerical schemes based on Euler discretization which are prevalent currently. The comparisons are given with respect to both accuracy and computational time for the European call option under the CIR model whereas with respect to convergence rate for the path-dependent option under the CIR model and the European call option under the Heston model.