Special Issue on 

Stochastic Simulation Method and Its Applications

Stochastic modeling is a form of financial modeling that includes one or more random variables. The purpose of such modeling is to estimate how probable outcomes are within a forecast to predict conditions for different situations. The Monte Carlo simulation is one example of a stochastic model; when used for portfolio evaluation, various simulations of how a portfolio may perform are developed based on probability distributions of individual stock returns.The goal of this special issue is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in this area of stochastic simulation method and its applications.

In this special issue, we invite front-line researchers and authors to submit original research and review articles that explore stochastic simulation method and its applications. In this special issue, potential topics include, but are not limited to:

• Stochastic modeling
• Monte carlo simulation
• Discrete-event simulation
• Continuous simulation
• Combined simulation
• Random number generators
• Applications of stochastic simulation methods

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly specify the “Special Issue” under your manuscript title. The research field “Special Issue - Stochastic Simulation Method and Its Applications” should be selected during your submission.

Special Issue timetable:

Guest Editor:

For further questions or inquiries

Please contact the Editorial Assistant at

jamp@scirp.org