Stochastic Processes And Monte Carlo Simulation

Abstract

This article analyzes the theoretical foundations and practical application of the methodology of stochastic processes and Monte Carlo simulation. It highlights the concept of randomness, mathematical modeling methods of stochastic processes, and their significance in real systems— particularly in assessing financial market risks. Through the Monte Carlo method, numerous repeated simulations are conducted to determine the probable outcomes of complex processes and develop risk management strategies. This approach helps investors and financial analysts identify potential risks and returns under various market conditions. The article discusses the advantages and limitations of this methodology based on theoretical concepts, modeling principles, and practical examples.