MONTE CARLO METHOD FOR MODELING THE ASSESSMENT OF POTENTIAL SCENARIOS OF MARKET BEHAVIOR AND THE IMPACT OF RANDOM EVENTS ON THE PORTFOLIO
Section: GENERAL SECTION
Authors:
1.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation
Russian Federation
2.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
(Departtment of Computer Science and Information Systems, assistant professor)
Voronezh, Voronezh, Russian Federation
Voronezh, Voronezh, Russian Federation
3.
Voronezh State University of Forestry and Technologies named after G.F. Mo-rozov
Russian Federation
Russian Federation
4.
Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation
Russian Federation
Type:
Сonference article
Published:
18.06.2025
Subject area:
004.94
Language:
Russian
Keywords:
Monte Carlo method, stochastic modeling, financial risks, investment portfolio, Black-Scholes model
Abstract (English):
The Monte Carlo method is one of the most effective tools for modeling market scenarios and analyzing financial risks. This article discusses the mathematical foundations of the method, its application to evaluate investment portfolios, as well as the use of the Black-Scholes model to evaluate the value of derivative financial instruments. An example of using the method to analyze the impact of random macroeconomic events on an investor's portfolio is given. The advantages of the method, its accuracy and computational complexity, as well as its role in modern automated trading systems are discussed.
The Monte Carlo method is one of the most effective tools for modeling market scenarios and analyzing financial risks. This article discusses the mathematical foundations of the method, its application to evaluate investment portfolios, as well as the use of the Black-Scholes model to evaluate the value of derivative financial instruments. An example of using the method to analyze the impact of random macroeconomic events on an investor's portfolio is given. The advantages of the method, its accuracy and computational complexity, as well as its role in modern automated trading systems are discussed.
Keywords:
Monte Carlo method, stochastic modeling, financial risks, investment portfolio, Black-Scholes model
Monte Carlo method, stochastic modeling, financial risks, investment portfolio, Black-Scholes model
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