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Communication Papers of the 21st Conference on Computer Science and Intelligence Systems (FedCSIS)

Annals of Computer Science and Information Systems, Volume 49

A multithreaded Java implementation of Monte Carlo simulation for Value-at-Risk estimation

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DOI: http://dx.doi.org/10.15439/2026F1699

Citation: Paweł Borowiecki,

Full text

Abstract. The continuous development of computers has made software that performs calculations in various fields of science, including economics, significantly more efficient. This paper presents two parallel implementations developed in Java and a performance analysis of Monte Carlo simulations for Value-at-Risk estimation, using geometric Brownian motions and a log-normal distribution of returns. The first implementation variant utilizes data parallelism and parallel loops. The second implementation variant, in addition to data parallelism and parallel loops, also utilizes task parallelism and the fork-join model. Software tests were conducted on three computers equipped with Intel processors. The main area of research was the dependence of simulation execution time and speedup on the number of threads and data size. The program's performance was accelerated by more than 42 times.

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