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Multilevel Monte Carlo Path Simulation [PDF]
Operations Research, 2008 We show that multigrid ideas can be used to reduce the computational complexity of estimating an expected value arising from a stochastic differential equation using Monte Carlo path simulations. In the simplest case of a Lipschitz payoff and a Euler discretisation, the computational cost to achieve an accuracy of O(ϵ) is reduced from O(ϵ−3) to O(ϵ−2 (
M. Giles
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Jurnal Lebesgue, 2023 The development of palm oil production is quite rapid in Indonesia. The method used to estimate inventory costs in this study is the Monte Carlo Simulation method. Monte Carlo simulation is used in structuring optimal raw material policies.
Cindy Artika +2 more
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The OpenGATE ecosystem for Monte Carlo simulation in medical physics
Physics in Medicine and Biology, 2022 This paper reviews the ecosystem of GATE, an open-source Monte Carlo toolkit for medical physics. Based on the shoulders of Geant4, the principal modules (geometry, physics, scorers) are described with brief descriptions of some key concepts (Volume ...
D. Sarrut +20 more
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Comparative evaluations of the Monte Carlo-based light propagation simulation packages for optical imaging [PDF]
Journal of Innovative Optical Health Sciences, 2018 Monte Carlo simulation of light propagation in turbid medium has been studied for years. A number of software packages have been developed to handle with such issue.
Lin Wang, Shenghan Ren, Xueli Chen
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Parallel Monte Carlo simulations [PDF]
Physical Review E, 1995 The Monte Carlo (MC) method is an important tool in sampling the state space of a chosen statistical ensemble. It allows the study of thermodynamic averages of configurational properties by generating ``moves'' in a system and accepting or rejecting the thus generated new state depending on the energy of the new system and/or a random choice.
Esselink, K., Loyens, L.D.J.C., Smit, B.
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MENENTUKAN HARGA OPSI DENGAN METODE MONTE CARLO BERSYARAT MENGGUNAKAN BARISAN KUASI ACAK FAURE
E-Jurnal Matematika, 2021 An option contract is a contract that gives the owner the right to sell or even to buy an asset at the predetermined price and period time. The conditional Monte Carlo is one of the several methods that is used to determine the option price which in the ...
PUTU WIDYA ASTUTI +2 more
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Jambura Journal of Mathematics, 2023 Value at Risk (VaR) and Tail Value at Risk (TVaR) are two measures that are commonly used to quantify the risk associated with a loss severity distribution.
Ruhiyat Ruhiyat +2 more
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Optimal Control Methods of Experiment Times in System-of-Systems Combat Computer Simulation [PDF]
ITM Web of Conferences, 2019 In the process of scheme optimization, in order to eliminate the influence of random factor, it needs to conduct computer simulation of Monte Carlo. Therefore, it is proposed to introduce confidence interval into systemof-systems combat simulation, and ...
Zhao Zhiqiang, Zhou Feiyue
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STARlight: A Monte Carlo simulation program for ultra-peripheral collisions of relativistic ions [PDF]
Computer Physics Communications, 2016 Ultra-peripheral collisions (UPCs) have been a significant source of study at RHIC and the LHC. In these collisions, the two colliding nuclei interact electromagnetically, via two-photon or photonuclear interactions, but not hadronically; they ...
S. Klein +4 more
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PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO
E-Jurnal Matematika, 2012 Value at Risk (VaR) is the maximum potential loss on a portfolio based on the probability at a certain time. In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data.
WAYAN ARTHINI +2 more
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