Results 11 to 20 of about 128,537,122 (247)
High performance Monte Carlo computation for finance risk data analysis [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Finance risk management has been playing an increasingly important role in the finance sector, to analyse finance data and to prevent any potential crisis ...
Zhao, Yu
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Multilevel Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics [PDF]
, 2012 We show how to extend a recently proposed multi-level Monte Carlo approach to the continuous time Markov chain setting, thereby greatly lowering the computational complexity needed to compute expected values of functions of the state of the system to a ...
Anderson, David +3 more
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Crossed source-detector geometry for a novel spray diagnostic: Monte Carlo simulation and analytical results [PDF]
, 2005 Sprays and other industrially relevant turbid media can be quantitatively characterized by light scattering. However, current optical diagnostic techniques generate errors in the intermediate scattering regime where the average number of light ...
Churmakov, D. Y. +4 more
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Mean exit times and the multilevel Monte Carlo method [PDF]
, 2013 Numerical methods for stochastic differential equations are relatively inefficient when used to approximate mean exit times. In particular, although the basic Euler–Maruyama method has weak order equal to one for approximating the expected value of the ...
Roj, Mikolaj +4 more
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Mapping Robot Singularities through the Monte Carlo Method
Applied Sciences, 2022 In addition to other things, a robot’s design also determines its singularity configurations and points in the workspace. In designing the robot’s working trajectory, one of the main issues of robot steering is avoiding singularities.
Tomáš Stejskal +2 more
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The Monte Carlo method of random simulation samples
Mercados y Negocios, 2023 The Monte Carlo method is one of the most powerful mathematical techniques that, through calculation, analyzes risk and allows solving physical and mathematical problems through computer programs.
Juan Gaytán Cortés
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Why Monte Carlo Simulations are Inferences and not Experiments [PDF]
, 2012 Monte Carlo Simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the ...
John D. Norton +3 more
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E-Jurnal Matematika, 2017 Contract options are the most important part of an investment strategy. An option is a contract that entitles the owner or holder to sell an asset on a designated maturity date.
DEWA AYU AGUNG PUTRI RATNASARI +2 more
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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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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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