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PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO
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
doaj +1 more source
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions [PDF]
Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo
Livingstone, Samuel +5 more
core +1 more source
Multilevel Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics [PDF]
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
core +1 more source
Automatic differentiable Monte Carlo: Theory and application
Differentiable programming has emerged as a key programming paradigm empowering rapid developments of deep learning while its applications to important computational methods such as Monte Carlo remain largely unexplored.
Shi-Xin Zhang, Zhou-Quan Wan, Hong Yao
doaj +1 more source
This paper explores how far the scientific discovery process can be automated. Using the identification of causally significant flow structures in two-dimensional turbulence as an example, it probes how far the usual procedure of planning experiments to test hypotheses can be substituted by `blind' randomised experiments, and notes that the increased ...
openaire +3 more sources
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
doaj +1 more source
Quantum-Assisted Variational Monte Carlo [PDF]
Longfei Chang, Zhendong Li, Wei-Hai Fang
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Frequency-resolved Monte Carlo
We adapt the Quantum Monte Carlo method to the cascaded formalism of quantum optics, allowing us to simulate the emission of photons of known energy. Statistical processing of the photon clicks thus collected agrees with the theory of frequency-resolved ...
Juan Camilo López Carreño +2 more
doaj +1 more source
Hybrid Monte Carlo on Hilbert spaces [PDF]
The Hybrid Monte Carlo (HMC) algorithm provides a framework for sampling from complex, high-dimensional target distributions. In contrast with standard Markov chain Monte Carlo (MCMC) algorithms, it generates nonlocal, nonsymmetric moves in the state ...
Beskos, A +15 more
core +1 more source
Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable.
Bardenet Rémi
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