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Monte Carlo and Quasi-Monte Carlo Simulation
2014Is this chapter we will learn the basics of pricing derivatives using simulation methods. We will consider both Monte-Carlo and quasi-Monte Carlo but – of course – with a special emphasis on the latter. The aim of our exposition is not to provide a large toolbox for the quantitative analyst, but to help getting started with the topic. QMC-pricing is an
Friedrich Pillichshammer +1 more
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2020
In this chapter, we describe the Monte Carlo (MC) simulation used in this analysis. The purposes of the MC simulation are to estimate the signal acceptance for the \(K_L \!\rightarrow \! \pi ^0 \nu \overline{\nu }\) and \(K_L \!\rightarrow \! \pi ^0 X^0\) decays the acceptance for the normalization mode decays, namely \(K_L \!\rightarrow \! 3\
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In this chapter, we describe the Monte Carlo (MC) simulation used in this analysis. The purposes of the MC simulation are to estimate the signal acceptance for the \(K_L \!\rightarrow \! \pi ^0 \nu \overline{\nu }\) and \(K_L \!\rightarrow \! \pi ^0 X^0\) decays the acceptance for the normalization mode decays, namely \(K_L \!\rightarrow \! 3\
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Faster Monte Carlo simulations
Physical Review E, 1995For Monte Carlo simulations of systems of size [ital M], either kinetic simulations or equilibrium simulations that use the method of Bortz, Kalos, and Liebowitz [J. Comput. Phys. [bold 17], 10 (1975)], the best computer time per event has been [ital O]([ital M][sup 1/2]). We present two methods whose computer time per event is [ital O]([ital M][sup 1/[
Francis Sullivan +2 more
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Monte-Carlo simulation of Callisto’s exosphere [PDF]
Icarus, 2015 We model Callisto's exosphere based on its ice as well as non-ice surface via the use of a Monte-Carlo exosphere model. For the ice component we implement two putative compositions that have been computed from two possible extreme formation scenarios of the satellite.
Vorburger, A. +4 more
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2016
Das Kapitel 3 wendet sich der Monte-Carlo-Simulation von Optionen zu. Allgemeine stochastische Differentialgleichungen mussen hierzu numerisch integriert werden — das erste Thema des Kapitels. Der Prototyp einer solchen Methode ist das Euler-Verfahren, mit dem sich die meisten Beispiele simulieren lassen.
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Das Kapitel 3 wendet sich der Monte-Carlo-Simulation von Optionen zu. Allgemeine stochastische Differentialgleichungen mussen hierzu numerisch integriert werden — das erste Thema des Kapitels. Der Prototyp einer solchen Methode ist das Euler-Verfahren, mit dem sich die meisten Beispiele simulieren lassen.
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2014
The name “Monte Carlo” emerged from the name of the city “Monte Carlo”, famous for its Casino. In the casino there was a roulette where a small button was fixed at the centre of a wheel and the numbers 0–9 were marked at the end of the ten spokes of the wheel. When the button was pressed, the wheel starts rotating. When the wheel stops, a number within
Tanuka Chattopadhyay +1 more
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The name “Monte Carlo” emerged from the name of the city “Monte Carlo”, famous for its Casino. In the casino there was a roulette where a small button was fixed at the centre of a wheel and the numbers 0–9 were marked at the end of the ten spokes of the wheel. When the button was pressed, the wheel starts rotating. When the wheel stops, a number within
Tanuka Chattopadhyay +1 more
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2003
Monte Carlo, Monaco, hosts casinos where games of chance, such as slot machines, are played. Although a slot machine occasionally spews out chunks of tokens to lucky patrons, it, in the long run, earns a predictable fortune for the casino owner. A scientist usually devices her games of chance with various tunable parameters.
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Monte Carlo, Monaco, hosts casinos where games of chance, such as slot machines, are played. Although a slot machine occasionally spews out chunks of tokens to lucky patrons, it, in the long run, earns a predictable fortune for the casino owner. A scientist usually devices her games of chance with various tunable parameters.
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2019
The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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2017
This chapter will provide an introduction into the basic ideas of Monte Carlo simulations , i.e. the importance sampling technique and its application to simulations in various ensembles.
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This chapter will provide an introduction into the basic ideas of Monte Carlo simulations , i.e. the importance sampling technique and its application to simulations in various ensembles.
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Overrelaxation and Monte Carlo simulation
Physical Review D, 1987I study a simple variation of the algorithm of Metropolis et al. for simulating statistical systems. The trial changes in any given variable are taken from a region of phase space far from the old value but involving only small changes in energy. This results in correlation times which are short compared to the usual applications of the algorithm of ...
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