Variance reduction for Monte Carlo simulation in a stochastic volatility environment

With the prevalence of credit system, the stipulation of “academic warning” is written into the teaching management constitution by more colleges and universities. However, the establishment of this stipulation hasn’t formed unified and scientific standards at present. This paper aims at studying the credit setting of academic warning through the method of Monte Carlo simulation, and at applying multivariate normal distribution and variance reduction techniques to calculate relatively reasonable academic warning credit line, which provides a new train of thought and a universal method for colleges and universities to set specific standards.

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Variance reduction of Monte Carlo and randomized quasi-Monte Carlo estimators for stochastic volatility models in finance

WSC'99. 1999 Winter Simulation Conference Proceedings. 'Simulation - A Bridge to the Future' (Cat. No.99CH37038) ◽

10.1145/324138.324237 ◽

1999 ◽

Cited By ~ 5

Author(s):

Hatem Ben Ameur ◽

Pierre L'Ecuyer ◽

Christiane Lemieux

Keyword(s):

Monte Carlo ◽

Stochastic Volatility ◽

Variance Reduction ◽

Stochastic Volatility Models ◽

Quasi Monte Carlo ◽

Volatility Models

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Variance-Reduction Methods for Monte Carlo Simulation of Radiation Transport

Frontiers in Physics ◽

10.3389/fphy.2021.718873 ◽

2021 ◽

Vol 9 ◽

Author(s):

Salvador García-Pareja ◽

Antonio M. Lallena ◽

Francesc Salvat

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Variance Reduction ◽

Radiation Transport ◽

Scattering Method ◽

Variance Reduction Techniques ◽

Simulation Efficiency ◽

Reduction Techniques ◽

Exponential Transform ◽

Reduction Methods

After a brief description of the essentials of Monte Carlo simulation methods and the definition of simulation efficiency, the rationale for variance-reduction techniques is presented. Popular variance-reduction techniques applicable to Monte Carlo simulations of radiation transport are described and motivated. The focus is on those techniques that can be used with any transport code, irrespective of the strategies used to track charged particles; they operate by manipulating either the number and weights of the transported particles or the mean free paths of the various interaction mechanisms. The considered techniques are 1) splitting and Russian roulette, with the ant colony method as builder of importance maps, 2) exponential transform and interaction-forcing biasing, 3) Woodcock or delta-scattering method, 4) interaction forcing, and 5) proper use of symmetries and combinations of different techniques. Illustrative results from analog simulations (without recourse to variance-reduction) and from variance-reduced simulations of various transport problems are presented.

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Monte Carlo Simulation and Improvement of Variance Reduction Techniques

DEStech Transactions on Computer Science and Engineering ◽

10.12783/dtcse/mmsta2017/19628 ◽

2018 ◽

Cited By ~ 1

Author(s):

Zi-xuan CAO ◽

Zhuo YANG ◽

Kun LIU ◽

Ze-wei ZHANG ◽

Zi-ting LUO ◽

...

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Variance Reduction ◽

Variance Reduction Techniques ◽

Reduction Techniques

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Monte Carlo Simulation of Characteristic Secondary Fluorescence in Electron Probe Microanalysis of Homogeneous Samples Using the Splitting Technique

Microscopy and Microanalysis ◽

10.1017/s1431927615000495 ◽

2015 ◽

Vol 21 (3) ◽

pp. 753-758 ◽

Cited By ~ 5

Author(s):

Mauricio Petaccia ◽

Silvina Segui ◽

Gustavo Castellano

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Electron Probe Microanalysis ◽

Electron Probe ◽

Variance Reduction ◽

Fluorescence Enhancement ◽

Radiation Transport ◽

X Rays ◽

X Ray ◽

Secondary Fluorescence

AbstractElectron probe microanalysis (EPMA) is based on the comparison of characteristic intensities induced by monoenergetic electrons. When the electron beam ionizes inner atomic shells and these ionizations cause the emission of characteristic X-rays, secondary fluorescence can occur, originating from ionizations induced by X-ray photons produced by the primary electron interactions. As detectors are unable to distinguish the origin of these characteristic X-rays, Monte Carlo simulation of radiation transport becomes a determinant tool in the study of this fluorescence enhancement. In this work, characteristic secondary fluorescence enhancement in EPMA has been studied by using the splitting routines offered by PENELOPE 2008 as a variance reduction alternative. This approach is controlled by a single parameter NSPLIT, which represents the desired number of X-ray photon replicas. The dependence of the uncertainties associated with secondary intensities on NSPLIT was studied as a function of the accelerating voltage and the sample composition in a simple binary alloy in which this effect becomes relevant. The achieved efficiencies for the simulated secondary intensities bear a remarkable improvement when increasing the NSPLIT parameter; although in most cases an NSPLIT value of 100 is sufficient, some less likely enhancements may require stronger splitting in order to increase the efficiency associated with the simulation of secondary intensities.

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