Optimal Estimator for Sample Size Using Monte-Carlo Method

Determining the optimal sample size in the Monte Carlo experiments

A convergence criterion for the Monte Carlo estimates will be proposed which can be used as a stopping rule for the Monte Carlo experiments. The proposed criterion searches a convergence band of a given width and length such that the probability of the Monte Carlo sample variance to fall outside of this band is practically null. After the convergence to the process variance realized according t...

A general method for debiasing a Monte Carlo estimator

Consider a stochastic process Xn, n = 0, 1, 2, ...such that EXn → x∞ as n → ∞. The sequence {Xn} may be a deterministic one, obtained by using a numerical integration scheme, or obtained from Monte-Carlo methods involving an approximation to an integral, or a Newton-Raphson iteration to approximate the root of an equation but we will assume that we can sample from the distribution of X1, X2, .....

Sample Size Determination for Regression Models Using Monte Carlo Methods in R - Practical Assessment, Research & Evaluation

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Sample Size Requierement for Monte Carlo - simulations using Latin Hypercube Sampling

Monte Carlo-based Tail Exponent Estimator

In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α−stable distributions. Using large Monte Carlo simulations we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introdu...