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A Nonparametric Simulated Maximum Likelihood Estimation Method.

Fermanian, J.D.; Salanie, B. - 2001

This paper presents a new simulated maximum-likelihood method that rests on estimating the likelihood nonparametrically on a simulated sample. We prove that this method, which can be used on very general models, is consistent and asymptotically efficient.

Persistent link: https://www.econbiz.de/10005780756

On the Number of Bootstrap Repetitions for Bootstrap Standard Errors, Confidence Intervals, and Tests

Andrews, Donald W.K.; Buchinsky, Moshe - Cowles Foundation for Research in Economics, Yale University - 1997

This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap standard errors, confidence intervals, and tests. For each of these problems, the paper provides a three-step method for choosing B to achieve a desired level of accuracy. Accuracy is measured by the...

Persistent link: https://www.econbiz.de/10004990816

Non-Parametric Specification Tests for Conditional Duration Models.

Fernandes, M.; Grammig, J. - Department of Economics, European University Institute - 2000

This paper deals with the estimation and testing of conditional duration models by looking at the density and baseline hazard functions. More precisely, we focus on the distance between the aprametric density (or hazard rate) function implied by the duration process and its non-parametric estimate.

Persistent link: https://www.econbiz.de/10005816412

Equality Restricted Random Variables: Densities and Sampling Algorithms

Kleibergen, F. - Econometrisch Instituut, Faculteit der Economische … - 1996

Many common statistical models can be specified as linear models with restrictions imposed on the parameters. A large amount of these models impose restrictions which do not allow for the analytical construction of the probability density function (pdf) of the parameters given the restrictions....

Persistent link: https://www.econbiz.de/10005660914

Decomposing Portfolio Value-at-Risk: A General Analysis

Hallerbach, Winfried G. - Tinbergen Instituut - 1999

the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …

Persistent link: https://www.econbiz.de/10011256282