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Using a Bootstrap Method to choose the Sample Fraction in Tail Index Estimation

Danielsson, J.; de Haan, L.; Peng, L.; de Vries, C.G. - 1997

We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the samplefraction, in the sense of minimal mean squared error, which is needed for tail index estimation. Unlike previous methodsour procedure is fully self contained. In particular, the...

Persistent link: https://www.econbiz.de/10010324719

Fast methods for jackknifing inequality indices

Karoly, Lynn A.; Schröder, Carsten - 2013

The jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a …

Persistent link: https://www.econbiz.de/10010335356

Portfolio Choice and Estimation Risk: A Comparison of Bayesian to Heuristic Approaches

Herold, Ulf; Maurer, Raimond - 2002

approach introduced by Michaud (1998), resampling efficiency. Michaud argues that the limitations of MV efficiency in practice … that leads to new procedures that can reduce estimation risk. Resampling efficiency has been contrasted to standard … fill this gap. Optimal portfolios based on the Bayes/Stein estimator and resampling efficiency are compared in an empirical …

Persistent link: https://www.econbiz.de/10010316250

Portfolio construction by using different risk models: a comparison among diverse economic scenarios

Hunjra, Ahmed Imran; Alawi, Suha Mahmoud; Colombage, Sisira - In: Risks 8 (2020) 4, pp. 1-23

We aim to construct portfolios by employing different risk models and compare their performance in order to understand their appropriateness for effective portfolio management for investors. Mean variance (MV), semi variance (SV), mean absolute deviation (MaD) and conditional value at risk...

Persistent link: https://www.econbiz.de/10013200659

Efficient optimization of the likelihood function in Gaussian process modelling

Butler, A.; Haynes, R.D.; Humphries, T.D.; Ranjan, P. - In: Computational Statistics & Data Analysis 73 (2014) C, pp. 40-52

Gaussian Process (GP) models are popular statistical surrogates used for emulating computationally expensive computer simulators. The quality of a GP model fit can be assessed by a goodness of fit measure based on optimized likelihood. Finding the global maximum of the likelihood function for a...

Persistent link: https://www.econbiz.de/10010871407

Portfolio construction by using different risk models: a comparison among diverse economic scenarios

Hunjra, Ahmed Imran; Alawi, Suha Mahmoud; Colombage, Sisira - In: Risks : open access journal 8 (2020) 4/126, pp. 1-23

Persistent link: https://www.econbiz.de/10012390956

An empirical evaluation of sensitivity bounds for mean-variance portfolio optimisation

Paskaramoorthy, Andrew; Woolway, Matthew - In: Finance research letters 44 (2022), pp. 1-9

Persistent link: https://www.econbiz.de/10014494865

A varying-coefficient panel data model with fixed effects : theory and an application to U.S. commercial banks

Feng, Guohua; Gao, Jiti; Peng, Bin; Zhang, Xiaohui - 2015

Persistent link: https://www.econbiz.de/10011781225

Estimation and inference for a class of generalized hierarchical models

Dong, Chaohua; Gao, Jiti; Peng, Bin; Yan, Yayi - 2024

Persistent link: https://www.econbiz.de/10014534139

Microdata Disclosure by Resampling: Empirical Findings for Business Survey Data

Gottschalk, Sandra - 2003

), and compare resampling with a common method of disclosure control, i.e. disturbance with multiplicative error, concerning … results show that univariate distributions can be better reproduced by unweighted resampling. Parameter estimates can be … reproduced quite well if (a) the resampling procedure implements the correlation structure of the original data as a scale and (b …

Persistent link: https://www.econbiz.de/10010297305