Locally adaptive estimation methods with application to univariate time series
Statistics Theory
2008-12-03 v1 Statistical Finance
Statistics Theory
Abstract
The paper offers a unified approach to the study of three locally adaptive estimation methods in the context of univariate time series from both theoretical and empirical points of view. A general procedure for the computation of critical values is given. The underlying model encompasses all distributions from the exponential family providing for great flexibility. The procedures are applied to simulated and real financial data distributed according to the Gaussian, volatility, Poisson, exponential and Bernoulli models. Numerical results exhibit a very reasonable performance of the methods.
Cite
@article{arxiv.0812.0449,
title = {Locally adaptive estimation methods with application to univariate time series},
author = {Mstislav Elagin},
journal= {arXiv preprint arXiv:0812.0449},
year = {2008}
}
Comments
Submitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)