Showing 1 - 9 of 9
Persistent link: https://www.econbiz.de/10010849583
In this paper we study the goodness-of-fit test introduced by Fortiana and Grané (2003) and Grané (2012), in the context of randomly censored data. We construct a new test statistic undergeneral right-censoring, i.e., with unknown censoring distribution, and prove its asymptoticproperties....
Persistent link: https://www.econbiz.de/10010861858
Outliers of moderate magnitude cause large changes in financial time series of prices and returns and affect both the estimation of parameters and volatilities when fitting a GARCH-type model. The multivariate setting is still to be studied, but similar biases and impacts on correlation dynamics...
Persistent link: https://www.econbiz.de/10010861874
The statistic introduced in Fortiana and Grané (J R Stat Soc B 65(1):115–126, <CitationRef CitationID="CR6">2003</CitationRef>) is modified so that it can be used to test the goodness-of-fit of a censored sample, when the distribution function is fully specified. Exact and asymptotic distributions of three modified versions of this...</citationref>
Persistent link: https://www.econbiz.de/10011000085
Persistent link: https://www.econbiz.de/10005613197
The aim of this work is to introduce a new nonparametric regression technique in the context of functional covariate and scalar response. We propose a local linear regression estimator and study its asymptotic behaviour. Its finite-sample performance is compared with a Nadayara-Watson type...
Persistent link: https://www.econbiz.de/10005221639
Persistent link: https://www.econbiz.de/10008925336
In this paper we focus on the impact of additive level outliers on the calculation of risk measures, such as minimum capital risk requirements, and compare four alternatives of reducing these measures' estimation biases. The first three proposals proceed by detecting and correcting outliers...
Persistent link: https://www.econbiz.de/10008625889
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and poor volatility forecasts. Therefore, their detection and correction should be taken seriously when modeling financial data. The present paper focuses on these issues and proposes a general detection...
Persistent link: https://www.econbiz.de/10008462360