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A blocking and regularization approach to high dimensional realized covariance estimation

Hautsch, Nikolaus; Kyj, Lada M.; Hautsch, Nikolaus - 2009

We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven...

Persistent link: https://www.econbiz.de/10010303678

Estimating standard errors for the Parks model: Can jackknifing help?

Reed, W. Robert; Webb, Rachel S. - In: Economics: The Open-Access, Open-Assessment E-Journal 5 (2011) 2011-1, pp. 1-14

Non-spherical errors, namely heteroscedasticity, serial correlation and cross-sectional correlation are commonly …

Persistent link: https://www.econbiz.de/10010303845

Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments

DiPrete, Thomas A.; Gangl, Markus - 2004

Propensity score matching provides an estimate of the effect of a 'treatment' variable on an outcome variable that is largely free of bias arising from an association between treatment status and observable variables. However, matching methods are not robust against 'hidden bias' arising from...

Persistent link: https://www.econbiz.de/10010304029

Analyzing ordered categorical data derived from elliptically symmetric distributions

Kukuk, Martin - 1998

The polychoric correlation is an ML estimator for the correlation parameter between two latent variables. Each latent … study applying the polychoric correlation based on normality if the true distribution is in fact an elliptically symmetric … distribution. The results show that the polychoric correlation is robust in the sense that the true correlation between the latent …

Persistent link: https://www.econbiz.de/10010305029

Distinguishing between long-range dependence and deterministic trends

Sibbertsen, Philipp; Venetis, Ioannis - 2003

We provide a method for distinguishing long-range dependence from deterministic trends such as structural breaks. The method is based on the comparison of standard log-periodogram regression estimation of the memory parameter with its tapered counterpart. The difference of these estimators...

Persistent link: https://www.econbiz.de/10010306228

A rule-of-thumb for the variable bandwidth selection in kernel hazard rate estimation

Weißbach, Rafael; Gefeller, Olaf - 2004

In nonparametric curve estimation the decision about the type of smoothing parameter is critical for the practical performance. The nearest neighbor bandwidth as introduced by Gefeller and Dette 1992 for censored data in survival analysis is specified by one parameter, namely the number of...

Persistent link: https://www.econbiz.de/10010306234

Maximin and Bayesian optimal designs for regression models

Dette, Holger; Haines, Linda M.; Imhof, Lorens A. - 2003

For many problems of statistical inference in regression modelling, the Fisher information matrix depends on certain nuisance parameters which are unknown and which enter the model nonlinearly. A common strategy to deal with this problem within the context of design is to construct maximin...

Persistent link: https://www.econbiz.de/10010306254

Jump-preserving monitoring of dependent time series using pilot estimators

Steland, Ansgar - 2003

An important problem of the statistical analysis of time series is to detect change-points in the mean structure. Since this problem is a one-dimensional version of the higher dimensional problem of detecting edges in images, we study detection rules which benefit from results obtained in image...

Persistent link: https://www.econbiz.de/10010306257

On detecting jumps in time series: Nonparametric setting

Pawlak, Mirek; Rafajlowicz, Ewaryst; Steland, Ansgar - 2003

Motivated by applications in statistical quality control and signal analysis, we propose a sequential detection procedure which is designed to detect structural changes, in particular jumps, immediately. This is achieved by modifying a median filter by appropriate kernel-based jump preserving...

Persistent link: https://www.econbiz.de/10010306263

A note on maximin and Bayesian D-optimal designs in weighted polynomial regression

Biedermann, Stefanie; Dette, Holger - 2003

We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynominal regression model with a certain efficiency function depending on two unknown parameters, which models he heteroscedastic error structure. This problem is tackled by adopting a Bayesian...

Persistent link: https://www.econbiz.de/10010306264