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Härdle, Wolfgang; Fai, Phoon-kok; Lee, David Kuo Chuen - 2016

We analyse a sample of funds and other securities each assigned a total rating score by an unknown expert entity. The scores are based on a number of risk and complexity factors, each assigned a category (factor score) of Low, Medium, or High by the expert entity. A principal component analysis...

Persistent link: https://www.econbiz.de/10011557303

Academic ranking scales in economics : prediction and imputation

Zharova, Alona; Mihoci, Andrija; Härdle, Wolfgang - 2016

quality of published research that enters decisions on jobs, salary, tenure, etc. Academic ranking scales in economics and … ranking systems are competing, allow for different disciplinary gravity and sometimes give orthogonal results. Here a … Scholar (GS) systems is presented. Quantile regression allows us to successfully predict missing ranking data and to obtain a …

Persistent link: https://www.econbiz.de/10011459002

An indicator for national systems of innovation : methodology and application to 17 industrialized countries

Belitz, Heike; Clemens, Marius; Hirschhausen, Christian … - 2011

calculating and ranking the innovation indictor scores for the 17 countries, we group them into three classes: innovation leader … ; Ranking …

Persistent link: https://www.econbiz.de/10009156479

On local times of ranked continuous semimartingales : application to portfolio generating functions

Ghomrasni, Raouf (contributor) - 2005

Persistent link: https://www.econbiz.de/10003323022

Testing for the cointegrating rank of a VAR process with level shift and trend break

Trenkler, Carsten (contributor); … - 2006

A test for the cointegrating rank of a vector autoregressive (VAR) process with a possible shift and broken linear trend is proposed. The break point is assumed to be known. The setup is a VAR process for cointegrated variables. The tests are not likelihood ratio tests but the deterministic...

Persistent link: https://www.econbiz.de/10003376003

Functional principal component analysis for derivatives of multivariate curves

Grith, Maria; Härdle, Wolfgang; Kneip, Alois; Wagner, Heiko - 2016

We present two methods based on functional principal component analysis (FPCA) for the estimation of smooth derivatives of a sample of random functions, which are observed in a more than one-dimensional domain.We apply eigenvalue decomposition to a) the dual covariance matrix of the derivatives,...

Persistent link: https://www.econbiz.de/10011530075

Factorisable sparse tail event curves with expectiles

Härdle, Wolfgang; Huang, Chen; Chao, Shih-Kang - 2016

Persistent link: https://www.econbiz.de/10011452923

Factorisable multi-task quantile regression

Chao, Shih-Kang; Härdle, Wolfgang; Yuan, Ming - 2016

For many applications, analyzing multiple response variables jointly is desirable because of their dependency, and valuable information about the distribution can be retrieved by estimating quantiles. In this paper, we propose a multi-task quantile regression method that exploits the potential...

Persistent link: https://www.econbiz.de/10011579012

Multivariate factorisable sparse asymmetric least squares regression

Chao, Shih-Kang; Härdle, Wolfgang; Huang, Chen - 2016

More and more data are observed in form of curves. Numerous applications in finance, neuroeconomics, demographics and also weather and climate analysis make it necessary to extract common patterns and prompt joint modelling of individual curve variation. Focus of such joint variation analysis...

Persistent link: https://www.econbiz.de/10011579014

Time varying quantile Lasso

Zbonakova, Lenka; Härdle, Wolfgang; Wang, Weining - 2016

In the present paper we study the dynamics of penalization parameter ? of the least absolute shrinkage and selection operator (Lasso) method proposed by Tibshirani (1996) and extended into quantile regression context by Li and Zhu (2008). The dynamic behaviour of the parameter ? can be observed...

Persistent link: https://www.econbiz.de/10011557306