J
Jens Perch Nielsen
Researcher at City University London
Publications - 197
Citations - 4874
Jens Perch Nielsen is an academic researcher from City University London. The author has contributed to research in topics: Estimator & Kernel density estimation. The author has an hindex of 37, co-authored 195 publications receiving 4574 citations. Previous affiliations of Jens Perch Nielsen include Codan & University of Copenhagen.
Papers
More filters
Journal ArticleDOI
Two-dimensional Hazard Estimation for Longevity Analysis
TL;DR: This work investigates developments in Danish mortality based on data from 1974–1998 working in a two-dimensional model with chronological time and age as the two dimensions and suggests that life insurance companies use the estimation technique and the cross-validation for bandwidth selection when analyzing their portfolio mortality.
Journal ArticleDOI
A General Approach to the Predictability Issue in Survival Analysis with Applications
Enno Mammen,Jens Perch Nielsen +1 more
TL;DR: In this paper, a general approach to the solution of the predictability issue in martingale integrals is presented, where the integrand is not predictable and where the counting process theory of martingales is not directly applicable, as for example in nonparametric and semiparametric applications where the integration is based on a pilot estimate.
Posted Content
Nonparametric prediction of stock returns guided by prior knowledge
TL;DR: In this article, a straightforward bootstrap-test confirms that non-and semiparametric techniques help to obtain better forecasts and the inclusion of prior knowledge enables for American data a further notable improvement in the prediction of excess stock returns of 35% compared to the fully nonparametric model.
Posted Content
Boundary and Bias Correction in Kernel Hazard Estimation
TL;DR: In this article, a new class of local linear azard estimators based on weig ted least square kernel estimation is considered and a new bias correction technique based on bootstrap estimation of additive bias is proposed.
Journal ArticleDOI
The link between classical reserving and granular reserving through double chain ladder and its extensions
TL;DR: This paper draws on recent research and concludes that chain ladder can be seen as a structured histogram, which gives a direct link between classical aggregate methods and continuous granular methods.