Conditional Variance Forecasts for Long-Term Stock Returns

Autor: Enno Mammen, Jens Perch Nielsen, Michael Scholz, Stefan Sperlich

Publikováno v: Risks, Vol 7, Iss 4, p 113 (2019)

In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation ra

Externí odkaz: https://doaj.org/article/07a0f5157e934d27bf9ff6d8c5a3ab02

Nonparametric estimation of locally stationary Hawkes processes

Autor: Enno Mammen, Marilena Müller

Publikováno v: Bernoulli. 29

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::88d09774f17479b12748412e40b3e889
https://doi.org/10.3150/22-bej1532

A general semiparametric approach to inference with marker-dependent hazard rate models

Autor: Jens Perch Nielsen, Lena Janys, Enno Mammen, Gerard J. van den Berg

Publikováno v: Journal of Econometrics, 221(1), 43-67. Elsevier Science
van den Berg, G J, Janys, L, Mammen, E & Nielsen, J P 2021, ' A general semiparametric approach to inference with marker-dependent hazard rate models ', Journal of Econometrics, vol. 221, no. 1, pp. 43-67 . https://doi.org/10.1016/j.jeconom.2019.05.025
Journal of Econometrics, 221(1), 43-67. Elsevier BV
van den Berg, G J, Mammen, E, Janys, L & Nielsen, J P 2020, ' A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models ', Journal of Econometrics . https://doi.org/10.1016/j.jeconom.2019.05.025

We examine a new general class of hazard rate models for survival data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and (possibly time-dependent) marker or covariate effects. A number of well-known models

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::864cad6cf91cd02051045068eb141c87
https://doi.org/10.1016/j.jeconom.2019.05.025

Calendar effect and in-sample forecasting

Autor: Michael Vogt, Jens Perch Nielsen, Enno Mammen, María Dolores Martínez-Miranda

Publikováno v: Insurance: Mathematics and Economics. 96:31-52

A very popular forecasting tool in the actuarial sciences is the so-called chain ladder. Mammen et al. (2015) recently introduced in-sample forecasting, a general forecasting technique applicable in many fields which builds on the continuous chain la

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e817c71b1280b8fde76462a11edfbcec
https://doi.org/10.1016/j.insmatheco.2020.10.003

A nonparametric approach to identify age, time, and cohort effects

Autor: Enno Mammen, Kyusang Yu, Bernd Fitzenberger, Dirk Antonczyk

Publikováno v: Journal of Statistical Planning and Inference. 204:96-115

Empirical studies in the social sciences and biometrics often rely on data and models where a number of individuals born at different dates are observed at several points in time, and the relationship of interest centers on the effects of age a , coh

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::61e53f75d939b8e82cc692e4af15a464
https://doi.org/10.1016/j.jspi.2019.04.009