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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

NIBIO's Scientific Publications →

2023

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Authors

Håvard Steinshamn

Abstract

No abstract has been registered

Authors

Chloé Grieu Andrea Ficke Guro Brodal

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No abstract has been registered

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Authors

Arne Sæbø Hans Martin Hanslin Bart Muys David W. Shanafelt Tommaso Sitzia Roberto Tognetti

Abstract

The BioCities concept builds on the integration of natural and human processes in urban design, with natural biotic and abiotic factors and processes integrated with the development of constructed features to provide for human well-being.

Authors

Susanne Friis Pedersen Kaia Slågedal Michel Verheul

Abstract

No abstract has been registered

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Authors

Sigridur Dalmannsdottir Karin Juul Hesselsøe Trygve S. Aamlid

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No abstract has been registered

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Authors

Siri Elise Dybdal Marit Jørgensen

Abstract

No abstract has been registered

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Authors

Grete H. M. Jørgensen Inger Hansen Cathy Dwyer

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Authors

Claire Morgan-Davies Germain Tesniere Cathy Dwyer Grete H. M. Jørgensen Eliel Gonzalez-Garcia Sotiris Patsios Evangeline Sossidou Tim Keady Brid McClearn Fiona Kenyon Gerrardo Caja Lise Grøva Mauro Decandia Ludovic Cziszter Ilan Halachmi Jean Marc Gautier

Abstract

No abstract has been registered

Authors

Pia Heltoft Thomsen Marit Almvik Karin Juul Hesselsøe Monica Fongen Jørgen Hornslien Anne Friederike Borchert Kristine Sundsdal Trygve S. Aamlid

Abstract

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Authors

Christian Oliver Ewald Jelena Hadina Erik Haugom Gudbrand Lien Ståle Størdal Muhammad Yahya

Abstract

In this paper we examine how sensitive Value-at-Risk (VaR) forecasts based on simple linear quantile regressions are to the sampling frequency used to calculate realized volatility. We use sampling frequencies from one to 108 min for ICE Brent Crude Oil futures and test the out-of-sample performance of a set of quantile regression models using formal coverage tests. The results show that a one-factor model performs exceptionally well for most sampling frequencies used to calculate realized volatility. In comparison with the well-known Heterogeneous Auto-regressive Model of Realized Volatility (HAR-RV) and a quantile regression version of the HAR model (HAR-QREG), we also find that the one-factor model is much less sensitive to the sampling frequency used to calculate realized volatility.