Modeling asymmetric volatility in weekly Dutch temperature data

In addition to clear-cut seasonality in mean and variance, weekly Dutch temperature data appear to have a strong asymmetry in the impact of unexpectedly high or low temperatures on conditional volatility. Furthermore, this asymmetry also shows fairly pronounced seasonal variation. To describe these features, we propose a univariate seasonal time series model with asymmetric conditionally heteroskedastic errors. We fit this (and other, nested) model(s) to 25 years of weekly data. We evaluate its forecasting performance for 5 years of hold-out data and find that the imposed asymmetry leads to be... Mehr ...

Verfasser: Franses, Ph.H.B.F. (Philip Hans)
Neele, J. (Jack)
Dijk, D.J.C. (Dick) van
Dokumenttyp: workingPaper
Erscheinungsdatum: 1998
Schlagwörter: asymmetric volatility / seasonal variation / temperature volatility / weekly dutch temperature
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27065406
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://repub.eur.nl/pub/1533

In addition to clear-cut seasonality in mean and variance, weekly Dutch temperature data appear to have a strong asymmetry in the impact of unexpectedly high or low temperatures on conditional volatility. Furthermore, this asymmetry also shows fairly pronounced seasonal variation. To describe these features, we propose a univariate seasonal time series model with asymmetric conditionally heteroskedastic errors. We fit this (and other, nested) model(s) to 25 years of weekly data. We evaluate its forecasting performance for 5 years of hold-out data and find that the imposed asymmetry leads to better out-of-sample forecasts of temperature volatility.