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 better out-of-sample forecasts of temperature volatility.
|Keywords||asymmetric volatility, seasonal variation, temperature volatility, weekly dutch temperature|
Franses, Ph.H.B.F., Neele, J., & van Dijk, D.J.C.. (1998). Modeling asymmetric volatility in weekly Dutch temperature data (No. EI 9840). Retrieved from http://hdl.handle.net/1765/1533
|feweco19981126102103.pdf Final Version , 584kb|