Generating VaR scenarios with product beta distributions

We propose a Monte Carlo simulation method to generate stress tests by VaR scenarios under Solvency II for dependent risks on the basis of observed data. This is of particular interest for the construction of Internal Models and requirements on evaluation processes formulated in the Commission Delegated Regulation. The approach is based on former work on partition-ofunity copulas, however with a direct scenario estimation of the joint density by product beta distributions after a suitable transformation of the original data.Comment: 10 pages, 25 figures, 5 table

Ruin probability in a risk model with a variable premium intensity and risky investments

We consider a generalization of the classical risk model when the premium intensity depends on the current surplus of an insurance company. All surplus is invested in the risky asset, the price of which follows a geometric Brownian motion. We get an exponential bound for the infinite-horizon ruin probability. To this end, we allow the surplus process to explode and investigate the question concerning the probability of explosion of the surplus process between claim arrivals.Comment: 16 page

Weather stations in Norway suitable for SNOWPACK modelling in Norway in 2016

A physical SNOWPACK model developed by Swiss Federal Institute for Snow and Avalanche Research, SLF, requires following meteorological observations as input data1 for the model simulations: - air temperature (TA) - relative humidity (RH) - wind speed (VW) - incoming short wave radiation (ISWR) or reflected short wave radiation (RSWR) - incoming long wave radiation (ILWR) or surface temperature (TSS) - precipitation (PSUM) or snow height (HS) - ground temperature (TSG, if available) - snow temperatures at various depths (TS1, TS2, etc. if available and only for comparisons) According to the data requirements specified for SNOWPACK model, above listed parameters must be available at least at an hourly time step.Norges vassdrags- og energidirektorat (NVE

Review of meteorological data from Fonnbu 2009–2016

12 observed parameters are recalculated with a time step of 1 hour from the original raw data set of observed values with 10 minute time step. To form winter season data sets which would cover complete snow season, it was decided to set the start of each season on 1st September and the finish on 30th June.Norges vassdrags- og energidirektorat (NVE