An actuarial model of forest insurance against multiple natural hazards in fir (Abies Alba Mill.) stands in Slovakia

• This paper provides the theoretical basis of an actuarial forest insurance scheme designed to insure multiple natural events.
• We propose two different links for the hazards mutually dependent or independent. In addition, we propose two parametric solutions discrete time period approach or continuous one.
• We propose an application to a silver fir (Abies Alba Mill.) stand in the Slovak Paradise region (Slovakia).
• The most efficient solution, is obtained when assuming mutually independent natural hazards and a continuous time period approach. Such a solution provides gross insurance premiums ranging from €5.62/ha.

Natural hazards are the main threat for forest all over the world. Some of these disturbances may be insured such as fire and/or storm in some European countries. However, forest insurance has trouble to spread in particular because of the existence of some brakes such as the forest insurance premium, often considered as too high compared to the profitability of the forest investment. In this context, we propose an actuarial insurance model to insure multiple natural hazards (windthrow, fire, insect outbreak) in forests that determine the insurance premium in different senarios. In particular, the scenarios differ in terms of the link between the hazards, either they are mutually independent or dependent, and in terms of the parametric solutions to the actuarial problem, either a discrete time period approach or a continuous one. We propose an application of the actuarial model to a silver fir (Abies Alba Mill.) stand in the Slovak Paradise region (Slovakia). We show that gross insurance premiums range from €5.62/ha at a scale of 150,000 ha at age 150, to €6312.81/ha at a scale of 15 ha at age 50. In addition, we show that the most efficient solution in terms of the minimisation of the gross insurance premiums is provided under the assumption of random occurrence of mutually independent natural hazards and with a continuous time period approach.