This paper thoroughly investigates needs and requirements for overhead distribution feeder inspection and develops models to investigate possible relations between short term inspections remarks and outages. The study was conducted in collaboration with Fortum Distribution AB that supplied extensive information about their overhead power feeders concerning both inspection and power outages. The investigated models where Lognormal linear model, Poisson generalized linear model and negative binomial generalized linear model. All models were implemented utilizing offset terms to compensate for differences in feeder length and amount of overhead versus underground feeders. The Poisson generalized linear model was rejected at an early stage due to overdispersion and neither of the remaining models fit the data perfectly.

Med dagens låga ränta lånar privatpersoner mer än någonsin för att finansiera sina bostadsköp. Denna uppsats behandlar ränterisken en privatperson utsätter sig för vid bostadsköp då denne skall ta lån med fast ränta. Vanligtvis brukar det ta tre månader (90 dagar) från det att köpekontrakt skrivits på till att köpet genomförts. Genom att anta att ränteförändringarna är Lognormalfördelade har jag kommit fram till att tvåårs och femårs räntan inte stiger betydande under 90 dagar. Slutsatsen jag dragit är att ränterisken är låg med dagens låga ränta..

Climate change is expected to increase the frequency and intensity of extreme weather events, with significantimplications for the financial stability of insurance markets. This study analyses how nature-related insurancepayouts and required solvency capital may develop over the period 2025?2099 under three emissions scenarios: RCP 2.6, RCP 4.5 and RCP 8.5, and what this means for the long-term sustainability of insurance as an economic institution. Using Monte Carlo simulation of a non-homogeneous Cram?r-Lundberg model, claimfrequency is modelled as a negative binomial process calibrated against SMHI's climate projections, and claimsizes are approximated by a Lognormal distribution fitted to Swedish insurance data (NATY, 2015?2023).The results show that accumulated insurance payouts amount to SEK 96.7 billion under RCP 2.6, SEK 106.0billion under RCP 4.5 and SEK 131.9 billion under RCP 8.5.

Climate change is expected to increase the frequency and intensity of extreme weather events, with significantimplications for the financial stability of insurance markets. This study analyses how nature-related insurancepayouts and required solvency capital may develop over the period 2025?2099 under three emissions scenarios: RCP 2.6, RCP 4.5 and RCP 8.5, and what this means for the long-term sustainability of insurance as an economic institution. Using Monte Carlo simulation of a non-homogeneous Cram?r-Lundberg model, claimfrequency is modelled as a negative binomial process calibrated against SMHI's climate projections, and claimsizes are approximated by a Lognormal distribution fitted to Swedish insurance data (NATY, 2015?2023).The results show that accumulated insurance payouts amount to SEK 96.7 billion under RCP 2.6, SEK 106.0billion under RCP 4.5 and SEK 131.9 billion under RCP 8.5.