A New Toolkit for Mortality Data Analytics - Krömer, Sarah; Stummer, Wolfgang (Stochastic Models, Statistics and Their Applications, 2019)
For the calculation of premiums, financial reserves, annuities, pension benefits, various benefits of social insurance programs, and many other quantities, a realistic representation of mortality rates is of fundamental essence. We achieve this by a new far-reaching and flexible approach for the smoothing and error-correcting of crude rates, based on the recently developed scaled Bregman distances of Stummer (Proc Appl Math Mech 7(1):1050503–1050504, 2007, [22]), Stummer and Vajda (IEEE Trans Inform Theory 58(3):1277–1288, 2012, [25]), Kißlinger and Stummer (Recent Advances in Robust Statistics – Theory and Applications, pp. 81–113. Springer, India, 2016, [12]), which are generalizations of the well-known Kullback–Leibler information divergence (relative entropy). As illuminations, we present several examples and a concrete data analysis.
CRIS-Team Scopus Importer:2019-12-10
Keywords: Mortality rates; Scaled Bregman distances; Smoothing/Graduation

Model risk regarding monthly wind energy production for the valuation of a wind farm investment - Krömer, Sarah (International Journal of Energy Sector Management, 2019)
Purpose: The purpose of this paper is to assess model risk with regard to wind energy output in monthly cash flow models for the purpose of valuation and risk assessment of wind farm investments, where only a few approaches exist in the literature. Design/methodology/approach: This paper focuses on the risk-return characteristics of this investment from the perspective of private and institutional investors and takes into account several risks, in particular the resource risk related to the uncertainty of the monthly wind energy produced. To this end, this paper presents different approaches for modeling monthly wind power output and assesses the impact of three selected models with different properties on the investment’s risk-return characteristics by means of a stochastic discounted cash flow model. In addition, the model considers the possibility of a joint operation of the wind farm with a pumped hydro storage system to reduce risk and improve profits. Findings: The results show that the (non-)consideration of seasonality of the monthly wind energy produced considerably influences the risk-return characteristics, but that principal developments dependent on input parameters and model variables remain similar. Originality/value: This paper contributes to the literature by presenting different approaches for modeling the monthly wind energy produced based on direct models of the wind energy output, which are rare in the existing literature. Further, their impact on risk-return characteristics of a wind farm investment is analyzed, and thus, related model risk is assessed.
CRIS-Team Scopus Importer:2019-08-13
Keywords: Cash flow; Energy storage; Monte Carlo simulation; Policy risk; Renewable energy; Wind farm; Wind power modeling

Renewable Energy Investments with Storage: A Risk-Return Analysis - Krömer, Sarah; Gatzert, Nadine (International Journal of Energy Sector Management, 2018)
The aim of this paper is to study investments in renewable energy projects which are jointly operated with an energy storage system, with particular focus on risk-return characteristics from the perspective of private and institutional investors, taking into account resource risk, energy price risk, inflation risk, and policy risk. To this end, this article presents a stochastic discounted cash flow model which is then applied to a wind farm with a pumped hydro storage system. The results show that energy storage systems have the potential to increase the expected present value of future investment cash flows and to hedge (downside) risk. However, in order to realize this potential, storage systems have to be cost-effective in terms of fixed operation, maintenance, staffing and insurance costs. Also, several key factors are identified which have a considerable influence on the performance of the operation strategy. The paper contributes to the literature by conducting an analysis of (downside) risk and return of renewable energy investments with a storage system taking into account stochastic policy, resource, inflation, and energy price ris
Keywords: Renewable energy; wind farm; energy storage; policy risk; value at risk