New Research on Risk Management from University of Hamburg Summarized (Kalman Filter Learning Algorithms and State Space Representations for Stochastic Claims Reserving)

2021 JUL 16 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on insurance is the subject of a new report. According to news reporting originating from Hamburg, Germany, by NewsRx correspondents, research stated, “In stochastic claims reserving, state space models have been used for almost 40 years to forecast loss reserves and to compute their mean squared error of prediction.”

The news journalists obtained a quote from the research from University of Hamburg: “Although state space models and the associated Kalman filter learning algorithms are very powerful and flexible tools, comparatively few articles on this topic were published during this period. Most recently, several articles have been published which highlight the benefits of state space models in stochastic claims reserving and may lead to a significant increase in its popularity for applications in actuarial practice.”

According to the news reporters, the research concluded: “To further emphasize the merits of these papers, this commentary highlights various additional aspects that are useful for practical applications and offer some fruitful directions for future research.”

For more information on this research see: Kalman Filter Learning Algorithms and State Space Representations for Stochastic Claims Reserving. Risks, 2021,9(112):112. (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks9060112.

Our news editors report that additional information may be obtained by contacting Nataliya Chukhrova, Faculty of Business Administration, University of Hamburg, 20146 Hamburg, Germany. Additional authors for this research include Arne Johannssen.

(Our reports deliver fact-based news of research and discoveries from around the world.)