Findings in Actuarial Science Reported from P. Parodi and Co-Researchers (Property Graphs – a Statistical Model for Fire and Explosion Losses Based On Graph Theory)

2019 MAY 31 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Fresh data on Science - Actuarial Science are presented in a new report. According to news reporting out of London, United Kingdom, by NewsRx editors, research stated, “It is rare that the severity loss distribution for a specific line of business can be derived from first principles. One such example is the use of generalised Pareto distribution for losses above a large threshold (or more accurately: asymptotically), which is dictated by extreme value theory.”

Our news journalists obtained a quote from the research, “Most popular distributions, such as the lognormal distribution or the Maxwell-Boltzmann-Bose-Einstein-Fermi-Dirac (MBBEFD), are convenient heuristics with no underlying theory to back them. This paper presents a way to derive a severity distribution for property losses based on modelling a property as a weighted graph, that is, a collection of nodes and weighted arcs connecting these nodes. Each node v (to which a value can also be assigned) corresponds to a room or a unit of the property where a fire can occur, while an arc (v, v’; p) between vertices v and v’ signals that the probability of the fire propagating from v to v’ is p. The paper presents two simple models for fire propagation (the random graph approach and the random time approach) and a model for explosion risk that allow one to calculate the loss distribution for a given property from first principles.”

According to the news editors, the research concluded: “The MBBEFD model is shown to be a good approximation for the simulated distribution of losses based on property graphs for both the random graph and the random time approach.”

For more information on this research see: Property Graphs - a Statistical Model for Fire and Explosion Losses Based On Graph Theory. Astin Bulletin, 2019;49(2):263-297. Astin Bulletin can be contacted at: Cambridge Univ Press, Edinburgh Bldg, Shaftesbury Rd, CB2 8RU Cambridge, England.

Our news journalists report that additional information may be obtained by contacting P. Parodi, Scor Global P&C, London, United Kingdom.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1017/asb.2019.4. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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