Modelling of Low Probability High Impact Events : Estimating Yearly Losses Incurred Due to Tornadoes in the United States

Michal Majka

ISBN 10: 6202221925 / ISBN 13: 9786202221924

Published by AV Akademikerverlag, 2019

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - In many real world phenomena the need for modelling of losses caused by an underlying process that generates both large number of occurrences with minor losses and occurrences with severe impact exists. Prominent examples are natural disasters (earthquakes, hurricanes, tornadoes etc.), operational losses in highly regulated institutions or claims generated by an insurance policy. In each case, the aggregated loss distribution can be modelled with a so called compound model that is a combination of two separate distributions describing the number of events and their severities. In the first part of this book in-depth description of the compound model is provided. The formal discussion is then followed by a case study, in which the previously elaborated theory is applied to model yearly losses incurred due to tornadoes in the United States.

Seller Inventory # 9786202221924

Bibliographic Details

• Title: Modelling of Low Probability High Impact Events : Estimating Yearly Losses Incurred Due to Tornadoes in the United States
• Publisher: AV Akademikerverlag
• Publication Date: 2019
• Language: English
• ISBN 10: 6202221925
• ISBN 13: 9786202221924
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 6D millimeters 220 millimeters width by 150 millimeters height by 6 millimeters depth
• Weight: 149 grams

About this title

Synopsis

In many real world phenomena the need for modelling of losses caused by an underlying process that generates both large number of occurrences with minor losses and occurrences with severe impact exists. Prominent examples are natural disasters (earthquakes, hurricanes, tornadoes etc.), operational losses in highly regulated institutions or claims generated by an insurance policy. In each case, the aggregated loss distribution can be modelled with a so called compound model that is a combination of two separate distributions describing the number of events and their severities. In the first part of this book in-depth description of the compound model is provided. The formal discussion is then followed by a case study, in which the previously elaborated theory is applied to model yearly losses incurred due to tornadoes in the United States.