Bayesian analysis in an aggregate loss model: validation of the structure functions

Agustin Hernandez Bastida; Jose Maria Perez Sanchez; Pilar Fernandez-Sanchez

doi:10.21314/jrmv.2017.176

Bayesian analysis in an aggregate loss model: validation of the structure functions

The Journal of Risk Model Validation ◽

10.21314/jrmv.2017.176 ◽

2017 ◽

Vol 11 (3) ◽

pp. 19-47

Author(s):

Agustin Hernandez Bastida ◽

Jose Maria Perez Sanchez ◽

Pilar Fernandez-Sanchez

Keyword(s):

Bayesian Analysis ◽

Model Validation ◽

Structure Functions ◽

Loss Model ◽

Aggregate Loss

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Analysis of an aggregate loss model in a Markov renewal regime

Applied Mathematics and Computation ◽

10.1016/j.amc.2020.125869 ◽

2021 ◽

Vol 396 ◽

pp. 125869

Author(s):

Pepa Ramírez-Cobo ◽

Emilio Carrizosa ◽

Rosa E. Lillo

Keyword(s):

Loss Model ◽

Aggregate Loss

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A multivariate aggregate loss model

Insurance Mathematics and Economics ◽

10.1016/j.insmatheco.2012.06.009 ◽

2012 ◽

Vol 51 (2) ◽

pp. 402-408 ◽

Cited By ~ 2

Author(s):

Jiandong Ren

Keyword(s):

Loss Model ◽

Aggregate Loss

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PERHITUNGAN UKURAN RISIKO UNTUK MODEL KERUGIAN AGREGAT

JURNAL MATEMATIKA MURNI DAN TERAPAN EPSILON ◽

10.20527/epsilon.v14i1.2200 ◽

2020 ◽

Vol 14 (1) ◽

pp. 21

Author(s):

Nadya Pratiwi ◽

Aprida Siska Lestia ◽

Nur Salam

Keyword(s):

Monte Carlo ◽

Standard Deviation ◽

Monte Carlo Method ◽

Value At Risk ◽

Risk Measure ◽

Random Variable ◽

Insurance Companies ◽

Loss Model ◽

Aggregate Loss ◽

Conditional Tail Expectation

In the case of nonlife insurance, insurance companies are very potential to get losses if claims submitted by customers (policyholders) exceeds the reserves of budgeted claims. It is the risk that have to managed properly by insurance companies . One possible disadvantage is the aggregate loss model. The aggregate loss model is a random variable that states the total of all losses incurred in an insurance policy block. This kind of loss can be modeled using a collective risk approach where the number of claims is a discrete random variable and the size of claim is a continuous random variable. The purpose of this study is to determine risk measure of standard deviation premium principle, value at risk (VaR), and conditional tail expectation (CTE) of the aggregate loss model. Standard deviation premium principle risk measure of aggregate loss model is determined analytically by substituted it expected value and varians. Meanwhile, VaR risk measure is determined using numerical method by Monte Carlo method, then the quantile value and it confidence interval for the actual value will estimate. In the CTE calculation, based on the loss data obtained in the Monte Carlo method, the CTE value is estimated by calculating the average loss that exceeds the VaR value. If the data size is large enough, the CTE value estimation will converge to the actual value.Keywords: Aggregate Loss Model, Standard Deviation Premium Principle, Value at Risk (VaR), Conditional Tail Expectation (CTE).

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