Comparison of distribution tails). Consider the distribution of losses owned by insurance companies. Loss for the coming year is predicted to have a mean of 100 with a standard deviation of 223.607. If it is assumed that the loss distribution is Normal, Pareto and Gamma (with mean and variance above), determine VaR for each loss distribution with a safety level of 90%; 99% and 99.9%. Notes: From the mean and standard deviation as well as the k-th moment, the parameter values for each distribution (in millions) will be obtained. Furthermore, by using the inverse FDK, the VaR value will be obtained.
Comparison of distribution tails). Consider the distribution of losses owned by insurance companies. Loss for the coming year is predicted to have a mean of 100 with a standard deviation of 223.607. If it is assumed that the loss distribution is Normal, Pareto and Gamma (with mean and variance above), determine VaR for each loss distribution with a safety level of 90%; 99% and 99.9%. Notes: From the mean and standard deviation as well as the k-th moment, the parameter values for each distribution (in millions) will be obtained. Furthermore, by using the inverse FDK, the VaR value will be obtained.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Please solve with the step max in 60-90 minutes the chapter actuarial
Comparison of distribution tails). Consider the distribution of losses owned by insurance companies. Loss for the coming year is predicted to have a
If it is assumed that the loss distribution is Normal, Pareto and Gamma (with mean and variance above), determine VaR for each loss distribution with a safety level of 90%; 99% and 99.9%.
Notes:
From the mean and standard deviation as well as the k-th moment, the parameter values for each distribution (in millions) will be obtained. Furthermore, by using the inverse FDK, the VaR value will be obtained.
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