An exploration of non-exponential family distributions in run-off triangle.
The conventional way to model claims liabilities is by using distributions from the exponential family to fit run-off triangles. In this research, we explore the possibilities of using distributions from non-exponential family to model claim liabilities. Five such distributions are applied to three...
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sg-ntu-dr.10356-441952023-05-19T07:23:09Z An exploration of non-exponential family distributions in run-off triangle. Teo, Wesley. Setiadi, Albertus Teddy. Szeto, Wing Ki. Li Ka Ki Jackie Nanyang Business School DRNTU::Business::Finance::Actuarial science The conventional way to model claims liabilities is by using distributions from the exponential family to fit run-off triangles. In this research, we explore the possibilities of using distributions from non-exponential family to model claim liabilities. Five such distributions are applied to three sets of claims run-off data and the R statistical programming software is used to generate the data analysis. Using Maximum Likelihood Estimation (MLE), we derive the estimated parameters of claims distributions and calculated outstanding claim liabilities of each distribution. Next, using the comparison methods - Mean Absolute Percentage Error (MAPE), Standardized Residual Analysis and t-Statistics Test, we seek the best non-exponential family distribution. We were thus able to identify that Laplace distribution is the best fit to model claim liabilities. In addition, our findings have highlighted some precautions that users should note when using a non-exponential distribution to fit claim liabilities. BUSINESS 2011-05-31T01:07:23Z 2011-05-31T01:07:23Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/44195 en Nanyang Technological University 73 p. + 1 template application/msword application/vnd.ms-excel |
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DRNTU::Business::Finance::Actuarial science Teo, Wesley. Setiadi, Albertus Teddy. Szeto, Wing Ki. An exploration of non-exponential family distributions in run-off triangle. |
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The conventional way to model claims liabilities is by using distributions from the exponential family to fit run-off triangles. In this research, we explore the possibilities of using distributions from non-exponential family to model claim liabilities. Five such distributions are applied to three sets of claims run-off data and the R statistical programming software is used to generate the data analysis. Using Maximum Likelihood Estimation (MLE), we derive the estimated parameters of claims distributions and calculated outstanding claim liabilities of each distribution. Next, using the comparison methods - Mean Absolute Percentage Error (MAPE), Standardized Residual Analysis and t-Statistics Test, we seek the best non-exponential family distribution. We were thus able to identify that Laplace distribution is the best fit to model claim liabilities. In addition, our findings have highlighted some precautions that users should note when using a non-exponential distribution to fit claim liabilities. |
author2 |
Li Ka Ki Jackie |
author_facet |
Li Ka Ki Jackie Teo, Wesley. Setiadi, Albertus Teddy. Szeto, Wing Ki. |
format |
Final Year Project |
author |
Teo, Wesley. Setiadi, Albertus Teddy. Szeto, Wing Ki. |
author_sort |
Teo, Wesley. |
title |
An exploration of non-exponential family distributions in run-off triangle. |
title_short |
An exploration of non-exponential family distributions in run-off triangle. |
title_full |
An exploration of non-exponential family distributions in run-off triangle. |
title_fullStr |
An exploration of non-exponential family distributions in run-off triangle. |
title_full_unstemmed |
An exploration of non-exponential family distributions in run-off triangle. |
title_sort |
exploration of non-exponential family distributions in run-off triangle. |
publishDate |
2011 |
url |
http://hdl.handle.net/10356/44195 |
_version_ |
1772825696791429120 |