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Is the multivariate chain–ladder method sensitive to outlying values?
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Why does a multivariate chain-ladder fail?
Do loss reserving techniques sensitivity to outliers?
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Sep 1, 2011 · However, it is well known that the chain–ladder method is very sensitive to outlying data. For the univariate case, we have already developed a robust version of the chain–ladder method. In this article we propose two techniques to detect and correct outlying values in a bivariate situation.
- Tim Verdonck, M Van Wouwe
- 2011
The multivariate time series chain-ladder (Merz & Wüthrich, Reference Merz and Wüthrich 2008) is applied on these robust claims. For the halfspace depth approach, we calculate residuals in the same fashion; however, the outlier detection and treatment methodology is altered.
Mar 1, 2016 · However, it is well known that the chain-ladder method is very sensitive to outlying data. For the bivariate situation, we have already developed robust solutions for the chain-ladder method by...
However, it is well known that the chainladder method is very sensitive to outlying data. For the bivariate situation, we have already developed robust solutions for the chain-ladder method by introducing two techniques for detecting and correcting outliers.
Verdonck, Van Wouwe, and Dhaene (2009) show that the traditional chain-ladder reserve estimates are highly susceptible to even just one outlier in the data set and further highlight that the impact on reserves may be positive or negative. To address this problem they provide a two-stage robust chain-ladder technique
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Mar 8, 2022 · Two approaches to robustify the chain-ladder method are focused on: the first method detects and adjusts the outlying values, whereas the second method is based on a robust generalized linear model technique.
However, the GMCL method is based on the seemingly unrelated regression (SUR) technique which makes it very sensitive to outliers. To address this issue, we propose a robust alternative that...
