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Mack the chain ladder predictor of ultimate aggregate claims is unbiased but shares this property with many other predictors (Section 6). Optimality of the chain ladder predictor of ultimate aggregate claims remains an open problem. Throughout this paper, let (fL 7, P) be a probability space.
that the chain ladder method is almost certainly biased. However, there is a method for consideration (though not elimination) of bias resulting from (1) the presence of error terms and (2) the correlation of error terms within an accident year.
Over the past twenty years many actuaries have claimed and argued that the chain-ladder method of loss reserving is biased; nonetheless, the chain-ladder method remains the favorite tool of reserving actuaries. Nearly everyone who acknowledges this bias believes it to be upward.
a model in which the chain ladder predictor of ultimate aggregate claims turns out to be unbiased. 1. INTRODUCTION The chain ladder method is a simple and suggestive tool in claims reserving, and vari-ous attempts have been made aiming at its justification in a stochastic model. Remar-
If these assumptions hold, the Mack chain-ladder-model gives an unbiased estimator for IBNR (Incurred But Not Reported) claims. The Mack chain-ladder model can be regarded as a weighted linear regression through the origin for each development period: lm(y ~ x + 0, weights=w/x^(2-alpha)) , where y y is the vector of claims at development period ...
Jul 21, 2024 · Chain-ladder methods. The classical chain-ladder is a deterministic algorithm to forecast claims based on historical data. It assumes that the proportional developments of claims from one development period to the next are the same for all origin years.
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What is chain-ladder bias?
We propose a new estimator for the ultimate prediction uncertainty within the famous Mack’s distribution-free chain-ladder model, which can be proved to be unbiased (conditionally given the first triangle column) under some additional technical assumptions.
