NONOPTIMAL PREDICTION BY THE CHAIN LADDER METHOD

The chain ladder method is one of the most common methods for reservin g, and various attempts have been made to justify it in a stochastic m odel. A particularly interesting model was proposed by Mack (1993, 199 4a,b): Under the assumptions of his model, Mack proved that the chain ladder predictors of non-observable aggregate claims are unbiased, and Schmidt and Schnaus (1996) proved that the chain ladder predictor for the first non-observable calendar year is also optimal in the sense t hat it minimizes expected squared error loss over a wide class of unbi ased predictors. In the present paper, it is shown that optimality fai ls for the chain ladder predictor for the second non-observable calend ar year. (C) 1997 Elsevier Science B.V.