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Cape Cod Method Definition
Cape Cod method is used in calculating ultimate losses in loss reserves. Losses are projected through the Cape Cod method by measuring both loss exposure and loss development that occur in a year. There are diverse volume measures that estimate the loss reserves for historical accident years. The Cape Cod method, however, uses peculiar volume measures to project ultimate losses for all accident years.
Sometimes, the Cape Cod method is otherwise called the Stanard-Buhlmann method.
A Little More on What is the Cape Cod Method
The Cape Cod method is identified as a framework or an extension under the Bornhuetter-Ferguson method. It is a method that projects loss development as well as patterns that signal ultimate losses in accident years. The Cape Cod method uses approaches that are more comprehensive than other methods, for example, many volume measures, even the Bornhuetter-Ferguson methods use external information to calculate loss reserves for accident years. The Cape Cod method , however, uses both internal and external information for ultimate loss calculations. The Cape Cod method calculates loss reverses by dividing the loss to date by exposure, then dividing it by the ultimate loss development. Cumulative losses are also estimated by the Cape Cod.
Loss Reserving in the Cape Cod Method
The calculation of loss reserves using the Cape Cod method requires that consideration is given to weights proportional to loss exposure and weights inversely proportional to loss development. Loss reserving also entails that prior estimators of development patterns are identified and patterns of expected ultimate losses. The Bornhuetter-Ferguson framework contributed to the development of the Cape Cod method.
Limitations of the Cape Cod Method
There are certain limitations of the Cape Cod method, they are identified below;
- The Cape Cod method fails to give any regard to variability that is bound to occur in historical accidents years and historical loss estimates and other factors.
- The Cape Cod method cannot be used when estimating reported losses (IBNR), it is often used for the calculation of incurred losses.
- Another drawback of the Cape Cod method is that current experience has little weight as compared to historical experience which is accorded more importance.
Despite its shortcomings, when combined with the chain-ladder method and exposure-based method, Cape Cod method can achieve the best result.
Reference for “Cap Cod Method’
Academic research on “Cap Cod Method”
Using best practices to determine a best reserve estimate, Struzzieri, P. J., Hussian, P. R., & Plaza, T. P. (1998). Using best practices to determine a best reserve estimate. In CAS Forum (pp. 353-413).
A simulation test of prediction errors of loss reserve estimation techniques, Stanard, J. N. (1985). A simulation test of prediction errors of loss reserve estimation techniques (Doctoral dissertation, New York University, Graduate School of Business Administration). This paper uses a computer simulation model to measure the expected value and variance of prediction errors of four simple methods of estimating loss reserves. Two of these methods are new to the Proceedings. The simulated data triangles that are tested are meant to represent sample sizes typically found in individual risk rating situations. The results indicate that the commonly used age-to-age factor approach gives biased estimates and is inferior to the three other methods tested. Theoretical arguments for the source of this bias and a comparison of two of the methods are presented in the Appendices.
Using expected loss ratios in reserving, Gogol, D. (1993). Using expected loss ratios in reserving. Insurance: Mathematics and Economics, 12(3), 297-299. The required loss reserve for a recent time period is estimated by using the recent loss experience plus two probability distributions. One distribution is of ultimate losses for the recent period, based on prior experience and rate adequacy changes. The other distribution is of the ratio of the estimator based on recent experience to the true ultimate loss.
Estimating predictive distributions for loss reserve models, Meyers, G. G. (2007). Estimating predictive distributions for loss reserve models. Variance, 1(2), 248-272.
LDF curve-fitting and stochastic reserving: a maximum likelihood approach, Clark, D. R. (2003, May). LDF curve-fitting and stochastic reserving: a maximum likelihood approach. In CAS Forum(Vol. 3, No. 4, pp. 41-92).