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Balanced quantile regression credibility models with inflation factor. (Chinese. English summary) Zbl 1463.91108

Summary: Insurance data often appear as spikes or thick tails, but the classical reliability model does not effectively reflect the distribution of upper and lower-end information. This paper considers the safety load of premiums and the impact of inflation on the amount of coverage for future insurance periods. From the quantile perspective, the mean square loss is replaced by the balanced loss. By using the sample quantile to make full use of the information of all data, a quantile reliability model with inflation factor is established. Moreover, it extends the classical reliability model and provides insurance companies with different weights according to the actual situation. Finally, a more realistic premium approach can be developed.

MSC:

91G05 Actuarial mathematics
62P05 Applications of statistics to actuarial sciences and financial mathematics
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