Predictive Modeling Applications in Actuarial Science

Chapter 10 - Fat-Tailed Regression Models


Peng Shi | University of Wisconsin-Madison

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In the actuarial context, fat-tailed phenomena are often observed where the probability of extreme events is higher than that implied by the normal distribution. The traditional regression, emphasizing the center of the distribution, might not be appropriate when dealing with data with fat-tailed properties. Overlooking the extreme values in the tail could lead to biased inference for ratemaking and valuation. In response, this chapter discusses four fat-tailed regression techniques that fully utilize the information from the entire distribution: transformation, models based on the exponential family and on generalized distributions, and median regression.

Data R Code
Section 3
Section 4.3(SAS Code)
Section 5