This paper proposes efficient estimators of risk measures in a semiparametric GARCH model defined through moment constraints. Moment constraints are often used to identify and estimate the mean and variance parameters and are however discarded when estimating error quantiles. In order to prevent...

This paper proposes efficient estimators of risk measures in a semiparametric GARCH model defined through moment constraints. Moment constraints are often used to identify and estimate the mean and variance parameters and are however discarded when estimating error quantiles. In order to prevent...

Robustness of risk measures to changes in underlying loss distributions (distributional uncertainty) is of crucial importance when making well-informed risk management decisions. In this paper, we quantify for any given distortion risk measure its robustness to distributional uncertainty by...

In the same spirit as the Mack standard deviation for non-life reserves, which can be estimated with a closed-form formula applied to a loss development triangle (see Mack 1993), this article introduces a closed-form formula to estimate the skewness of non-life reserves which can also be applied...

The paper is concerned with loss reserving at the individual claim level (also referred to as micro-reserving or granular reserving) in the context of workers compensation, or similar income replacement insurance. The individual claim reserve is constructed on the basis of detailed information,...

Here we make several comments concerning the full nonparametric Bayesian approach that motivated the new techniques in the paper "Credibility estimation of distribution functions with applications to experience rating and general insurance,'' by Cai, Wen, Wu, and Zhou, published in the North...

With the emergence of telematics car driving data, insurance companies start to boost classical actuarial regression models for claim frequency prediction. In this paper, we propose two data-driven neural network approaches that process telematics car driving data to construct driving behavior...

The structure of a typical rainfall insurance is complex; insurance payoffs are based on many parameters such as the rainfall volume, the rainfall distribution (the number of consecutive dry days), the number of days with excess rainfall etc. Such a complex insurance structure is essential to...

Maximum likelihood estimation has been the workhorse of statistics for decades, but alternative methods, going under the name “regularization,” are proving to have lower predictive variance. Regularization shrinks fitted values towards the overall mean, much like credibility does. There is...

In recent literature, a new class of unbiased Monte Carlo estimators have been proposed, which is based on truncating a telescopic representation of the expectation of a functional of the stochastic process at an independent random level. The generality of the method lies in that it can...