Tail distribution and extreme quantile estimation using non-parametric approaches

Abstract

Estimation of tail distributions and extreme quantiles is important in areas such as risk management in finance and insurance in relation to extreme or catastrophic events. The main difficulty from the statistical perspective is that the available data to base the estimates on is very sparse, which calls for tailored estimation methods. In this chapter, we provide a survey of currently used parametric and non-parametric methods, and provide some perspectives on how to move forward with non-parametric kernel-based estimation.