Affordable Access

Value-at-Risk and least squares tail index estimation



The empirical evidence of heavy tails in stock return data is recognised by risk managers as an important factor in assessing the Value-at-Risk and risk profile of investment portfolios. Tail index estimation appears to be a tailor-made tool for estimating the extreme quantiles of heavy tailed distributions, as it exploits the information provided by the extreme observations. The tail shape of heavy tailed distributions resembles-to a first approximation-the hyperbolic shape of the Pareto distribution characterised by the so-called tail index. Ususally, a Hill-type estimator is used to estimate this tail index. This paper takes a new approach that hinges to a lesser extent on the choice of the treshold level and is easier to apply, by estimating the tail shape via least squares.

There are no comments yet on this publication. Be the first to share your thoughts.


Seen <100 times