A New Method to Choose the Threshold in the POT Model

Abstract

The selection of an appropriate threshold is one of the main concerns about the POT (Peaks Over Threshold ) model, which is widely used in many fields, such as in insurance and environmental analysis. In this article, a new method which is based on the MSE criterion and two-sample K-S tests is proposed to determine the optimal threshold in the GPD model. Different from the traditional subjective methods, the proposed method can determine the threshold by quantification, and is easy to be implemented by a computer program. An empirical study using the daily returns of S&P 500 index is also presented. It's shown that the proposed method can well capture the optimal threshold.

4 Figures and Tables

Showing 1-10 of 11 references

A introduction to statistical modeling of extreme value

  • S C Coles
  • 2001
1 Excerpt

Tail index and quantile estimation with very high frequency data

  • J Danielsson, C G De Vries
  • 1997
1 Excerpt

Bayesian methods in extreme value model: a review and new developments

  • S G Coles, E A Powell
  • 1996

On the frequency of large stock returns: putting booms and busts into perspectives

  • D W Jansen, C G De, Vries
  • 1991

Models for exceedances over high thresholds " (with comments)

  • A C Davison, R L Smith
  • 1990

Estimating tails of probability distributions

  • R L Smith
  • 1987

Parameter and quantile estimation for the generalized pareto distribution

  • J R M Hosking, Wallis
  • 1987

Statistical inference using extreme order statistics

  • J Pickands
  • 1975
1 Excerpt