Scaling conditional tail probability and quantile estimators

John Cotter presents a novel procedure for scaling relatively high-frequency tail probability and quantile estimates for the conditional distribution of returns

A key issue for risk management is to decide the relevant horizon associated with risk measurement. Many different horizons may be relevant, from short (for example, daily) to long (for example, monthly) time frames, and a risk manager must be able to provide measures across a range of horizons.1 This article measures risk at different horizons using volatility forecasts at high frequency as inputs that are then scaled for longer horizons.

[image] - Scaling conditional tail probability and

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact or view our subscription options here:

You are currently unable to copy this content. Please contact to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here