Skip to main content

Main menu

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JOD
    • Editorial Board
    • Published Ahead of Print (PAP)
  • IPR Logo
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

User menu

  • Sample our Content
  • Request a Demo
  • Log in

Search

  • ADVANCED SEARCH: Discover more content by journal, author or time frame
The Journal of Derivatives
  • IPR Logo
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Sample our Content
  • Request a Demo
  • Log in
The Journal of Derivatives

The Journal of Derivatives

ADVANCED SEARCH: Discover more content by journal, author or time frame

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JOD
    • Editorial Board
    • Published Ahead of Print (PAP)
  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter
Primary Article

An Empirical Evaluation of Value at Risk by Scenario Simulation

Peter A. Abken
The Journal of Derivatives Summer 2000, 7 (4) 12-29; DOI: https://doi.org/10.3905/jod.2000.319138
Peter A. Abken
A senior financial economist in the Risk Analysis Division at the Office of the Comptroller of the Currency in Washington, D.C.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Info & Metrics
  • PDF (Subscribers Only)
Loading

Abstract

It has become standard practice for banks and financial institutions to calculate value at risk and similar measures of portfolio risk exposure on a regular basis. Typically, Monte Carlo simulation of fairly complex models is required. This creates a potentially enormous computational burden, especially when assets in multiple currencies are involved, that limits both the accuracy and the frequency that is feasible for the analysis. Using principal components to reduce the dimensionality of the set of underlying risk factors helps, but the need to revalue a large number of assets in each simulation run is still a major impediment. One recent suggestion has been to restrict each risk factor to take only a small number of distinct values, leading to a small (or, at last, manageable) number of possible “scenarios,” each corresponding to a portfolio value that only needs to be computed once. Monte Carlo simulation is then done by sampling among these scenarios, leading to a great reduction in the number of portfolio revaluations required. In this article, Abken explains these techniques in detail and examines their relative performance on a portfolio involving interest rate derivatives. Unfortunately, he finds that scenario simulation only converges slowly to the correct limiting values, and convexity of the derivative values significantly impairs the performance of scenario simulation relative to standard Monte Carlo.

  • © 2000 Pageant Media Ltd

Don’t have access? Click here to request a demo

Alternatively, Call a member of the team to discuss membership options

US and Overseas: +1 646-931-9045

UK: 0207 139 1600

Log in using your username and password

Forgot your user name or password?
PreviousNext
Back to top

Explore our content to discover more relevant research

  • By topic
  • Across journals
  • From the experts
  • Monthly highlights
  • Special collections

In this issue

The Journal of Derivatives
Vol. 7, Issue 4
Summer 2000
  • Table of Contents
  • Index by author
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on The Journal of Derivatives.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
An Empirical Evaluation of Value at Risk by Scenario Simulation
(Your Name) has sent you a message from The Journal of Derivatives
(Your Name) thought you would like to see the The Journal of Derivatives web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
An Empirical Evaluation of Value at Risk by Scenario Simulation
Peter A. Abken
The Journal of Derivatives May 2000, 7 (4) 12-29; DOI: 10.3905/jod.2000.319138

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Save To My Folders
Share
An Empirical Evaluation of Value at Risk by Scenario Simulation
Peter A. Abken
The Journal of Derivatives May 2000, 7 (4) 12-29; DOI: 10.3905/jod.2000.319138
del.icio.us logo Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Tweet Widget Facebook Like LinkedIn logo

Jump to section

  • Article
  • Info & Metrics
  • PDF (Subscribers Only)
  • PDF (Subscribers Only)

Similar Articles

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • A Comparison of Markov–Functional and Market Models
  • Price Hedging with Local and Aggregate Quantity Risk
  • Delivery Options and Treasury–Bond Futures Hedge Ratios
Show more Primary Article
LONDON
One London Wall, London, EC2Y 5EA
United Kingdom
+44 207 139 1600
 
NEW YORK
41 Madison Avenue, New York, NY 10010
USA
+1 646 931 9045
pm-research@pageantmedia.com
 

Stay Connected

  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

MORE FROM PMR

  • Home
  • Awards
  • Investment Guides
  • Videos
  • About PMR

INFORMATION FOR

  • Academics
  • Agents
  • Authors
  • Content Usage Terms

GET INVOLVED

  • Advertise
  • Publish
  • Article Licensing
  • Contact Us
  • Subscribe Now
  • Log In
  • Update your profile
  • Give us your feedback

© 2022 Pageant Media Ltd | All Rights Reserved | ISSN: 1074-1240 | E-ISSN: 2168-8524

  • Site Map
  • Terms & Conditions
  • Privacy Policy
  • Cookies