IDEAS home Printed from https://ideas.repec.org/a/rsk/journ0/7951861.html
   My bibliography  Save this article

Subsampling and other considerations for efficient risk estimation in large portfolios

Author

Listed:
  • Michael B. Giles
  • Abdul-Lateef Haji-Ali

Abstract

Computing risk measures of a financial portfolio comprising thousands of derivatives is a challenging problem both because it involves a nested expectation requiring multiple evaluations of the loss of the financial portfolio for different risk scenarios and because evaluating the loss of the portfolio is expensive and the cost increases with portfolio size. We apply multilevel Monte Carlo simulation with adaptive inner sampling to this problem and discuss several practical considerations. In particular, we discuss a subsampling strategy whose computational complexity does not increase with the size of the portfolio. We also discuss several control variates that significantly improve the efficiency of multilevel Monte Carlo in our setting.

Suggested Citation

Handle: RePEc:rsk:journ0:7951861
as

Download full text from publisher

File URL: https://www.risk.net/system/files/digital_asset/2022-08/jcf_Hajiali_web_final.pdf
Download Restriction: no
---><---

More about this item

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rsk:journ0:7951861. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thomas Paine (email available below). General contact details of provider: https://www.risk.net/journal-of-computational-finance .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.