IDEAS home Printed from https://ideas.repec.org/a/rsk/journ0/2160368.html
   My bibliography  Save this article

Correlation matrix with block structure and efficient sampling methods

Author

Listed:
  • Jinggang Huang, Liming Yang

Abstract

ABSTRACT Random sampling from a multivariate normal distribution is essential for Monte Carlo simulations in many credit risk models. For a portfolio of N obligors, standard methods usually require O(N2) calculations to get one random sample. In many applications, the correlation matrix has a block structure that, as we show, can be converted to a “quasi-factor” model. As a result, the cost to get one sample can be reduced to O(N). Such a conversion also enables us to check whether a user-defined “correlation” matrix is positive semidefinite and “fix” it if necessary in an efficient manner.

Suggested Citation

Handle: RePEc:rsk:journ0:2160368
as

Download full text from publisher

File URL: https://www.risk.net/system/files/import/protected/digital_assets/10350/Correlation_matrix_with_block_structure_and_efficient_sampling_methods.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:journ0:2160368. 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.