IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Kalman Filtering and Online Learning Algorithms for Portfolio Selection

Listed author(s):
  • Raphael Nkomo and Alain Kabundi

This paper proposes a new online learning algorithms for portfolio selection based on alternative measure of price relative called the Cyclically Adjusted Price Relative (CAPR). The CAPR is derived from a simple state-space model of stock prices and we prove that the CAPR, unlike the standard raw price relative widely used in the machine literature, has well deÂ…ned and desirable statistical properties that makes it better suited for nonparametric mean reversion strategies. We find that the statistical evidence of out-of-sample predictability of stock returns is stronger once stock price trends are adjusted for high persistence. To demonstrate the robustness of our approach we perform extensive historical simulations using previously untested real market datasets. On all datasets considered, our proposed algorithms significantly outperform their comparative benchmark allocation techniques without any additional computational demand or modeling complexity.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Paper provided by Economic Research Southern Africa in its series Working Papers with number 394.

in new window

Length: 26 pages
Date of creation: 2013
Handle: RePEc:rza:wpaper:394
Contact details of provider: Postal:
Newlands on Main, F0301 3rd Floor Mariendahl House, cnr Campground and Main Rds, Claremont, 7700 Cape Town

Phone: 021 671-3980
Fax: +27 21 671 3912
Web page:

More information through EDIRC

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:rza:wpaper:394. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Charles Tanton)

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.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.