IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

An alternative methodological approach to assess the predictive performance of the moving average trading rule in financial markets: application to the london stock exchange

  • Alexandros E. Milionis

    ()

    (Bank of Greece and University of the Aegean)

  • Evangelia Papanagiotou

    (University of the Aegean)

In this work a modification of the Box-Tiao methodology for the assessment of the impact of external events on time series is proposed as an alternative statistical approach of assessing the predictive performance of the moving average trading rule in financial markets. With the proposed methodology measures of the predictive performance of the moving average trading rule can be simultaneously estimated, while at the same time controlling for autocorrelation in the series of asset returns. The potential advantages of the proposed methodology over the existing ones are discussed. Application of this alternative methodology to the returns of the FT30 Index of the London Stock Exchange shows good agreement with the empirical findings of other methods.

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: http://www.bankofgreece.gr/BogEkdoseis/Paper2010107.pdf
File Function: Full Text
Download Restriction: no

Paper provided by Bank of Greece in its series Working Papers with number 107.

as
in new window

Length: 30
Date of creation: Dec 2009
Date of revision:
Handle: RePEc:bog:wpaper:107
Contact details of provider: Web page: http://www.bankofgreece.gr

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:bog:wpaper:107. 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: (Christina Tsochatzi)

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.