Semiparametric Density Forecasts of Daily Financial Returns from Intraday Data
In this article we propose a new method for producing semiparametric density forecasts for daily financial returns from high-frequency intraday data. The daily return density is estimated directly from intraday observations that have been appropriately rescaled using results from the theory of unifractal processes. The method preserves information concerning both the magnitude and sign of the intraday returns and allows them to influence all properties of the daily return density via the use of nonparametric specifications for the daily return distribution. The out-of-sample density forecasting performance of the method is shown to be competitive with existing methods based on intraday data for exchange rate and equity index data. (JEL: C58, C22, G17)
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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 12 (2014)
Issue (Month): 2 ()
|Contact details of provider:|| Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK|
Fax: 01865 267 985
Web page: http://jfec.oxfordjournals.org/
More information through EDIRC
|Order Information:||Web: http://www.oup.co.uk/journals|
When requesting a correction, please mention this item's handle: RePEc:oup:jfinec:v:12:y:2014:i:2:p:408-432.. 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: (Oxford University Press)or (Christopher F. Baum)
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.