Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25026
Appears in Collections:Economics Journal Articles
Peer Review Status: Refereed
Title: Non-linear predictability of UK stock market returns
Author(s): McMillan, David
Contact Email: david.mcmillan@stir.ac.uk
Issue Date: Dec-2003
Date Deposited: 27-Feb-2017
Citation: McMillan D (2003) Non-linear predictability of UK stock market returns. Oxford Bulletin of Economics and Statistics, 65 (5), pp. 557-573. https://doi.org/10.1111/j.1468-0084.2003.00061.x
Abstract: Linear predictability of stock market returns has been widely reported. However, recently developed theoretical research has suggested that due to the interaction of noise and arbitrage traders, stock returns are inherently non-linear, whereby market dynamics differ between small and large returns. This paper examines whether an exponential smooth transition threshold model, which is capable of capturing this non-linear behaviour, can provide a better characterization of UK stock market returns than either a linear model or an alternate non-linear model. The results of both in-sample and out-of-sample specification tests support the exponential smooth transition threshold model and hence the belief that investor behaviour does differ between large and small returns.
DOI Link: 10.1111/j.1468-0084.2003.00061.x
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Licence URL(s): http://www.rioxx.net/licenses/under-embargo-all-rights-reserved

Files in This Item:
File Description SizeFormat 
McMillan-2003-Oxford_Bulletin_of_Economics_and_Statistics.pdfFulltext - Published Version122.66 kBAdobe PDFUnder Embargo until 2999-12-16    Request a copy

Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.



This item is protected by original copyright



Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.