Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH-MIDAS Approach
Southern Denmark University, Denmark.
2013 (English)In: Journal of Forecasting, ISSN 0277-6693, E-ISSN 1099-131X, Vol. 32, no 7, 600-612 p.Article in journal (Refereed) Published
Abstract [en]

This paper aims to examine the role of macroeconomic variables in forecasting the return volatility of the US stock market. We apply the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict shortterm and long-term components of the return variance. We investigate several alternative models and use a large group of economic variables. A principal component analysis is used toincor porate the information contained in different variables. Our results show that including low frequency macroeconomic information into the GARCH-MIDAS model improves the prediction ability of the model, particularly for the long-term variance component. Moreover, the GARCHMIDAS model augmented with the first principal component outperforms all other specifications, indicating that the constructed principal component can be considered as a good proxy of the business cycle.

Place, publisher, year, edition, pages
2013. Vol. 32, no 7, 600-612 p.
Keyword [en]
Mixed data sampling, long-term variance component, macroeconomic variable, principal component, variance prediction
National Category
Economics
Identifiers
URN: urn:nbn:se:su:diva-116075DOI: 10.1002/for.2256OAI: oai:DiVA.org:su-116075DiVA: diva2:802195
Available from: 2015-04-11 Created: 2015-04-11 Last updated: 2017-12-04Bibliographically approved

Open Access in DiVA

fulltext(1237 kB)228 downloads
File information
File name FULLTEXT01.pdfFile size 1237 kBChecksum SHA-512
ae250909985c5567caf992a91b83d82d0fbd9a17d6021f0fc3a6d07be00c6ece0789ea171a5e035eb23407402c28c2b0affa8d873ca9fc50d05558d0709d4dfe
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Hou, Ai Jun
In the same journal
Journal of Forecasting
Economics

Search outside of DiVA

GoogleGoogle Scholar
Total: 228 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 508 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf