News aware volatility forecasting: is the content of news important?

Robertson, Calum S., Geva, Shlomo and Wolff, Rodney C. (2007). News aware volatility forecasting: is the content of news important?. In: Peter Christen, Paul Kennedy, Jiuyong Li, Inna Kolyshkina and Graham Williams., Data Mining and Analytics 2007: Proceedings of the Sixth Australasian Data Mining Conference (AusDM2007). AusDM 2007: 6th Australasian Data Mining Conference, Gold Coast, QLD, Australia, (161-170). 3-4 December, 2007.

Author Robertson, Calum S.
Geva, Shlomo
Wolff, Rodney C.
Title of paper News aware volatility forecasting: is the content of news important?
Conference name AusDM 2007: 6th Australasian Data Mining Conference
Conference location Gold Coast, QLD, Australia
Conference dates 3-4 December, 2007
Proceedings title Data Mining and Analytics 2007: Proceedings of the Sixth Australasian Data Mining Conference (AusDM2007)
Journal name Conferences in Research and Practice in Information Technology
Place of Publication Sydney, NSW, Australia
Publisher Australian Computer Society
Publication Year 2007
Sub-type Fully published paper
Open Access Status
ISBN 9781920682514
ISSN 1445-1336
Editor Peter Christen
Paul Kennedy
Jiuyong Li
Inna Kolyshkina
Graham Williams.
Volume 70
Start page 161
End page 170
Total pages 10
Language eng
Formatted Abstract/Summary
The efficient market hypothesis states that the market incorporates all available information to provide an accurate valuation of the asset at any given time. However, most models for forecasting the return or volatility of assets completely disregard the arrival of asset specific news (i.e., news which is directly relevant to the asset). In this paper we propose a simple adaptation to the GARCH model to make the model aware of news. We propose that the content of news is important and therefore describe a methodology to classify asset specific news based on the content. We present evidence from the US, UK and Australian markets which show that this model improves high frequency volatility forecasts. This is most evident for news which has been classified based on the content. We conclude that it is not enough to know when news is released, it is necessary to interpret its content.
Keyword Stock markets
News
Document Classification
Volatility
Forecast
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Conference Paper
Collection: W.H. Bryan Mining Geology Research Centre
 
Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Tue, 17 Jun 2014, 15:57:31 EST by Rodney Wolff on behalf of WH Bryan Mining and Geology Centre