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News Aware Volatility Forecasting: Is the Content of News Important?

Robertson, Calum S., Geva, Shlomo, & Wolff, Rodney C. (2007) News Aware Volatility Forecasting: Is the Content of News Important? In Christen, Peter, Kennedy, Paul, Li, Jiuyong, Kolyshkina, Inna, & Williams, Graham (Eds.) Sixth Australasian Data Mining Conference (AusDM 2007), 3-4 December, Gold Coast, Queensland, Australia. (In Press)

Abstract

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.

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ID Code: 10460
Item Type: Conference Paper
Additional URLs:
Keywords: Stock Market, News, Document Classification, Volatility, Forecast
ISBN: 9781920682514
ISSN: 1445-1336
Subjects: Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > ECONOMETRICS (140300) > Econometric and Statistical Methods (140302)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Expert Systems (080105)
Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > ECONOMETRICS (140300) > Time-Series Analysis (140305)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > ECONOMETRICS (140300) > Economic Models and Forecasting (140303)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Natural Language Processing (080107)
Divisions: Current > QUT Faculties and Divisions > QUT Business School
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2007 Australian Computer Society
Copyright Statement: Reproduction for academic research and not-for-profit purposes is granted provided the copyright notice on the first page of each paper is included.
Deposited On: 29 Oct 2007
Last Modified: 29 Feb 2012 23:31

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